This article is authored in conjunction with iMoney. For further information regarding iMoney’s services, please contact them via their website or drop an email at marketing@imoney.my.

From computer software to the streaming industry, the successful implementation of hyper-personalisation has seen companies reaping big rewards such as Netflix adding 9 million subscribers in the first quarter of this year. 

Customers and consumers today want that personalised “Netflix” experience as part of their daily services; exceptionally relevant product suggestions that are provided in real-time.

The same goes for financial services that we use as part of our daily life to save, invest or apply for a loan. This begs the question, “Why aren’t more key decision-makers in the banking and finance industry integrating it into their operations?”

In this article, we will explain and explore a few of the benefits and challenges that those in the banking and finance industry face when it comes to implementing hyper-personalisation solutions. 

Ultimately, banks must integrate and nurture hyper-personalisation into their architecture as the cost of ignoring can be too big for banks and financial institutions (FI) to ignore.

What is Hyper-personalisation in Banking?

Hyper-personalisation in banking is the utilisation of machine learning (ML) and artificial intelligence (AI) technology to thoroughly understand and create highly customised financial services and products tailored to the needs and preferences of individual customers.

Using customer data, such as demographic information and transaction histories, banks can build detailed profiles of their customers to offer personalised and bespoke banking experiences.

While traditional AI has set the stage for personalisation in banking, Generative AI (GenAI) advances this with more dynamic and intuitive features. It understands customer needs better. It creates more engaging and personalised content. It provides scalable solutions that adapt to changing financial environments. This leads to a more personalised and satisfying banking experience for customers. Read here to find out more on how GenAI is emerging in the Banking and Financial Services industries. 

Building Detailed KYC/customer Personas 

Banks can further hone their customer personas and strengthen their know-your-customer (KYC) standards by using big data combined with ML and AI technology. 

This provides a deeper understanding of their customers, going beyond just the standard demographic data. By pulling from external sources such as social media and utilising past interactions, banks can create customer personas that will help them deliver personalised experiences.

Netflix is a prime example of how using the vast data they have acquired through the years to build a customer persona that allows them to provide personalised recommendations and improve their user retention.

Analysing and Understanding Customer Data 

To fully utilise these personas will require a strong foundation in the bank’s abilities to harness, analyse, and understand big data. With data, banks can pull key insights that help build their customer personas. These insights can be broken down into the following three:

• Descriptive insights – Visualises and explains the behaviour/nuances of customers’ spending patterns, transactions, assets, etc.
• Diagnostic insights – Providing the answers to the ‘hows’ and ‘whys’ of customers to better understand customer behaviours.
• Predictive insights – To help banks foresee a customer’s financial health and to alert them on potential issues such as cash flow, unplanned large payments, or penalties. This allows banks to anticipate their customers’ needs and create customised solutions when needed.

By better understanding the data acquired and the type of available insights, banks and FIs can make better decisions on creating and developing experiences that will resonate with their customers.

Creating Customised/Personalised Banking Experiences

Hyper-personalisation is not just big data. It moves beyond ‘data-driven’ and focuses on better understanding customers’ emotional state and the context behind it, allowing you to respond/nudge the customer suitably. 

The combination of convenience, customer engagement, and emotional engagement can lead to stronger loyalty in customers, which will eventually lead to higher conversions. Plus customers are 80% more likely to purchase from a company that offers such personalised experiences.

With the advent of GenAI, hyper-personalisation in banking has reached new heights. Recent surveys show that 91% of financial services companies are either evaluating or using AI technologies. A significant number focus on GenAI to drive innovation, improve efficiency, and enhance customer experiences. Additionally, 63% of European financial services leaders are optimistic about GenAI’s potential to transform their operations. This advanced technology enhances user engagement and greatly boosts customer retention by offering a more intuitive and personalised banking experience. Here are some compelling use cases showing the transformative impact of GenAI in banking:

• Advanced Automated Customer Interaction: A GenAI-powered chatbot is capable of enhancing customer service by providing accurate, context-aware responses, leading to improved customer satisfaction and retention.
• Real-Time Data Analytics: GenAI analyses real-time transaction data to predict and suggest personalised financial products to customers, such as customised loan options based on their current spending patterns and financial behaviour.
• Customised Product and Service Development: GenAI helps banks develop new financial products tailored to specific customer segments, such as bespoke investment packages for young professionals or retirement plans for seniors.
• Enhanced Fraud Detection and Security: GenAI monitors transactions in real-time, learning and adapting to detect and respond to fraudulent activities specific to each customer’s transaction habits, improving security measures.

How Failing to Utilise Hyper-personalisation Can Be Costly for Banks

While the opportunities for growth and improving the performance of banks and FIs can be limitless with hyper-personalisation, the cost of ignoring or failing to integrate it on time can be devasting. 

Unsatisfactory customer experiences for banks have led to customer defections, with the lack of personalised experiences being a key point. The study by Standard & Poor highlights how customer loyalty will waver without these personalised experiences with responses by consumers who are willing to switch from one bank to another if they provide “better mobile app experiences” (39%) and “better customer experience” (38%).

But beyond losing customers, banks that fail to utilise hyper-personalisation will face significant business impacts. A study by Forrester highlights the major costs that banks faced such as increased costs (62%), slowed business agility (60%), poor customer experience (56%), and lost operational resilience (54%).

Ignoring or failing to use hyper-personalisation can be detrimental to your growth and profitability. At the same time, it’s also important to understand why banks and FIs are failing so that leaders can avoid making the same mistakes.

Reasons Why Most Banks Fail to Utilise Hyper-personalisation

The banking industry is particularly suited to adopt hyper-personalisation given its large customer bases and high amount of data per customer. However, banks and FIs are not fully harnessing what hyper-personalisation has to offer due to a myriad of reasons. 

Legacy Technology and Systems

The World Retail Banking Report 2022 pointed out the fact that legacy technology and systems remain the biggest hurdle for banks and FIs. 95% of its surveyed executives believe their outdated legacy systems and technological capabilities make it hard to fully optimise their data for customer-centric growth strategies.

Legacy technology and systems have made it difficult for banks to access the potential goldmine of customer data, which has seen banks needing the ability to fully harness data analytics or behavioural science to increase the utility of their products. 

Strict Data Regulations and Compliances

In addition to facing legacy technology issues, banks also face strict regulations in the form of stringent customer protection and data privacy and security regulations, which also act as perceived constraints towards the adoption of hyper-personalisation. 

Given that hyper-personalisation relies on huge amounts of data collection, there are raising concerns among users regarding their privacy and how it is protected. Add to that privacy regulations such as the GDPR and CCPA, banks and FIs have to ensure that they are collecting and using data in a compliant manner.

Taking the Initiative to Integrate Hyper-personalisation

So, how do banks overcome these costly challenges and start taking advantage of hyper-personalisation?

It all starts with investing and setting up a comprehensive data infrastructure. With the right technology, banks can ensure that the right personalised data is captured and is shareable across all other systems.

From investing in the right platform and building up a data-centric vision to integrating hyper-personalisation, there are numerous ways that banks and FIs can approach this. 

Hyper-personalisation in JurisTech’s Digital Onboarding Platform

A survey conducted by Gladly showed that 59% of customers value personalisation when it comes to their onboarding/customer service experience over speed. For banks and FIs, a hyper-personalised digital onboarding platform is a necessity to keep up with the growing needs and demands of its customers.

JurisTech’s digital onboarding platform tackles these demands through two major approaches:

1. Personalised Application Journeys:
   1. Tailor intuitive application journeys for various financial products, such as car loans, personal loans, auto-financing, and mortgages.
   2. Incorporates pre-approval steps, virtual viewing options, and personalised product recommendations to enhance customer experience.
2. AI-Powered Capabilities:
   1. Reduces costs by improving customer conversion rates and lowering acquisition costs through enhanced sales processes.
   2. Increases revenue by providing AI-driven product recommendations, cross-selling, and upselling opportunities.
   3. Offers valuable insights into customer behaviour, enabling predictive analytics for churn prediction and Loan-to-Value (LTV) assessment. 

Implementation of JurisTech’s digital onboarding platform has led to proven results within the financial industries with corporations and financial institutions being able to improve client experiences and simplify corporate processes, such as fast and precise customer onboarding with straight-through processing, enhanced security measures for you and your customers’  peace of mind, ease of use with low-code/no-code technology, and fast scalability through compatibility with all standard APIs. 

Hyper-personalisation in JurisTech’s Debt Collection System

Basic personalisation is not enough in the modern collection space. Ensuring that banks and FIs can clear accounts in a scalable manner and not impact customer retention will require a personalised experience at every step of the journey.

As such, JurisTech’s debt collection system offers personalised collection strategies with the following capabilities:

1. Profiles customers into different segments based on criteria such as product type, risk value, geographic location, and days past due (DPD).
2. Creates personalised collection strategies for each segment to maximise effectiveness and increase collection rates.  

In addition, JurisTech’s debt collection system takes full advantage of AI-driven predictive analytics and offers the following benefits:

1. Predicts self-curing accounts and potential non-performing loans (NPL) customers using behavioural scoring and AI analytics, improving revenue forecasting accuracy.
2. Maximises revenue collection through the Whiz strategy manager, which simplifies strategy management and allows experimentation with different approaches.

Attract, Keep and Expand Customer Loyalty With Hyper-personalisation

As part of the digital transformation movement, banks and FIs will need to commit to adopting and integrating hyper-personalisation in their key services, which can act as a key differentiator for success. 

By utilising solutions and platforms such as JurisTech’s debt collection system and digital onboarding platform, they will take another step towards taking full advantage of what hyper-personalisation has to offer and maximising growth and profitability.

About JurisTech

JurisTech is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, telecommunications, and automobile companies globally.

We power economies by reimagining financial services with cutting-edge software solutions, which includes artificial intelligence (AI), auto-decisioning, digital customer onboarding, loan origination, credit scoring, loan documentation, litigation, and debt collection.

Our solutions have enabled businesses across a broad array of industries to undergo digital transformation, providing enhanced customer experiences and, most importantly, achieving their business goals.

About iMoney.my

iMoney.my (Intelligent Money) is an award-winning financial intelligence centre that helps simplify personal financial decision-making for Malaysians. Since we started in 2012, our purpose has remained to help people reach their goals through good money decisions.

From tools to jargon-free advice, we make it easy for our users to find the right financial products, apply for them online, and learn about financial tips and tools through insightful articles and financial tools.

The post The Monumental Price Banks Pay For Overlooking Hyper-Personalisation appeared first on JurisTech.

The demand for fully digital onboarding services is increasing, and the banking and financial services sector is realising that it needs hyper-personalised digital onboarding platforms to keep up. Digital onboarding in the financial industry is an automated process that provides customers with access to financial products and services such as opening a bank account, taking out a loan, or setting up an account with a digital bank or neobank. Numerous business advantages come with digital onboarding, including improved fraud prevention, reduced expenses, and a quicker and better user experience.

As per a Forbes article, artificial intelligence (AI) is expected to have a significant impact on the banking and investment sectors, transforming customer service and offering more efficient solutions. Furthermore, according to a Gartner Research study, 62% of banks place a high priority on developing new goods and services, including digital onboarding services. Additionally, clients can now access fully digital onboarding services via mobile devices thanks to the online platforms that are replacing traditional banking services, making the process more convenient and seamless.

The Advantages of JurisTech’s Digital Onboarding Platform

With JurisTech’s digital onboarding platform, financial institutions can now streamline their customer onboarding operations, improve customer experiences, and adapt to the changing demands of the digital age.

What are the features and capabilities of JurisTech’s digital onboarding platform that allow for such great improvements, you may ask? 

Features such as a loan straight-through processing (STP) engine, digital verification via eKYC, secure document management, compliance checks, authentication mechanisms, data encryption, secure communication, and continuous security monitoring, are available on JurisTech’s digital onboarding platform to help financial institutions digitise their customer onboarding journey. The aforementioned features are intended to guarantee the confidentiality and security of data, optimise workflows, and augment customer satisfaction, ultimately resulting in better business results.

Cut Through the Noise with Straight-Through Processing

JurisTech’s loan STP engine is a standout feature that simplifies and automates the loan application and approval process. The engine evaluates loan applications using predefined business rules, credit scoring algorithms, and real-time credit checks; it then provides customers with real-time decisions and notifications. This feature allows for a quick and effective onboarding process by drastically cutting down on the amount of time needed for application evaluation and decisioning.

Enhanced Security Measures for You and Your Customers’ Peace of Mind

Digital verification features like eKYC and internal blacklist checking are also available on JurisTech’s digital onboarding platform, enabling safe and effective customer identity verification procedures. Customers can upload and manage confidential documents on a secure platform that guarantees data encryption and protection both during transmission and storage. Compliance checks, like CDD and EDD, are carried out to make sure that regulations are followed and to reduce the risk of fraud and money laundering.

Advanced encryption protocols protect customer data, guaranteeing that sensitive information is shielded from unauthorised access or breaches. Authentication mechanisms, like 2FA and OTP verification, improve the security of customer accounts and transactions. Encrypted messaging and video conferencing are examples of secure communication channels that safeguard private conversations and client interactions.

A security matrix, which offers granular access control to guarantee that users only have access to the data and processes they require, is another feature of JurisTech’s digital onboarding platform. A comprehensive audit trail for compliance and security purposes is provided by the platform’s security audit trail, which keeps track of all user actions and system modifications.

In order to guarantee that client data is handled in compliance with legal requirements, JurisTech’s digital onboarding platform also complies with industry standards and laws, such as GDPR and other data privacy laws. Mechanisms for threat detection and continuous monitoring are put in place to quickly identify and address any potential security threats or vulnerabilities.

Streamline Operations with Low-Code Technology

In addition, the platform offers a number of features that improve user experience, such as a drag-and-drop interface, dynamic form builder, and low-code platform. Business users can drag-and-drop visual editors and reusable actions into processes for rapid development without coding thanks to these features, which make process design and development simple and intuitive.

Build Digital Ecosystems with Open API Compatibility

Last but not least, JurisTech’s digital onboarding platform complies with Open API standards to facilitate ecosystem integration and data exchange. Financial institutions can take advantage of the power of data and propel business growth with this feature, which makes it simple for them to integrate with other platforms and systems.

The Proven Use Cases of JurisTech’s Digital Onboarding Platform

Credit leasing, auto financing, and mortgages are just a few of the financial industries that have successfully adopted JurisTech’s digital onboarding platform. By improving client experiences and simplifying corporate processes, the platform’s cutting-edge features and capabilities have completely changed the way financial institutions run.

In the mortgage sector, JurisTech’s digital onboarding platform has facilitated the creation of a mortgage marketplace that connects over 1800 lawyers and financiers, streamlining the mortgage application and approval process. As a result, financial institutions are now better equipped to use data and technology to boost their competitiveness and spur corporate expansion.

JurisTech’s digital onboarding platform, which offers a digital platform for customer-initiated applications, affordability and repayment calculators, and seamless document uploads, has empowered a major luxury vehicle brand in the auto-financing industry. The decision-making process has been accelerated for customers by the platform’s real-time credit check and decisioning capabilities, which have secured more favourable financing and credit terms. This has improved consumer loyalty and satisfaction by improving the auto-financing experience overall.

With the help of JurisTech’s digital onboarding platform, which streamlines the credit leasing process and improves business relationships, credit leasing companies can now connect with over 20,000 dealers through its marketplace. Additionally, a major local bank was able to expand their credit leasing offerings by partnering with property developers and agents through the platform’s assistance in creating a rent-to-own marketplace. Due to this, financial institutions have been able to increase the scope of their services and attract new clients, which has boosted their revenue and profitability.

In a Nutshell

To sum up, JurisTech’s digital onboarding platform is an all-inclusive digital platform that enables financial institutions to meet the changing demands of the digital age, digitise their operations, and improve customer experiences. The features and capabilities offered by the platform guarantee data privacy and security measures, expedite procedures, and improve customer experiences.

JurisTech, Your Preferred Partner

At JurisTech, we are committed to giving our customers the best possible support for their digital transformation projects. As one of the partners in the Asia Pacific region, Visa accredited five of JurisTech’s software solutions, including JurisTech’s digital onboarding platform, to offer the most effective and competitive solutions for the fintech industry landscape.

The VISA certification demonstrates JurisTech’s dedication to providing customers with a quick and safe connection to technology providers throughout the world. Let your customers enjoy a better banking experience by utilising JurisTech’s exceptional solutions, which guarantee award-winning expertise in digital customer onboarding and seamless integration.

Our team can assist you in navigating your system and ensuring that it meets your business requirements. Our members have extensive industry experience and are both technical experts and business consultants. We also offer comprehensive training prior to, during, and post-project implementations to ensure that all of your support needs are met. Ensuring mutual understanding of performance expectations is our top priority, and we put a lot of effort into making the digital transformation process enjoyable for our clients. 

For a free demo, get in touch with us right now to find out more about how JurisTech’s digital onboarding platform can increase your customer satisfaction and optimise your customer onboarding process.

About JurisTech

JurisTech (Juris Technologies) is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, telecommunications, and automobile companies in Malaysia, Southeast Asia, and beyond.

The post The Proven Results of JurisTech’s Digital Onboarding Platform appeared first on JurisTech.

JurisTech has been at the forefront of the fintech industry, driving economies forward with our first-class AI-powered solutions. We are well on our way to accomplishing our 2018 goal of reaching 100 organisations in 10 countries in 10 years, having over two decades of experience in the fintech space and serving more than 50 banks and financial institutions through more than 80 project implementations with a 100% project delivery rate.

In an age when technology is a major driving force, let us look at some of the key factors propelling JurisTech forward within the fintech industry.

The Use of Open API in JurisTech’s Products

Application Programming Interfaces (APIs) are the building blocks of digital ecosystems because they serve as links between networks. A collection of standards known as the Open Application Programming Interface (Open API) is what software developers can use to create an interface that lets their program talk to any other program.

Clear documentation, simple implementation, increased functionality, portability, simplicity, and language agnosticism are just a few advantages of Open API, which help to accelerate time-to-market. Open API is distinct from other specifications in that it is strictly structured, has robust tools, and has wide adoption. It is the most widely used and supported standard for describing APIs, and many businesses, like Microsoft, Google, GitHub, and Twitter, support it.

Open Banking, Powered by Open API

With the help of APIs, open banking allows banks and other third-party financial providers to share and absorb data, resulting in the creation of digital ecosystems. With customer consent, these providers analyse data to offer personalised services. Customers benefit from increased choice and control over personal data as a result of increased competition among banks and other financial institutions. Companies can take advantage of data-driven insights to gain a competitive edge, comprehend customer preferences, and cultivate a customer-centric approach. This evolution in banking is reshaping the industry and empowering both consumers and businesses.

The Implementation of AI/ML and Hyperautomation

As our solutions are built in adherence to the Open API guidelines, we are able to integrate JurisTech’s artificial intelligence solution together with our suite of products, as well as third-party systems that follow the Open API guidelines.

A newspaper featuring the impact of JurisTech’s AI and Collection solutions for Bank Rakyat in New Strait Times.

What are the use cases of AI/ML in finance and banking industry? In the case of JurisTech, we apply AI/ML in our solutions that serve the banking and finance sector across several key areas, which are debt collection, identifying credit default risk, alternative credit scoring, hyperautomation and personalisation, and optimising telemarketing, just to name a few.

AI/ML Use Cases in Banking – Debt Collection

AI and ML redefine the debt collection processes in banks and financial institutions. When borrowers miss payments for longer than ninety-nine days, banks have historically had trouble with non-performing loans (NPLs). The majority of banks’ automated collection systems are not flexible enough to pick up on the minute details of consumer behaviour. Because of this restriction, financial institutions are ill-prepared for potential difficulties that may arise and are unable to identify possible non-performing loans in a timely manner.

By presenting a proactive and adaptable methodology, JurisTech’s AI Solution transforms the way that NPLs are approached. With the help of this innovative solution, banks can predict how loan accounts will perform in the future by examining the five C’s of credit: Character, Capacity, Capital, Collateral, and Conditions. The emphasis on customer behaviour patterns ensures a more accurate and timely identification of potential NPL accounts.

AI/ML Use Cases in Banking – Identifying Credit Default Risk

The COVID-19 pandemic has reshaped the dynamics of credit-sensitive transactions, requiring a nuanced approach to identify and mitigate risks effectively. AI and ML prove to be useful tools for identifying credit default risk. JurisTech’s AI Solution leverages Machine Learning modelling, revolutionising the scoring and loan approval stage. With faster processing speed and a more precise forecast of future loan defaults, its AI-powered algorithm evaluates a large amount of customer data. This improves the entire credit risk management process by lowering time-to-market and guaranteeing accurate credit scores.

AI/ML Use Cases in Banking – Alternative Credit Scoring

AI and ML enable the use of alternative credit scoring through non-traditional data sources such as financial transactions, web traffic, mobile device usage, and public records. Diverging from traditional financial methods, Juris Mindcraft acknowledges the drawbacks of depending only on the credit system. Lack of credit history is a common barrier faced by the unbanked, unserved, or underserved markets. JurisTech’s Machine Learning model pioneers a holistic approach, incorporating nontraditional data sources like financial transactions, web traffic, and public records. This not only broadens the reach of digital banks and fintechs, but also allows for a more personalised and accurate creditworthiness assessment, enabling financial inclusion.

AI/ML Use Cases in Banking – Hyperautomation and Personalisation

AI and ML are crucial for analysing vast amounts of data to enable hyperautomation and personalisation. Recognising the uniqueness of each customer journey, JurisTech’s AI Solution steps in to assist origination and collection officers. It makes decision-making faster, more precise, and automated by recommending the next best course of action based on data insights. It also assists officers in making informed decisions, fostering meaningful interactions, and ensuring customer needs are met, from analysing creditworthiness during origination to predicting bad paymasters during collection.

AI/ML Use Cases in Banking – Optimising Telemarketing

Customer acquisition cost (CAC) is still a major concern for businesses, especially telemarketers. By automating processes, prioritising leads, offering real-time insights, and boosting personalisation, AI and ML optimise telemarketing, ultimately leading to increased efficiency and success rates. JurisTech’s AI solution can help maximise lead generation efforts, revolutionising the way companies interact with prospective clients. It identifies high-value prospects by mining the existing customer database, allowing agents to focus on quality leads. Through more focused and effective interactions, it not only achieves customer satisfaction but also expedites telemarketing efforts.

How Do These Factors Affect Customer Experience (CX)? 

For the financial industry, especially in banking and finance, the integration of automation, artificial intelligence, and machine learning holds great promise for enhancing the experiences of both customers and employees. Hyperautomation is a crucial enabler that boosts productivity, lowers errors, and enables banks to achieve higher precision in less time. Enhanced collaboration and fewer mistakes are two of the main ways that financial process automation increases productivity. Other benefits include improved regulatory compliance, increased flexibility, and a decrease in human error.

Additionally, hyperautomation enables automated customer interactions through AI chatbots and pre-established workflows, guaranteeing prompt and precise customer service. Moreover, it improves document processing and verification by utilising machine learning, NLP, and OCR for data extraction, verification, and policy evaluation.

By analysing consumer patterns and preferences for individualised interactions, artificial intelligence (AI) and machine learning help ensure better decision-making accuracy. The overall customer experience is improved as a result of this combined use of technologies, which also increases efficiency and reduces costs while improving customer service.

The Call for Financial Inclusion

As a leading innovator in credit scoring and lending solutions, JurisTech has always been a staunch supporter of financial inclusion. We have done this by utilising the revolutionary potential of artificial intelligence (AI) and data analytics. This innovation has broken down barriers, democratised finance, and provided opportunities for individuals and businesses around the world that were previously excluded from traditional financial systems.

The world still faces difficulties in achieving financial inclusion, which is essential to reducing poverty and fostering economic growth. Basic financial services are unavailable to the unbanked and underbanked, who make up a sizable section of the population. In Southeast Asia alone, 290 million people fall into this category, limiting their access to loans and perpetuating financial inequality.

As mentioned above, the evaluation of creditworthiness is revolutionised by the use of alternative data for credit scoring made possible by our autoML and AI platform. Lenders are able to obtain a complete picture of a borrower’s ability to repay loans by using artificial intelligence (AI) and machine learning to analyse data from a variety of sources, including utility bills, purchase histories, and mobile data. Through this method, loans are made available to the unbanked community.

Conclusion

JurisTech is a pioneering force in the ever-changing landscape of fintech, driving innovation and inclusivity in the financial industry. By integrating Open API, AI/ML, and hyperautomation strategically, we have not only advanced towards our ambitious target of reaching 100 organisations across 10 countries in 10 years, but we have also made a substantial impact on the financial ecosystem’s transformation. Through our advocacy of open banking, utilisation of alternative data for credit scoring, and deployment of cutting-edge technologies to improve customer experiences, JurisTech persists in breaking down barriers and promoting financial inclusion for the underbanked and unbanked. Our steadfast dedication to transforming the customer experience and advancing financial accessibility continues as we skillfully negotiate the ever-changing world of finance and technology.

About JurisTech

JurisTech (Juris Technologies) is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, telecommunications, and automobile companies in Malaysia, Southeast Asia, and beyond.

The post Driving Economies Through JurisTech’s Outstanding Impact on the Fintech Industry appeared first on JurisTech.

In today’s fast-paced business environment, collecting debt efficiently is critical for maintaining a healthy cash flow. Nevertheless, given the current state of the economy, it can be a difficult undertaking. At JurisTech, we recognise the difficulties companies encounter in pursuing unpaid debts. That is why we have put together this comprehensive guide to assist you in optimising your debt collection efforts and achieving better results.

The Rise in Adoption of Debt Collection Software

The size of the global debt collection software market was estimated at US$ 4.0 billion in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 10.91% from 2023 to 2028, to reach US$ 7.4 billion. The financial institution sector led the global market in 2021, and this trend is anticipated to hold true for the duration of the forecast. The demand for debt collection software is expected to grow as debt collectors face increased pressure to reduce costs while enhancing operations and increasing revenue.

Understanding the Debt Collection Process

Before diving into strategies for improvement, it’s crucial to have a clear understanding of the debt collection process. This involves a series of steps, beginning with the initial contact with the debtor and ending with the resolution of the outstanding balance. Familiarising yourself with each stage will provide a solid foundation for implementing the strategies outlined in this guide.

Early-Stage Collections (Less Than 30 Days Past Due):

During this stage, the creditor typically sends phone and mail notices to the debtor informing them of the outstanding payment. If applicable, services may be suspended and credit reporting bureaus notified. The debtor may also receive communication directly from the original creditor regarding the overdue payment.

Mid-Stage Collections (30 to 60 Days Past Due):

At this point, the original creditor may still be actively involved in debt recovery efforts. The debtor may receive additional communication from the original creditor or a third-party collection agency. It is important to note that the debtor retains the right to contest the debt and request verification.

Late-Stage Collections (60 to 90 Days Past Due and Beyond):

The original creditor may decide to write off the debt and sell it to an outside collection agency, often for a fraction of the original balance. As a result, the collection agency makes every effort to recover as much of the debt as possible, using a variety of communication methods to reach out to the debtor. 

Advanced Debt Collection Optimisation Strategies

Now that we have covered the fundamentals, let us dive into advanced debt collection strategies that can significantly improve your results.

An Overview of the 4 Strategies to Optimise Your Debt Collection Strategy

1. Leveraging Data and Analytics

Data-driven decision-making is an effective debt collection tool. It enables you to focus your efforts more effectively, increasing the likelihood of successful recoveries. 

Predictive Modelling for Debt Recovery

Predictive modelling is the use of historical data and statistical algorithms to forecast future outcomes. Predictive modelling in debt collection can help identify which accounts are more likely to result in successful recoveries. By focusing your efforts on high-probability accounts, you can maximise your resources and increase your overall collection rate.

Monitoring Key Performance Indicators (KPIs)

Tracking relevant KPIs provides useful information about the effectiveness of your debt collection efforts. Metrics like collection rates, account ageing, and recovery rates can help you identify problem areas. Analysing KPIs on a regular basis allows for continuous improvement of your collection strategies.

2. Implementing a Segmented Approach

Not all debts are equal, and treating them as such can be detrimental. Using a segmented approach allows you to tailor your collection strategies to each debtor’s unique characteristics.

Prioritising High-Value Accounts

Determine high-value accounts that have a significant impact on the financial health of your company. These accounts may represent large outstanding balances or have strategic importance. Allocate additional resources and attention to ensure that they are resolved on time.

Tailoring Strategies for Different Customer Profiles

Recognise that different customers have different financial capabilities and communication preferences. Some people respond better to negotiation, while others benefit from structured instalment plans. You can improve your chances of a successful debt recovery by being aware of and accommodating these differences.

3. Offering Flexible Payment Solutions

Offering flexible payment options can significantly increase the likelihood of debt recovery. It exhibits empathy for debtors’ financial circumstances and a readiness to work with them. 

Negotiating Settlements

Offering a settlement could be a useful strategy for debtors who are struggling financially. Accepting a partial payment as a final resolution of the debt constitutes a settlement. Both parties stand to gain from this, as it lets the debtor lessen their financial burden while guaranteeing your business gets paid a portion of the outstanding balance.

When negotiating settlements, it is critical to maintain transparency and professionalism throughout the process. Outline the settlement terms in detail, including the agreed-upon amount and payment schedule. To avoid future misunderstandings, document the agreement in writing.

Providing instalment Plans

Structured instalment plans allow debtors to make smaller, more manageable payments over time. This method is especially useful for debtors who are unable to make a lump-sum payment. Determine a payment plan that is in line with the debtor’s financial resources in collaboration with them.

Make sure the written agreement contains a clear description of the instalment plan’s terms. Specify the agreed-upon payment amounts and due dates, as well as any applicable interest or fees. Communicate with the debtor on a regular basis to ensure that the agreed-upon terms are followed.

4. Embracing Technology and Automation

Today’s digital age allows you to revolutionise your debt collection process by utilising automation and AI technology. It improves communication with debtors while streamlining operations and increasing efficiency.

Implementing Debt Collection Software

Investing in advanced debt collection software can drastically improve the efficiency of your operations. Automated reminders, integrated communication channels, and predictive analytics are among the features available on these platforms. They support your efforts to maximise collections, monitor progress, and maintain organisation.

Introducing JurisTech’s Collection Suite

Diagram of JurisTech’s Collection Suite

JurisTech’s enterprise debt collection software, Juris Collect, is an end-to-end solution that addresses all stages of debt collection. Not only that, but our debt collection software is also integrable with other solutions to achieve a better outcome.

For instance, our debt collection software can be integrated with our automated Machine Learning (autoML) and AI platform, to predict self-curing customers and behavioural scoring during the early detection stage for you to identify late payers and personalise the treatment journey to optimise your collection efforts. This allows your business to concentrate its resources on the high-value accounts mentioned above.

Regarding the early and late stages of collection, our debt collection software can be integrated with our all-in-one computer-telephony integration (CTI) software, which uses the latest technology to modernise your call processes.

Not only that, but our debt collection software enables your business to connect to an ecosystem of collection agencies and lawyers by building a collaborative platform whereby all manual handling of case distribution and commission payment is automated. By integrating with our end-to-end agency management software, we link you to debt collection agencies and automate your agency management procedures. Additionally, through integration with our legal workflow management platform, our debt collection software can put you in touch with attorneys for late-stage recovery, while providing you with real-time status updates on ongoing legal cases. 

Whiz, the Heart of JurisTech’s Debt Collection Software

Whiz is the driving force behind Juris Collect, taking centre stage as it automates the complex and labour-intensive parts of the collection treatment procedure. Providing financial institutions and businesses with an intuitive interface that even non-techies can easily use, its unique feature is its capacity to streamline collection strategy management. 

Whiz enables managers to evaluate and optimise various collection strategies through the use of the Champion Challenger Module, guaranteeing the adoption of the most efficient techniques. Organisations benefit from this automation in that it reduces costs and manpower burdens while simultaneously improving efficiency and inclusivity and freeing up valuable time. Whiz is essentially a key element that sets our debt collection software apart from its rivals by providing an advanced, user-friendly solution that improves and expedites the entire debt collection process.

JurisTech, Your Preferred Partner

At JurisTech, we are dedicated to providing our clients with top-notch support for their digital transformation initiatives. As a VISA-certified fintech partner, JurisTech smoothly integrates five standout products, including our acclaimed debt collection software, Juris Collect, into the VISA Fintech Partner Connect programme. This software, celebrated for its effectiveness, secured JurisTech the Best of Financial Applications award at the Asia Pacific ICT Awards (APICTA) in 2012. 

Demonstrating excellence, our debt collection software not only clinched the top position in Malaysia but also progressed to the Asia-Pacific stage, winning the Merit Award in the prestigious “Best in Financial Applications” category. VISA certification highlights JurisTech’s commitment to delivering clients a swift and secure connection to technology providers globally. Immerse yourself in an enhanced banking experience with JurisTech’s outstanding solutions, ensuring seamless integration and award-winning proficiency in debt collection.

Our team can help you navigate your system and align it with your project requirements and organisational needs. It is made up of technical experts and business consultants with a wide range of industry knowledge. To make sure all of your support needs are satisfied, we also provide thorough training before, during, and after project implementation. Satisfied clients are our top priority, and we work hard to create a mutual understanding of performance expectations so that the digital transformation process is enjoyable.

Contact us today to learn more about how JurisTech’s debt collection software can improve your recovery results and streamline your operations.

About JurisTech

JurisTech (Juris Technologies) is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

The post Optimising Debt Collection: Strategies for Improved Results appeared first on JurisTech.

Introduction

In the dynamic realm where finance intersects with technology, the concept of “Fintech” has surged to the forefront as a transformative catalyst reshaping economies worldwide. Leading the charge in this fintech revolution is JurisTech, a forward-thinking enterprise steered by the visionary CEO See Wai Hun. In this article, we embark on a journey to uncover the pivotal factors steering the global fintech landscape, delve into JurisTech’s pivotal role in propelling this transformation, and gain glimpses into the future of fintech.

Fintech and Its Global Impact

What is Fintech?

Fintech, a portmanteau of “financial technology,” refers to the innovative use of technology to deliver financial services more efficiently, affordably, and inclusively. Fintech companies leverage cutting-edge technologies such as artificial intelligence (AI), blockchain, and data analytics to reimagine traditional financial services, ranging from payments and lending to insurance and asset management.

The Global Fintech Landscape

The fintech landscape is undergoing rapid transformation globally, driven by several key factors:

1. Increasing Digitisation: The proliferation of smartphones and internet access has empowered individuals worldwide with the ability to access financial services digitally. This digitalisation has created new opportunities for fintech companies to reach a global audience.
2. Changing Consumer Expectations: Consumers are increasingly seeking convenience, transparency, and personalised financial solutions. Fintech companies are capitalising on these expectations by offering user-friendly apps, robo-advisors, and accessible financial products.
3. Regulatory Support: Many governments and regulatory bodies are recognising the potential of fintech to improve financial inclusion and drive economic growth. They are introducing supportive regulations to foster fintech innovation.

JurisTech: A Driving Force in the Malaysian Fintech Revolution

The Visionary Leadership of See Wai Hun

At the helm of JurisTech stands CEO See Wai Hun, a visionary leader with a deep commitment to driving fintech innovation. Her leadership has propelled JurisTech from a local innovator to a global influencer, leaving an indelible footprint on the fintech landscape.

Fostering the Fintech Landscape Globally 

JurisTech’s 2018 goal (100 10 10) was to reach 100 organisations, in 10 countries in 10 years, with a vision to create amazing solutions and build and enrich lives. Thus, the impact of working towards the global fintech landscape direction is significant, and we are driven by several key factors:

1. Empowering Financial Inclusion: JurisTech has developed innovative credit scoring and lending solutions that empower individuals and businesses worldwide to access credit. By using artificial intelligence (AI) and data analytics, they have democratised finance, providing opportunities for those previously excluded from traditional financial systems.
2. Enhancing Operational Efficiency: Through its cutting-edge technologies, JurisTech has helped financial institutions across the globe streamline their operations, reduce costs, and improve efficiency. This optimisation has direct implications for the profitability of these institutions and the broader economy.

JurisTech: A Beacon of Innovation

JurisTech is akin to a beacon of innovation in the fintech industry. Like many fintech companies, it harnesses AI and advanced machinery to provide groundbreaking products and solutions. However, JurisTech stands out in several remarkable ways:

1. Redefining Financial Services: JurisTech’s solutions are created to revolutionise business models, processes, and operations. Utilising advanced technology, JurisTech envisions applying Generative AI (Gen AI) to  an AI industry analyst for credit papers. In this scenario, Gen AI would generate research on a company or its industry of operation automatically. Gen AI possesses sophisticated capabilities, such as decision-making, learning, and adaptation, that go beyond traditional machine learning AI. The advanced solutions of JurisTech are redefining how financial institutions interact with clients and streamline their operations.
2. Meeting your Business’s Needs: JurisTech tailors your products and services to your business’s needs. With our customers in mind, JurisTech places a great emphasis on our delivery capabilities to put our products at the forefront of our client’s ongoing and future digital transformation. This approach sets JurisTech apart, the foresight to allow clients like banks and financial institutions to not only provide personalised financial solutions to their customers but also to generate greater revenue through technology.

JurisTech’s Global Reach

While JurisTech’s roots are in Malaysia, its influence extends far beyond national borders. The company’s global vision has led to collaborations with industry leaders across various sectors and regions.

1. The alliance with a leading Japanese multinational automobile manufacturer has resulted in the development of advanced credit assessment models. These models have revolutionised lending practice, making credit more accessible to individuals and businesses.
2. In partnership with one of the oldest multi-finance companies in Indonesia, JurisTech has introduced cutting-edge risk management solutions. These solutions enable the company to make informed lending decisions, reduce default rates, and support responsible lending practices.
3. JurisTech’s association with the largest Islamic bank in Malaysia has led to the creation of innovative credit-scoring models that improve the bank’s lending processes and promote financial inclusion among Malaysians.
4. Collaboration with one of the world’s leading premium manufacturers of automobiles and motorcycles, JurisTech’s collaboration with the organisation in Australia, showcases its ability to deliver tailored fintech solutions for the automobile industry through JurisTech’s digital onboarding solution. This partnership has streamlined financing processes, enhancing the overall customer experience.
5. One of JurisTech’s most significant collaboration is with Malaysia’s largest bank. Through this partnership, JurisTech has helped the company create advanced credit scoring models and lending solutions, making credit more accessible to Malaysians and fostering economic growth.

The Future of Finance: A Glimpse Through JurisTech’s Lens

JurisTech’s journey from a Malaysian fintech innovator to a global industry influencer is not only remarkable but also provides insights into the future of finance. As fintech continues to evolve, here are some trends and possibilities we can anticipate, with JurisTech leading the way:

1. AI-Powered Finance: JurisTech’s Alternative Data, with Machinery AI solutions, are indicative of the future of finance. AI will become increasingly sophisticated, enabling financial institutions to automate decision-making, personalise customer experiences, and manage risk more effectively.
2. Prioritising Exceptional Customer Service: In the fintech industry, companies such as JurisTech are committed to delivering exceptional customer service. The financial ecosystem will place a greater emphasis on responsive and efficient support, ensuring a superior customer experience.
3. Expanding Collaborative Ventures: JurisTech’s collaborative approach is gaining momentum. Notably, our partnerships with industry leaders like CTOS and iMoney exemplify mutually beneficial relationships that enhance services for end-users.

Conclusion: Shaping a Brighter Financial Future 

CEO See Wai Hun, at the helm of JurisTech, strongly believes in the quote:

“We’re revolutionising the way financial transactions are conducted.”

This quote reflects JurisTech’s mission, as detailed in this article, to harness data-driven fintech solutions for financial institutions’ empowerment and economic growth. Our company is at the forefront of innovative fintech solutions that enhance financial inclusion, operational efficiency, and customer-centricity. The collaborations with industry leaders like CTOS and iMoney underscore the urgency for banks to embrace data-centric innovation. The quote symbolises JurisTech’s commitment to a future where finance and technology seamlessly merge for the benefit of all stakeholders.

JurisTech’s journey is not just a story of success; it’s a narrative of transformation, collaboration, and global impact. Under the visionary leadership of CEO See Wai Hun, the company has transcended boundaries and reshaped the global fintech landscape. From revolutionising lending practices to promoting financial inclusion and fostering cross-border collaborations, JurisTech’s influence is undeniable.

As we look to the future of finance, we see a world where fintech innovation, driven by companies like JurisTech, will continue to enhance financial accessibility, efficiency, and inclusivity. With AI-powered solutions, digital identities, and customer-centricity at the forefront, we can expect a financial landscape that empowers individuals and businesses worldwide.

JurisTech’s journey is a testament to the transformative power of fintech, and it leaves us with a clear message: the future of finance is bright, and it’s being shaped by those who dare to innovate and collaborate on a global scale. 

About JurisTech

JurisTech is a leading Malaysian-based Fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond. 

Make intelligent business decisions with our Juris Mindcraft, an effortless artificial intelligence (AI) platform that uses machine learning techniques to build powerful AI models.

The post JurisTech’s Fintech Footprint: From Malaysia To The Global Landscape appeared first on JurisTech.

Introduction

In the dynamic landscape of today’s digital world, Artificial Intelligence (AI) has emerged as a transformative force, reshaping traditional norms and propelling industries toward unprecedented advancements. Among these industries, the banking industry has witnessed remarkable transformations, thanks to the impressive strides made by AI. Increasingly, banks and financial institutions (FIs) are recognising the immense potential of AI and are leveraging its capabilities to elevate their credit risk management practices to new heights. 

Credit risk management plays an essential role in the banking industry as it assists banks and FIs to assess and minimise the likelihood of borrowers or counterparties failing to meet their financial obligations. The implementation of AI in credit risk management offers numerous benefits, including identification of potential risk, fraud detection, real-time monitoring, automated processes, accuracy in predictions, and reduction of credit management time. These advancements enable banks and FIs to enhance their risk mitigation strategies, improve decision-making processes, and ultimately strengthen their overall credit risk management framework.

While embracing AI in credit risk management promises a myriad of advantages, it also presents various challenges that need to be navigated. These include data quality and availability, bias and fairness, and data privacy and confidentiality. Let’s delve into the pivotal role played by AI in credit risk management, examining its wide-ranging benefits, the challenges it poses, and the best practices in AI-driven credit risk management. 

Limitations of Traditional Credit Risk Management

Insufficient data analysis

Before the advent of AI, one of the limitations of traditional credit risk management is insufficient data analysis. Insufficient data analysis is a common issue, as banks and FIs rely on manual processes and limited datasets to evaluate creditworthiness and make credit decisions. Without sufficient data analysis, the risk of making incomplete or inaccurate risk assessments will definitely increase. 

Subjectivity

Another limitation of traditional credit risk management is subjectivity. Traditional credit risk assessment normally relies on the subjective judgment of decision makers, where everyone has different risk appetites, experiences, biases and perceptions. That being said,  it can lead to inconsistency and bias in decision-making, and can even result in potential misjudgements as humans are usually subjective in nature. 

High cost and time-consuming

Traditional credit risk management often involves lengthy procedures for assessing creditworthiness. These procedures included manual credit scoring, financial analysis, and evaluation of collateral, requiring extensive time and expertise. In other words, traditional credit risk management is likely to limit the ability of banks and FIs in making prompt credit decisions as it is time-consuming, and this can even increase their operating cost. 

Implementation of AI in Credit Risk Management

Risk identification

The implementation of AI in credit risk management is an initiative that should be taken by most banks and FIs nowadays as it can assist them in identifying risk. In particular, AI algorithms can analyse vast amounts of historical credit data more efficiently and accurately than traditional methods. By recognising patterns and trends in past credit behaviour, AI can identify potential risks associated with specific borrowers or industries. Therefore, AI enables banks and FIs to make better-informed decisions while minimising risks.

Fraud detection

The expenditure on financial fraud detection platforms that utilise AI is projected to surpass $10 billion globally by 2027, as per Juniper Research’s findings. On top of that, AI technologies, specifically machine learning (ML) algorithms, have the capacity to examine large volumes of data and identify patterns and irregularities that could potentially signify instances of fraudulent activities.This clearly indicates that more banks and FIs will start adopting AI-driven credit risk management as they can assist them in detecting fraud over time. 

Automated process

According to 14% of market professionals, AI scoring systems have already demonstrated superior performance compared to human-based ones. AI algorithms possess the capability to undergo training for repetitive and time-consuming tasks, like data entry and analysis, with significantly increased speed and precision compared to human counterparts. This implies that more banks and FIs should implement AI in credit risk management as it enables automated processes which can result in greater efficiency. 

Reduction of credit risk management time

One of the greatest benefits that AI has brought to humans is to improve efficiency. Traditional credit risk management normally requires banks and FIs to invest considerable time in manually verifying applications. By implementing AI in credit risk management, the time required by credit risk management has reduced significantly as banks and FIs can decrease the reliance on manual processes. 

Challenges of AI in Credit Risk Management

Data quality and availability 

One of the primary challenges faced by AI in credit risk management is the data quality and availability. AI algorithms heavily rely on vast amounts of historical data to make accurate predictions and decisions. However, banks and FIs often face difficulties in obtaining high-quality, comprehensive, and up-to-date data. Incomplete or outdated data can lead to inaccurate credit risk assessments, potentially impacting the overall risk exposure of the institution.

Bias and fairness

AI algorithms are susceptible to inheriting biases present in historical data, leading to potential discrimination in credit risk assessment. The historical data may contain algorithmic bias, which could adversely affect certain groups of individuals or businesses. When AI models perpetuate these biases, it raises ethical concerns and may result in unfair credit decisions, hindering financial inclusion. 

Data privacy and confidentiality

As AI in credit risk management requires access to sensitive personal and financial information, data privacy and confidentiality become paramount concerns. Financial institutions have the responsibility to protect customer data from unauthorised access, breaches, or misuse. Failure to do so can lead to severe reputational damage and legal ramifications.

Best Practices in AI-driven Credit Risk Management

High-quality data 

The foundation of any successful AI-driven credit risk management system lies in the quality of the data it utilises. Accurate, comprehensive, and up-to-date data is crucial for building robust AI models capable of making precise risk assessments. Banks and FIs must ensure that their data sources are reliable as it allows AI to generate better predictions and yield more dependable results.

Bias and Fairness Mitigation Techniques 

Banks and FIs should adopt bias and fairness mitigation techniques in their AI-driven credit risk managment. One approach is to conduct regular audits of AI models to identify and address biases. Data scientists can use specialised algorithms to detect bias and introduce corrective measures to mitigate its impact. On top of that, transparency in the credit risk assessment process is also crucial. Banks and FIs should strive to make their AI models interpretable, allowing customers and regulators to understand the factors influencing credit decisions.

Robust Cybersecurity Measures

It is essential for banks and FIs to practice robust cybersecurity measures to protect sensitive customer data and maintain client trust. Specifically, they could implement state-of-the-art cybersecurity protocols, including data encryption, secure data storage, and multi-factor authentication. Regular security audits and vulnerability assessments can help identify and address potential weaknesses in the system. Additionally, educating employees about cybersecurity best practices can reduce the risk of internal security breaches. 

In Conclusion

The integration of AI into credit risk management has emerged as a beacon of transformation in the ever-evolving landscape of banking and finance. AI’s far-reaching benefits extend from enhancing risk assessment accuracy and fraud detection to automating time-consuming processes, ultimately bolstering decision-making and mitigating risks. The remarkable strides made by AI have paved the way for a new era of risk management practices, with innovative platforms like JurisTech’s explainable and automated Machine Learning (AutoML) and AI platform, Juris Mindcraft. Its capabilities span far and wide, from triggering early warning systems that forecast non-performing loans (NPLs) to employing self-curing prediction strategies for delinquent customers. By identifying credit default risks and leveraging alternative credit scoring methodologies, it even addresses the challenges posed by credit-invisible customers, facilitating a more inclusive financial landscape.

Through a commitment to high-quality data, fairness mitigation, and robust cybersecurity measures, banks and financial institutions can navigate the intricate path of AI integration, harnessing its power to forge a more resilient and efficient credit risk management framework. In the convergence of technology and finance, the proactive embrace of AI stands as a testament to the industry’s readiness to shape a future of informed and responsible financial management.

About JurisTech

JurisTech (Juris Technologies) is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

The post The Role of AI in Credit Risk Management appeared first on JurisTech.

In today’s interconnected world, the ability to access financial services is critical for the well-being of individuals and communities. The availability and accessibility of banking and financial services to all individuals, including those who have traditionally been underserved or unbanked, is referred to as financial inclusion. Digital banking platforms have emerged as influential tools in closing this gap and ensuring that everyone has access to the financial resources they require. 

Let us examine the significance of financial inclusion, the challenges to achieving it, and the empowering potential of digital banking platforms, which provide individuals with accessible financial services.

What is Financial Inclusion? 

Financial inclusion extends beyond the provision of basic banking services to include a broader range of financial solutions. It entails giving people access to savings accounts, loans, insurance, payment options, and investment opportunities, among other things. By extending these services to individuals previously excluded from the conventional banking landscape, financial inclusion aims to empower individuals, alleviate poverty, and stimulate economic growth.

Why is Financial Inclusion Important? 

In the pursuit of social and economic development, financial inclusion assumes a vital role. It enables people to save money, obtain credit for business ventures, mitigate risks, and build a prosperous future for themselves and their families. On a global level, approximately 1.7 billion adults lack access to banking services, despite the fact that two-thirds of them possess a mobile phone that could serve as a gateway to financial services. Furthermore, financial inclusion encourages entrepreneurship, inspires innovation, and strengthens the economy‘s overall stability.

Challenges to Financial Inclusion

Despite its importance, achieving financial inclusion is not without challenges. Geographical barriers, limited infrastructure, difficulties in obtaining formal identification documents, and cultural barriers all impede the progress of financial inclusion initiatives. Moreover, high transaction costs and the lack of tailored financial services for specific communities further contribute to the exclusion of vulnerable populations.

How Do Digital Banking Platforms Help Financial Inclusion? 

Digital banking platforms have emerged as a game changer in the promotion of financial inclusion. Let us look at how they are addressing the issues and empowering individuals:

Bridging the Access Gap

Serving as a bridge between underserved populations and formal financial services, digital banking platforms assume a significant role. Individuals seeking basic financial services face challenges in many developing countries due to a lack of traditional physical banks. However, digital platforms transcend geographical boundaries and serve as a virtual gateway to financial inclusion. These platforms ensure that individuals with limited financial literacy or technological skills can participate in the digital economy by providing user-friendly interfaces, streamlined account opening procedures, and multilingual support.

Lowering Transaction Costs

In contrast to traditional banking methods, digital banking platforms offer a considerable reduction in transaction costs. These platforms make financial services more cost-effective and accessible to people with limited resources by eliminating physical paperwork, manual procedures, and excessive administrative fees.

Customised Financial Services

Digital banking platforms that use advanced analytics and algorithms can provide individualised financial services that are tailored to specific needs and preferences. These platforms provide personalised recommendations and products based on their customers’ financial behaviour. This level of customisation improves the overall user experience and ensures that financial services are perfectly aligned with each individual’s unique needs.

Enhancing Financial Literacy

In addition to enabling access to financial services, digital banking platforms actively contribute to the improvement of financial literacy. For instance, Bank Negara Malaysia’s financial inclusion framework incorporates the utilisation of different digital channels as a means to advance financial literacy. These platforms frequently offer educational resources, tutorials, and interactive tools to help people make informed financial decisions. By promoting financial literacy, digital banking platforms enable individuals to take control of their finances and lay a solid foundation for their future.

Microfinance and Microloans

The rise of digital banking platforms has transformed the landscape of microfinance and microloan institutions. These institutions offer small loans to entrepreneurs and individuals residing in low-income communities, equipping them with the means to establish or scale their businesses. By leveraging digital platforms, the loan application process and disbursement are simplified, ensuring enhanced accessibility and efficiency for borrowers.

What Does the Future Hold for Digital Banking Platforms?

The future of digital banking platforms in promoting financial inclusion holds great promise. Artificial intelligence, blockchain, and biometrics are among the technological advancements poised to transform these platforms’ capabilities. Partnerships between governments, financial institutions, and technology companies will also be critical in expanding access to financial services and ensuring the inclusion of underserved populations. 

The Importance of Collaboration between Financial Institutions and Technology Companies

To optimally leverage the impact of digital banking platforms on financial inclusion, it is imperative to foster collaboration between financial institutions and technology companies. By combining the deep industry expertise of financial institutions with the technological advancements and forward-thinking capabilities of technology companies, holistic solutions can be crafted to cater to the diverse requirements of individuals and communities.

Speaking of collaboration between financial institutions and technology firms…

JurisTech, Your Preferred Partner

At JurisTech, we stand behind our end-to-end credit management solutions, which are not only intuitive, secure, and scalable but also aimed at driving financial inclusion for all. We bring more than two decades of experience in the Fintech sector, as well as a proven track record of successfully delivering projects to clients in 11 countries. We take pride in providing our clients with exceptional support for their digital transformation needs. 

Our dedication to your success extends beyond the completion of the project, as we provide ongoing post-implementation support to ensure a smooth transition to your improved system. Our teams of technical experts and business consultants have extensive industry knowledge and are always ready to walk you through your system, which is tailored to your specific project requirements and organisational needs. We provide comprehensive training before, during, and after project implementation to ensure that you are confident in using the system to its full potential. Our ultimate goal is to meet your expectations and form a mutually beneficial partnership that promotes a positive digital transformation experience.

Are you passionate about achieving financial inclusion like we are? Don’t delay; reach out to us today via contact@juristech.net to arrange a free demo of our solutions.

About JurisTech

JurisTech (Juris Technologies) is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

The post Unlocking Financial Inclusion: The Impact of Digital Banking Platforms appeared first on JurisTech.

The financial technology (Fintech) industry thrives on effective risk management, given its reliance on cutting-edge technologies and data analytics. Within this context, decision engines have emerged as a true game-changer. These powerful tools enable Fintech and financial institutions (FIs) to capitalise on the potential of data-driven decision-making, automate operations, and strengthen their risk management capabilities. Let us take a closer look at the critical role that decision engines play in shaping risk management strategies in the ever-changing Fintech ecosystem.

Understanding the Need for Effective Risk Management

Effective risk management is critical in the Fintech industry, where businesses face a variety of risks associated with lending, investments, fraud, and regulatory compliance. Dealing with the intricacies of these risks necessitates advanced tools and strategies for accurately evaluating, tracking, and mitigating them. Traditional risk management methods, which rely on manual procedures and subjective assessments, are often inefficient and error-prone. Furthermore, they struggle to keep up with the massive amounts of data generated by the Fintech ecosystem. Enter decision engines, the solution to these problems.

What Are Decision Engines?

Decision engines are advanced software systems that use artificial intelligence (AI), machine learning (ML), and big data analytics to make real-time decisions and automate complex processes. These engines seamlessly integrate disparate data sources, employ advanced algorithms, and produce actionable insights that serve as the foundation for risk management strategies. By merging data analytics with business rules and predefined models, decision engines empower organisations to swiftly and precisely make informed decisions.

How Decision Engines Improve Risk Management in Fintech

Streamlining Data Analysis and Fraud Detection

The financial impact of fraud on U.S. financial services and lending firms has escalated from approximately 6.7% to 9.9% when compared to the period before the pandemic. This implies that for every $1 lost to fraud, U.S. financial service companies now experience a cost of $4.00, while the figures stood at $3.25 in 2019 and $3.64 in 2020. 

With decision engines, potential fraud can be detected early by spotting anomalies in “normal” behaviour or patterns. Decision engines excel at processing large amounts of structured and unstructured data, such as customer information, transaction records, credit scores, and market data, in a timely and efficient manner. Decision engines uncover significant patterns, trends, and potential risks that would otherwise go unnoticed by quickly analysing this massive dataset. This enables firms to make data-driven decisions based on complete and up-to-date information, reducing the likelihood of errors and improving the effectiveness of their risk management strategies.

Enhancing Accuracy and Speed

Traditional risk management practices are often manual and time-consuming, resulting in lengthy decision-making processes and increased susceptibility to risks. By automating these time-consuming procedures, decision engines usher in a paradigm shift. This automation not only saves cost, time, and effort in risk assessment and analysis, but it also improves the accuracy of risk predictions and assessments by 20–40% by utilising advanced algorithms and machine learning techniques. As a result, FIs are better equipped to make more informed decisions faster and with greater precision.

Enabling Real-Time Risk Assessment

The ability to perform real-time risk assessment is critical in the fast-paced world of Fintech and finance for quickly identifying and addressing potential risks. Decision engines excel in this area because they provide real-time insights into risk exposures. As abovementioned, these engines raise alerts quickly when predefined thresholds or anomalies are detected by continuously monitoring data. This proactive risk management approach enables organisations to take immediate action, thereby effectively preventing potential losses or fraudulent activities.

Automating Compliance and Regulatory Requirements

Compliance with regulatory frameworks and industry standards is a fundamental aspect of risk management in Fintech. By incorporating regulatory guidelines into their algorithms and workflows, decision engines prove invaluable in automating compliance processes. This ensures that risk assessments and decisions are in accordance with legal and regulatory requirements, effectively mitigating the risk of non-compliance and the resulting penalties. By streamlining compliance tasks, decision engines enable organisations to focus their efforts on strategic risk management initiatives.

Challenges in Implementing Decision Engines

While decision engines show great promise for improving risk management in the Fintech industry, successful implementation is difficult. To fully leverage the capabilities of decision engines in effectively managing risks, it is critical to address these challenges diligently.

Data Quality and Integrity

Decision engines place significant reliance on the accuracy and integrity of the data they process. Inaccurate, incomplete, or biased data can result in flawed risk assessments and decisions. To maintain data integrity throughout the decision-making process, companies must take proactive measures to ensure the availability of high-quality data and establish robust data governance practises.

Interpretability and Explainability

Given the complexity of decision engines’ algorithms and machine learning models, ensuring interpretability and explainability is critical. Fintech companies must have a thorough understanding of the factors that influence risk assessments and decisions generated by these engines. Transparent and explainable models foster trust among stakeholders, regulators, and customers, increasing decision engine acceptance and adoption.

Best Practises for Utilising Decision Engines in Risk Management

To fully realise the potential of decision engines and strengthen risk management practices, Fintech companies should implement the following best practices: 

Ensuring High-Quality Data Inputs

Fintech companies should prioritise investments in data quality management mechanisms to ensure that decision engines have accurate, trustworthy, and comprehensive data inputs. They should also maintain data integrity by continuously monitoring and authenticating data sources throughout the risk management lifecycle to identify opportunities for improvement.

Establishing Robust Governance and Control Mechanisms

Fintech companies must implement strong governance frameworks and control mechanisms to oversee the operation of decision engines. They should establish transparent accountability structures, clearly define roles and responsibilities, and evaluate the performance and effectiveness of decision models on a regular basis.

Future Trends and Innovations in Decision Engines for Risk Management

The field of decision engines is constantly evolving, and future trends are expected to improve risk management capabilities in Fintech. Some emerging trends include the incorporation of explainable artificial intelligence (XAI), the use of natural language processing (NLP) for data analysis, and the use of blockchain technology for secure and transparent decision-making processes.

In a Nutshell

Decision engines have transformed risk management in the Fintech industry. These advanced tools use AI, machine learning, and data analytics to enable organisations to make data-driven decisions, streamline processes, and improve risk assessment and mitigation strategies. However, for successful implementation, challenges related to data quality, privacy, security, and explainability must be addressed. Fintech companies can fully leverage the potential of decision engines by adhering to best practises and staying up-to-date on future trends.

JurisTech, Your Preferred Partner

JurisTech is a Fintech enabler that has a two-decade track record of success, specialising in credit management, digital banking, and AI. Our expertise in AI is demonstrated by our explainable automated ML and AI platform, which enables banks and FIs to make informed business decisions and gain valuable insights into real-world issues. Furthermore, by leveraging data-driven insights, our auto-decisioning engine enables businesses in a variety of industries to confidently and accurately make complex decisions in real-time. 

Our technical experts and business consultants are dedicated to assisting clients in meeting their digital transformation objectives. We believe in building strong partnerships with our clients, tailoring solutions to their specific project requirements and organisational needs to ensure seamless integration with their systems. To ensure a smooth transition, we provide exceptional support that extends beyond project completion, including comprehensive post-implementation assistance and training to meet ongoing needs.

If you would like to learn more about how JurisTech can help you achieve your digital transformation goals, please get in touch with us right away. Our team is always available to help you on your journey to a more efficient and effective digital future.

About JurisTech

JurisTech (Juris Technologies) is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

The post The Remarkable Impact of Decisioning Engines on Risk Management appeared first on JurisTech.

The digitisation of the modern world has been rapidly accelerating over the past few decades, resulting in an enormous amount of data that is predicted to reach 175 ZB (zettabytes) by 2025. This has given rise to big data, which has become a critical asset for businesses across a range of industries. 

The financial industry is one of the most data-intensive sectors out there, offering an incredible opportunity to process, analyse, and leverage the data in meaningful ways. At the same time, the industry is also highly susceptible to risks such as financial crimes, credit risks, market volatility, etc. Therefore, the use of big data in financial risk management has become essential as it is a powerful tool that enables businesses to anticipate and mitigate potential risks before they occur. By making use of big data analytics and risk management tools, businesses can gain valuable insights into their operations, identify potential threats, and take proactive measures to mitigate risks. As a matter of fact, a report published by McKinsey Global Institute states that data-driven companies are 19 times more likely to be profitable. 

How is big data revolutionising the financial industry?

First and foremost, what is big data? 

Big data is a term that refers to extremely large datasets that are too complex for humans to manage effectively. Big data is collected from various sources, including social media, sensors, machines, and other digital devices. It can come in the form of structured, unstructured, and semi-structured datasets. The amount of big data generated in the finance industry is growing exponentially, transforming and revolutionising the way financial institutions operate. The sheer volume and complexity of data generated have created new opportunities for companies to derive insights, manage risks effectively, and make better-informed decisions. 

How does big data help manage risk?

Traditionally, bank employees were responsible for number crunching, and business leaders made decisions based on manually calculated risks and trends. Big data analytics, however, presents an exciting opportunity for banks and financial institutions to tackle and mitigate risks. 

By leveraging big data, financial institutions gain access to a vast amount of data from multiple sources, including customer transaction histories, social media activities, and sensor data from physical assets. With the right tools and technology, financial institutions can analyse this data to identify patterns and trends, which can then inform risk management decisions. For instance, if a financial institution notices an increase in delinquent loans in a certain geographic area, they can investigate further and take appropriate measures to manage the risk.

Besides that, by analysing patterns and trends in data, financial institutions will be able to gain a comprehensive understanding of risk across various areas of the business. This includes risks related to credit, market, operational, and liquidity. When coupled with Artificial Intelligence (AI) and Machine Learning (ML), financial institutions will be able to take the analysis to the next level. The traditional data analysis methods in managing risks have limitations — they may not capture all the relevant data or analyse it in a timely manner. Additionally, manual data analysis and monotony are prone to human errors. In fact, the greater the monotony, the higher the error rate in most situations. 

However, AI and ML enables financial institutions to uncover patterns and correlations that humans may not be able to see, and the algorithms make it possible to do so at a speed and scale beyond human capacity. Furthermore, its prediction accuracy increases over time when more data are being fed. For instance, AI and ML can identify links between seemingly unrelated data points, such as social media activity and credit risk. If all data points to a loan applicant being at high risk for default, financial institutions can take proactive measures to manage and mitigate the credit risk before it becomes a problem.

What are some major challenges associated with big data?

While the idea of implementing big data can provide significant benefits, it also comes with its own set of challenges. 

Data quality

Bad or outdated data can lead to inaccurate predictions and analysis, which can cause poor results in decision-making. Data quality issues can arise from various sources, such as human error, technical glitches, or data entry issues. Therefore, it is critical for organisations to have robust data quality processes in place to ensure that the data used for analysis is accurate and up-to-date.

Data integration

Like most businesses, banks and financial institutions often use multiple systems to store and manage their data, resulting in data silos. These silos make it difficult to get a comprehensive view of all the data, which can hinder efficient analysis. To effectively leverage big data, businesses need to integrate data from various sources into one centralised platform. If done manually, this process can be complex and time-consuming, requiring careful planning and execution to ensure that the data is properly aligned and structured. Failing to do so may negatively impact business operations such as inaccurate predictions and flawed decision-making. 

To address these challenges, we created Juris DecisionCraft, an automated decision engine that orchestrates and synergises data and analytics from different sources to achieve the best result. It is designed to empower business executives and decision makers to make fast data-backed decisions at scale. 

Understanding data’s decision

Another key challenge in implementing big data for organisations is the issue of black-boxed data decisions. As machine learning algorithms become more sophisticated and capable of making decisions based on data, it can become difficult to understand how those decisions were made. This could pose a problem for financial institutions that need to be able to explain their decision-making process to stakeholders and/or regulatory bodies. In some cases, the decisions made by machine learning algorithms may even be in violation of laws or ethical standards without anyone realising it. Therefore, it is important for organisations to be transparent about their data decision-making process and to ensure that their algorithms are programmed to prioritise ethical and legal considerations. 

This is where Juris Mindcraft succeeds —  it is an explainable AI, which means it can provide an explanation behind every decision reached. An example of what Juris Mindcraft is capable of is using and providing statistics or past data to support the reason behind prediction.

JurisTech, Your Preferred Partner

The ultimate business goal of using big data in the financial services industry is to gain real-time insight from the data to drive business operations forward. No doubt, the ability to effectively collect, manage, and analyse vast amounts of data will be a game changer for many businesses. But if it is not managed well, it may have the opposite effect, rendering data meaningless. 

If you are looking to take advantage of the power of big data in the financial industry, contact us today for more information. Our team of experts will work with you to understand your unique needs and provide you with solutions that meet your specific requirements. We are passionate about helping our clients in their digital transformation journey, and we have the expertise and tools to help you succeed!

About JurisTech

JurisTech (Juris Technologies) is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

As one of the Fintech pioneers in Malaysia, our vision is to enable financial inclusion for the financial industry with our diverse range of solutions. Check out our latest AI-powered technology Juris Mindcraft, an explainable and adaptive AI that provides an explanation behind every decision reached, which helps banks and financial institutions to transform their digital landscape. 

If you are interested in taking your business strategies to the next level with data-driven decisions, consider Juris DecisionCraft, an automated decision engine that orchestrates and synergises data and analytics from different systems or sources to achieve the best result.

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The financial industry is evolving at an unprecedented rate, with banks all over the world entering into a new era of digital automation and decisioning. Financial products that once required large amounts of paperwork and manual labour are now completely automated, where most processes can be completed by customers at any location with the help of omnichannel platforms. Loan origination is no exception, as the traditional process is prone to human errors due to the need for multiple form entries, as well as other problems like the long loan approval wait time that would massively put customers at an inconvenience. 

Banks are beginning to forego the outdated traditional loan origination systems and are exploring options to digitise their processes, looking to eliminate the problems aforementioned and cut major long-term costs by making use of technology. However, financial institutions might still be experiencing new-found problems with their current loan systems, with parts of the loan approval processes still being manual, causing long waiting periods. 

Loan origination systems might also experience issues with how to successfully integrate their systems with the main core banking or legacy systems. Systems that require programming knowledge are also ineffective, as training hundreds of employees on different programming languages that each system implements individually can be extremely costly, and the alternative of hiring experts isn’t exactly cost-effective either. 

Thus, banks are looking for a solution. Finding a quality loan origination system that is able to solve these problems and ease the origination process all while saving time and resources.

What better system to upgrade to than Juris Origination.

So, how does Juris Origination help?

Juris Origination aims to simplify the entire loan origination process and integrate the system with the bank’s main systems. It is a one-stop web-based system built on powerful application server technology that uses a graphical user interface (GUI) with drag and drop capabilities, aiming to make the system easy to use, even if the user has zero programming experience. We go above and beyond to completely optimise our system and present solutions to problems that financial institutions (FIs) may not have considered. Here are some methods that Juris Origination implements to optimise and ease the user experience:

• Straight-through processing (STP)

Juris Origination makes use of STP that helps expedite the loan lifecycle process, from data entry to post disbursement management. Our system aims to completely ease the user experience by eliminating manual labour and paperwork effort. To achieve this, our system covers the entire process in customer application management, onboarding, financial approvals, document and disbursement, and post-disbursement monitoring.

• Automation of decision-making processes

Using our system’s built in credit decisioning engine that can be used for qualitative and quantitative scoring, the system user can define multiple score sets and can decide the criteria for each set, which the system itself will sort out. For example, commercial loan applicants that are running a business for more than 10 years are more likely to have a higher credit score than an applicant running a business for only 5-7 years. Each score set will consist of multiple scorecards with a final scorecard that is used to complete the final credit rating.

Juris Origination also allows users to simply combine multiple criteria and the system will then return the values. This enables the complete framework of multi-tier scoring which sorts out the hassles of manual decisioning and passes a fairer evaluation according to a pre-programmed system.

• Automation of document generation (such as offer letters and rejection letters)

Digital automation can eliminate the time spent manually inputting customers’ details and printing documents. Our system makes use of parameterised document templates where case-specific information can be auto-pulled upon generation, and can also be edited in the separate Word document if required by the user. However, the entire process is set to be done automatically to enable STP and significantly reduce human errors from manual input.

• Built-in parameters

Most financial institutions have a wide range of products that offer an equally large variety of set parameters and rules; creating new financial products can be time consuming as the product information may need to be entered completely when processing different cases. Our origination system aims to eliminate that need. 

Juris Origination comes with a built-in product parameter feature, which comes ready with a comprehensive feature set including regulatory parameters, scoring rules to run, link to facility codes, etc. The simplification process that we implement includes a duplicate functionality to create products based on already existing products to reduce the time needed to adjust each field.

• Seamless integration with other systems

JurisTech is a company with a wide range of products, all optimised and procured to deliver the best results in their respective markets. Juris Origination is able to seamlessly integrate into other systems to enhance the entire loan origination process. For instance, a lead management system, financial evaluation system, credit administration platform, including advanced technologies such as integrating an auto decisioning engine or AI (autoML platform) to achieve specific business goals. All in all, complimenting our origination system and enhancing the user journey further. 

Conclusion

The loan origination process can be a tedious one. Finding a suitable system that can cater to all your needs while being user-centric can prove to be difficult, and we aim to solve that. By streamlining, optimising, and automating the entire loan disbursement and its decisioning processes, Juris Origination walks its users hand-in-hand to heavily reduce uncertainty and otherwise make it simple, fast and easy for our customers. Thus, heavily emphasising one of our main core values, customer first!

Take a leap of faith and contact us to find out more at contact@juristech.net!

About JurisTech

JurisTech (Juris Technologies) is a leading Fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.

The post How Juris Origination Can Optimise Your Loan Origination appeared first on JurisTech.