Meet Tan Yan Lun, our Chief Product Officer (CPO) at JurisTech! Yan Lun started his journey with us as a fresh graduate back in 2009, and has been with us ever since! Prior to his appointment as the CPO in 2022, he was heading the Presales business unit in JurisTech for several years. He was tasked with leading the team to successfully assist clients by identifying their needs, providing recommendations and advice that will enable clients to achieve their business goals, and to also coordinating with other various stakeholders!

Now as the CPO of JurisTech, Yan Lun has been constantly challenging the status quo of what excellence is in building and delivering best-in-class products. He leads and provides the company with a clear vision for our overall product suites, and establishes best practices for product roadmaps so that as a company, we are able to exceptionally deliver the right solutions to meet our clients’ business needs and goals.

Here, we have invited Yan Lun to share his journey in becoming a CPO and some of the lessons learned along the way.

1. What are some of your personal values you can share with us?

There are a few values that I hold on a personal level. Firstly, I believe in continuous learning, because you never know when you’ll learn something new that is applicable to your work and personal life. 

Secondly, is to always be open to ideas. Innovation and creativity are the driving forces behind the success of our products. Being open to ideas has helped me and my team to discover untapped opportunities, identify potential areas for growth, and stay ahead of the competition.

Thirdly, never say “it’s impossible”! Everything is possible with a little negotiation and managing expectations. All you have to do is to reframe your thoughts and the discussion from “impossible” to “challenging”. You will find that you are able to shift your focus to finding ways to overcome the obstacles rather than being defeated by them. 

Lastly, it is to always understand the “why”, and the reason behind every little thing that happens. This value has truly helped me communicate more effectively with my team members, and it has also enabled me to understand our customers better – their motivations, pain points, and preferences. Knowing the “why” behind the “what” has allowed me and my team to develop products and features that not only meet our customer’s current needs but also their future needs, exceeding our customers’ expectations.

2. What is your leadership style like?

Personally, I like to help my team reach their own decisions. I do not believe in giving direct instructions (depending on the situation, of course) because I recognise that my way might not always be the best way. I’d like everyone to share their own ideas and we can discuss what is the best way to achieve the desired outcome.  

3. How do you get the most out of your team? What role do you play in that?

As a CPO, I hold various responsibilities and lead a few teams. However, as of today, I believe in giving my team, the Collection Advisory Team (CAT) Team in JurisTech, the freedom to make their own decision as they see fit, while also being available and accessible to the team. This is so that whenever they hit any roadblocks, they would know that they have a place to seek advice or to discuss their roadblocks. This allows the team to learn and develop faster, on top of having higher engagement and better performance.

4. What are the changes you foresee in the near future since you joined the industry, and how do you plan to strategise and execute product-related activities within JurisTech?

When I first joined the company, the tech world was still in its infancy (iPhone 3GS and WhatsApp did not even exist yet!). The world we live in today has changed so much since then. People nowadays are interacting with apps and browsers on their phones more than before. Hence, I believe that the newer generation of products should be more customer-centric, attractive, and interactive. Technology shouldn’t be a barrier to getting work done, it should complement it. 

To strategise and execute product-related activities within our company, we plan to focus on the following areas:

• Innovation: Continue investing in product research and development to ensure that our products remain competitive in this rapidly evolving fintech landscape. Additionally, to ensure our products are powered by advanced technology to drive improvements in efficiency, accessibility, and user experience.
• Customer-centricity: Prioritise understanding the needs of our customers and ensuring our products are solutions to their pain points. On top of that, establishing feedback loops with customers to help identify issues, concerns, and opportunities for improvement, enabling JurisTech to iterate and enhance our product offerings. We aim to provide the right technology and consistently deliver our software with excellence, ensuring the highest levels of customer satisfaction.
• Collaboration: To work closely with our customers and fintech ecosystem partners to foster an environment where we can come together to exchange ideas and knowledge. This helps to identify areas for improvement and to co-create solutions that address customer’s pain points. We believe having a collaborative atmosphere fuels innovation by combining different areas of expertise and perspectives. Thus, creating a more holistic customer experience and personalised financial services.
• Agility: Continue being an agile company by adopting agile methodologies in our product development. This enables us to respond quickly to changing market conditions and customer needs. On top of prioritising continuous improvement and learning to ensure our products remain relevant and effective.
• Overall, we believe that these strategies will enable us to continuously deliver high-quality software solutions that meet the evolving needs of our customers and the market. We are committed to remaining at the forefront of the fintech industry and to leveraging our expertise and experience to drive innovation and growth within the company.

5. Share with us your personal victories in your career in JurisTech and what were the obstacles you managed to overcome.

I started off my career as a technical guy. In my mind, doing sales was not something I would want to do because it involved presentation, talking, and selling to people. However, I was entrusted with starting the Presales unit within JurisTech. It wasn’t an easy transition as I was expected to adopt a more “sales-y” mindset, learning the art of selling, instead of just looking at codes which I was more comfortable with. However, at the end of it, this experience opened my mind to learning that sales is applicable in every aspect of our lives, regardless of our roles. In fact, I would dare say, that even technical guys need to know how to sell the value of their products — or else no one would be using them!

Yan Lun is always keen on bringing fresh ideas and viewpoints to ensure we create innovative solutions and product experiences that are invaluable to the user, the company, and the financial industry.

“As a CPO in JurisTech, I’m thrilled to be at the forefront of digital transformation, helping our clients navigate the rapidly evolving landscape and achieve their goals. Our innovative technology solutions empower our clients to stay ahead of the curve and drive business growth, and I’m excited to be a part of this journey!” — Chief Product Officer of JurisTech, Tan Yan Lun

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. 

We have a team of technical experts and business consultants that are passionate about helping our clients in achieving their digital transformation goals. We believe in working closely with our clients, taking their unique project requirements and organisational needs into account to navigate their systems with ease. To ensure a smooth transition to our clients’ newly enhanced systems, we provide top-quality support that extends beyond project completion, offering comprehensive post-implementation support and training to meet our clients’ ongoing needs.

If you’re interested in learning more about how JurisTech can help you achieve your digital transformation goals, don’t hesitate to contact us today. Our team is always here to support you on your journey towards a more efficient and effective digital future.

The post 5 Questions with our Chief Product Officer (CPO), Tan Yan Lun 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.

The post Mitigating Financial Risks with Big Data appeared first on JurisTech.

Digitisation is profoundly transforming today’s business landscape, impacting businesses and companies across all industries worldwide. Digitisation refers to the process of converting analog information to digital data. As the pace of digitisation increases, data production also accelerates at an unprecedented rate. Experts predict that by 2025, data production will reach a staggering 175 ZB (zettabyte). In today’s data-driven world, businesses are constantly striving to make better decisions by leveraging on modern data; data on sales, growth, performance, etc. Companies are actively collecting information about their targeted audiences to understand their preferences and behaviours, turning them into actionable insights, then empowering them to make informed decisions. 

The availability of such data has led to a need for businesses to effectively manage and use them. However, with so much data to work with, a critical question arises — how confident are you in your ability to successfully harness, manage, and leverage this data?

The problem with too much data

There is no doubt that rapid technological advancement has led to an explosion of data being generated by businesses. Yet, this data is often siloed and is separated into different systems or departments, making it difficult to be accessed or analysed efficiently. As a result, there is a significant barrier in leveraging the data to fuel growth and innovation. 

For instance, non-tech executives must make informed decisions backed by accurate and comprehensive data. But to do so, they often rely on IT departments to streamline data processes, such as integrating data from various sources. This requires manual extraction, transformation, and loading (ETL) processes. The IT staff has to manually create scripts and code to extract data from different sources, transform it into a usable format, and load it into a target database or application. Manual data management is a time-consuming and error prone process that may lead to data inconsistencies, errors, and security risks. Moreover, if data stays siloed, it can be difficult to obtain a complete picture of the organisation, which may negatively impact business operations such as inaccurate predictions and flawed decision-making. Hence, businesses are leveraging modern data orchestration technologies to address these challenges. 

Data orchestration, the key to making better decisions

“We live in a world full of data. But what is the point if data isn’t cleaned to be interpreted? ”

As highlighted earlier in the article, the modern business landscape generates vast amounts of data that is spread across various systems, applications, and platforms, posing a challenge for businesses to effectively integrate, manage, and analyse data. In fact, IT departments spend 60% of their time cleaning and organising data, leaving less room to work on other critical tasks. Data orchestration, however, changes things up. 

Data orchestration is the process of collecting, organising, and managing siloed data from multiple sources (i.e., databases, applications, and APIs) in order to provide a single, unified view of the data. When businesses leave their data fragmented and siloed, they are unable to obtain a comprehensive understanding of what their data is conveying. Data orchestration breaks this barrier by automating the ETL processes and enabling seamless integration and management of data from multiple sources. This does not only help companies drastically reduce the time spent on acquiring and preparing data for analysis, but also allowing them to make the most out of their data. Businesses can now quickly and easily identify trends, patterns, and opportunities, enabling them to improve their decision-making processes.

For example, a retail business can use data orchestration to integrate different data sources, such as sales, customer, and inventory data. By analysing all three data sets together, business owners can gain better insights into their customers’ buying patterns, optimise inventory levels, and make more informed pricing decisions. In short, data orchestration is all about making your data more useful. If your business has multiple data systems, data orchestration may just be what you need.

Elevate your decision-making process with Juris DecisionCraft, our automated decision engine

Juris DecisionCraft is an automated decision engine that orchestrates and synergises data and analytics from different sources to produce the best decision possible. It is designed to empower business executives and decision makers to make fast data-backed decisions at scale. Juris DecisionCraft allows you to uncover actionable insights that will drive your business forward, and this is how:

Advanced integration to various data sources

As a data orchestration engine, Juris DecisionCraft’s advanced integration capabilities allow businesses to seamlessly pull data from various sources (i.e., internal and external sources, third-party data sources, alternative data, AI/ML models, etc) to provide the best result-based decision recommendation. For instance, if a business is using any automated Machine Learning (autoML) or AI platform such as Juris Mindcraft, Juris DecisionCraft is able to streamline the AI model selection process by orchestrating AI models from different systems and recommending the best one for each unique situation.  By leveraging Juris DecisionCraft’s powerful integration capabilities, businesses can make data-driven decisions that are both accurate and timely. This feature enables businesses to gain a more comprehensive understanding of their data, while providing them with a clear and concise recommendation that they can trust.

Make data-driven decisions in real time

Many decision-makers and executives perceive that quick decisions come at the cost of good ones. Our automated decision engine challenges this notion. Juris DecisionCraft does not only automate data processes, but is also able to seamlessly integrate new data in real-time, enabling the new data instantly available for analysis. Thus, encouraging proactive decision-making that gives businesses a competitive edge. For example, a loan that used to take weeks to approve can now be processed within minutes, allowing your business a chance to dominate the market. 

Besides that, its ability to synergise and orchestrate data enables businesses to make confident decisions quickly without the need for manual analysis or lengthy discussions. Businesses can now respond quickly to changing market conditions and customer needs. Simply input any type of data from any source or system, and Juris DecisionCraft will do its magic!

Assess potential business impact before deployment

It is essential that businesses are proactive in preparing for potential fallout that may arise so that there is a higher chance for recovery. To facilitate this preparation, our decision engine provides businesses the tool that allows them to test and refine decision models before they go live. This allows businesses to simulate different scenarios and evaluate the potential impact of each decision on their operations. Juris DecisionCraft also provides error-checking and logic validation tools to help businesses identify and fix any issues before deployment. Ultimately, this approach helps businesses improve their decision-making processes, minimise risks, and increase their chances of success. 

The Champion Challenger

Juris DecisionCraft is also equipped with a game-changing feature — the Champion Challenger. This feature is designed to help businesses determine the best decision model for any given situation, while allowing decision makers to update and configure the current decision model with ease when necessary. Champion Challenger allows businesses to run simulations and test different decision models and their potential performance or impact towards current decision rules. Businesses will then obtain valuable insights into how certain decision models would perform in real-world scenarios. 

And that’s not all..

That is only the tip of the ice-berg, there is more to what Juris DecisionCraft can do. Our automated decision engine aims to help businesses in streamlining their data processes, reduce errors, and ultimately, improve data quality and security through data orchestration. We understand that data is complex, and to manually manage and orchestrate them will hinder your day-to-day operations. Yet, if data continues to work in silos, we will never be able to unlock its true potential. If you want to stop working for your data and make it work for you instead, contact us today! At JurisTech, we are always here to support you on your digital transformation journey.

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 Achieve Better Decision Making with the Power of Data Orchestration appeared first on JurisTech.

The world has been undergoing a rapid technological change, advancing so fast that what was once deemed a science-fiction dream is now a critical part of our everyday lives. Artificial intelligence (AI) refers to a machine’s capability to carry out mental processes such as learning, logic, reasoning, problem-solving, perception, and creativity. Once believed to be exclusively human, these skills can now be replicated by technology and be applied in every industry (i.e health care, finance, automotive, etc). Over the past few decades, AI has achieved many technological breakthroughs, from playing checkers to generating its own content! 

According to IBM Global AI Adoption Index 2022, AI adoption is growing steadily, with 35% of companies and organisations having already deployed them and 42% at the exploration stage. There is no doubt that AI will continue its explosive growth into 2023. Here are three AI trends to lookout for in the coming year.

1. Explainable AI (XAI)

Like human nature, bias also exists in AI. Bias in AI occurs when the machine produces results that are systematically prejudiced. Algorithmic bias exists due to it being trained and fed (consciously or unconsciously) data sets that are prejudicial towards certain demographics (i.e race, gender, nationality, age, class, etc). This is a major concern for many industries. For instance, in the financial sector, AI offers an opportunity to create a fairer and more inclusive financial system through alternative credit scoring. It is able to avoid the traditional credit scoring and reporting system, which helps to perpetuate existing bias in the industry, especially towards the unserved and underserved market. However, if the data set that is being trained and fed into the system is biassed in the first place, the AI will then produce algorithmic bias, causing it to amplify pre-existing biases.

Fortunately, the rapid advancement in tech has pushed companies to do more to combat algorithmic bias — which is through explainable AI (XAI). Gartner defines XAI as a set of capabilities that describe a model that highlights its strengths and weaknesses, predicts its likely behaviour, and identifies any potential biases. With XAI, machine learning (ML) models are no longer “black boxes” as they are able to provide an explanation of the decision made, thus creating AI models that are transparent, understandable, and allows room for course-correction. For example, XAI solutions in the lending landscape will be able to help lenders to not only explain to consumers why their loan applications were denied, but also to identify any subtle systemic bias in the model output and retrain them as necessary. 

2. Adaptive AI

Next on the list is Adaptive AI. Flexibility and adaptability are the name of the game. The COVID-19 pandemic has taught us that there are bound to be unpredictable situations and the slightest disruption in the market or environment can cause drastic and significant impacts on many businesses and organisations. At the same time, decision-making is becoming increasingly connected, contextual, and continuous. This results in decision intelligence systems becoming more complex and will need to be reengineered to use adaptive AI so that it can exercise more autonomy when adapting to the changing environment. 

Gartner defines adaptive AI systems as systems that support a decision-making framework centred around making faster decisions while remaining flexible and adaptable when new issues arise. These systems aim to continuously learn when being fed new data and adapt more quickly to changing real-world circumstances. In other words, adaptive AI can revise its code to incorporate what it has learned from new data and adjust accordingly even for changes that were not anticipated or known at the time the code was first written, all while maintaining accuracy. It is effectively learning as things are happening, and it can occur while in production or even in post-deployment. Hence, the deployed model can be used over the years without having to replace it.

Undeniably, adaptive AI will transform businesses across the globe. In the financial industry, adaptive AI will be able to help lenders to predict self-curing customers. Self-curing is a strategy that gives a grace period for customers to proactively repay their outstanding balance before using the organisation’s resources to contact them requesting for that repayment. Self-curing predictions are assisted by a set of predictive rules generated by an AI model. By incorporating adaptive AI, the model will continuously learn as it absorbs more data, allowing it to automatically update and improve itself whenever new data gets fed into it. This means that the model would have the flexibility to adapt to changing conditions and improve its prediction accuracy all the while maintaining the model’s relevance. For instance, if a recession were to occur, spiking the debt to income ratio, the model would still be able to adapt to the changing conditions to predict self-curing customers. Therefore, debt collectors can now strategise and focus on customers with higher probability of defaulting as technology now provides greater insight and management for self-curing accounts.

3. Generative AI

Over the past five years, venture capital firms have invested over $1.7 billion into generative AI solutions. Generative AI gained huge traction in 2022, and it will continue to do so in 2023. But what is generative AI?

According to Gartner, generative AI refers to AI techniques that learn a representation of artefacts from data and use it to create entirely new, original artefacts that preserve a likeness to the original data. The artefacts produced can take the forms of text, image, video, audio, and code, which could potentially be a major game-changer for many businesses. While generative AI is highly popular within the creative industry as it makes content creation much easier, but even so, its influence in the engineering field should not be disregarded. One of the greatest advantages of generative AI in code generation is improving developers’ productivity by providing suggested code. It is worth noting that the goal is not to eliminate human programmers, but to help them to improve their speed and effectiveness in coding while minimising bugs and errors. As proof, one Deloitte experiment showed that engineers using AI to generate computer codes has sped up development time by 20%. 

AI has changed our world and it will continue to do so

AI is evolving at an unprecedented pace and will lay the groundwork for more technological innovations and business opportunities. As the technology matures, businesses are coming up with innovative ways to incorporate AI into their products and services, whether it is to stay relevant in the ever-changing environment or to set themselves apart from competitors. In 2023 and beyond, businesses and organisations will continue using AI to simplify complex work and executives should start preparing their companies for the AI-enabled future. 

So here’s the million dollar question — how many of these AI technologies is your business planning to use in 2023?

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.

The post Top 3 Artificial Intelligence (AI) Trends to Look Out for in 2023 appeared first on JurisTech.

Financial inclusion is a hot topic in the financial industry. Over the past few decades, Malaysia has made significant steps in accelerating financial inclusion for its people. According to the inaugural 2022 Global Financial Inclusion Index from Principal Financial Group, Malaysia is ranked the 20th most financially inclusive market out of 42 markets. The nation’s financial system received high scores for enabling business confidence, and the government’s support was ranked in the top 10 for laws and regulations prioritising consumer financial protection. As Bank Negara Malaysia (BNM) announced the winners of the digital banking licence, the nation is now moving towards a more inclusive financial system.

Financial inequality in SEA

A significant population of the world lacks or has inadequate access to financial services. Southeast Asia (SEA) is still experiencing low levels of financial inclusion, with 290 million of the total population that are still unbanked and underbanked. Two years ago, when the pandemic hit, it was especially hard for poor urban households. In 2020 alone, 97 million more people were pushed into poverty as a result of COVID-19. As they have no access to financial products and services, they have suffered disproportionately.

Figure 1: The percentage of unbanked, underbanked, and banked consumers in SEA (Source: Business Insider)

What is financial inclusion?

According to the World Bank Group, financial inclusion is a key enabler in reducing poverty and boosting prosperity. Financial inclusion refers to the provision of suitable, affordable, and quality financial services such as transactions, payments, credit, savings, and insurance to all segments of society, including the unserved and underserved markets. The United Nations (UN) states that the lack of access to a bank account is the key barrier to greater financial inclusion. Having a bank account is the first step as it serves as a gateway to most financial services. A bank account enables an individual to store, send and receive money. Yet, only 69% of adults globally have a bank account.

Figure 2: Adults without a bank account in 2017 (Source: Statista)

With the lack of a bank account, it robs individuals of the available financial services such as access to loans to increase their standard of living.

Common limitations and challenges to a financially inclusive world

1. Lack or no credit history

To get your loan approved or even get a credit card as an individual or a business owner, your credit history matters. The conventional lending models rely heavily on an applicant’s established credit history during credit scoring as it is able to provide lenders with in-depth insights into the applicant’s borrowing and/or spending habits. If you have a good credit history, you would most likely be eligible for the loan. If you have bad credit data or lack thereof, chances are, you will most likely get rejected as you will be classified as having a high risk of default. The latter is most likely the case for the unserved and underserved. After all, no financial institutions will place their confidence in individuals who may not be able to repay the entire amount.

2. Product market fit

Product market fit is a common barrier when it comes to serving the unserved and underserved market. Oftentimes, the financial products and services offered do not accommodate the capabilities of people of these segments. For instance, inflexible tenure, too many documentation requirements, high-interest rates, slow loan disbursement, etc. This is especially true for microenterprises and small businesses as their financial needs are often characterised as high in complexity and low in scalability. 

3. Affordability

Furthermore, in order for financial services to be widely accessible, financial products and services must be affordable, and the costs involved have to be sufficiently low as well, in order to ensure profitability despite limited revenues. As you can probably tell, offering financial services to these market segments tends to have higher costs and lower revenue streams. If banks are unable to generate profit from these services, it would be extremely difficult to scale or incentivise them.

The role of digital lending in increasing financial accessibility

Increasing financial access to borrowers who are unlikely to receive it is the first step to a financially inclusive society. Innovation and technology are the keys to making it happen. The ongoing COVID-19 crisis has accelerated the creation and adoption of new technologies across all sectors, and the financial industry is no exception. In fact, the lending industry is experiencing a paradigm shift towards digitisation and automation. Digital lending is now a rapidly growing global phenomenon and a crucial key to increasing financial inclusion.  

We are all well too aware of how time-consuming and lengthy the traditional lending process is. Digital lending, however, makes it possible for potential borrowers to apply for loan products from any time and anywhere, as long as there is internet access. Financial institutions also greatly benefit from this technology, ranging from boosting productivity to providing speedier services to their customers.

The key to driving greater financial inclusion

1. Alternative data for credit scoring, making loans accessible

Digital lending enables non-traditional ways of doing credit scoring. By making use of alternative data, banks and financial institutions will be able to tap into the unserved and underserved market to rate a borrower’s creditworthiness during the loan approval process. With alternative data, lenders will have access to data such as an individual’s spending patterns and behaviour through digital channels like e-wallets. This is a huge game changer for those with no credit history. Lenders will also be able to expand their customer base, provide more loans, and drive greater revenue! Lending is core to a bank’s profitability after all. 

In addition, coupling alternative data together with artificial intelligence (AI) and machine learning (ML) could also lead to increased financial inclusion. According to Gartner, explainable AI (XAI) has a huge potential to boost financial inclusion in banking, particularly in terms of helping banks to evaluate a wider selection of customers on their ability to repay whilst also solving the “black box problem.”

2. Provide cost-saving digital financial solutions

Digital lending has a significant potential to bridge the funding gap — by providing financial solutions at a lower cost. The average customer acquisition cost (CAC) in the banking sector is already fairly high, costing more than $300 per customer. The figure is also seen rising due to the negative effects of COVID-19 and the saturation of digital channels. Moreover, the complex and rigorous manual processes in traditional lending are not helping either as it leads to high overhead costs. 

Fortunately, the customer acquisition and loan processing costs for digital lending are much lower. Digital lending models are able to digitise the customer journey for a loan product; the customer onboarding and KYC, loan processing, and loan disbursement. This reduces the need for human intervention as everything is automated, thus reducing manual operating costs. As a result, banks are finally able to provide affordable financial products to the unserved and underserved market while expanding their revenue streams and ensuring profitability.

Our journey to a more financially inclusive world

In JurisTech, we believe that financial inclusion is the key to closing the inequality gap, reducing poverty, and promoting economic growth. We do our part by providing future-ready technology that reimagines financial services. Are you ready to build and enrich lives with our proven solutions? 

Drop us an email today at contact@juristech.net!

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. 

If you are looking to digitally transform your origination process, check out Juris Origination, a loan and financing origination system that automates the entire loan application and approval process. Juris Origination can be coupled with our artificial intelligence (AI) engine, Juris Mindcraft, to provide alternate credit scoring for greater financial inclusion.

The post Financial Inclusion: How Digital Lending Can Help appeared first on JurisTech.

On 11th November 2022, our CEO, See Wai Hun was invited by Taylor’s University to share insights on Malaysia’s latest financial landscape, and how it is disrupting the future of financial and banking services. 

After a fun ice-breaking session, Wai Hun began the talk by explaining how the industrial revolution (IR) for the past few decades has changed the world. In IR 1.0, traditional forms of work such as handicraft manufacturing were replaced with machines. IR 2.0 was a phase of rapid scientific discovery, standardisation, mass production and industrialisation. Whereas in IR 3.0, the rapid advancement of computer technology made it possible for people to use computers in their homes and offices.

How will IR 4.0 disrupt the financial industry?

Wai Hun shared that IR 4.0 is a new phase where modern forms of information technology are used to enhance and improve manufacturing processes in multiple sectors. The financial industry is no exception. Banking services are thriving due to the favourable impact of digital innovation in the industry bringing in new competitors entering the financial space such as digital banks.

Digital bank, a new era of banking

Wai Hun explained that a digital bank is one that operates wholly through the internet or other electronic platforms. Unlike brick-and-mortar banks, digital banks do not have any physical branches as everything banking can be done online. Digital banks provide speed, flexibility, and convenience, a huge customer experience boost.

Besides that, digital banks encourage financial inclusion. Wai Hun mentioned that Southeast Asia (SEA) is still experiencing low levels of financial inclusion. There are a total of 290 million of the population that are still unbanked and underbanked but digital banks may just be able to change that! For instance, digital banks are powered by more advanced technologies such as data analytics and artificial intelligence (AI). To determine an individual’s creditworthiness, traditional banks would have to rely on credit history whereas, with AI, digital banks can make use of alternative data (i.e. utility payments, rental payments, shopping history, mobile data, etc.) to better understand the repayment capacity of the individual. Hence, Wai Hun believes that this will leave a huge impact on the unserved and underserved people such as the low-income and early-income groups, in increasing their accessibility to finance. Thus, driving greater financial inclusion as a whole.

Highlighting an example that Wai Hun brought up, is the AEON Credit and MoneyLion Consortium, one of the winners of Malaysia’s digital banking licence. AEON Credit is a consumer finance company that provides financing (i.e. personal loans, motorcycle and used-car loans) to customers who are predominantly from the B40 group while MoneyLion provides a platform that is powered by technological capabilities such as data analytics and AI. She mentioned that the partnership between these two companies would enable the new digital bank to develop products and services that are able to address the unserved and underserved market’s pain points.

To stay in the game, traditional banks have to digitalise

However, with all the fancy perks, digital banks are not without their challenges. Wai Hun then puts out a simple question to the students present, “Would you put your salary and all your savings in a new digital bank?” 

“Trust” is the name of the game in the financial industry. Although customers are accustomed to the convenience of digital services, it may take years for digital banks to build the same level of trust that customers have with incumbent banks. But if traditional banks were to digitalise, they stand a chance to stay ahead of the game as they have what digital banks lack — trust. 

The talk ended with a conducive Q&A session between Wai Hun and the students, followed by a sincere act of gratitude by the event organiser to Wai Hun for shedding light on the latest development in the Fintech industry.

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 CEO See Wai Hun on New Financial Landscape with Taylor’s University appeared first on JurisTech.

From left to right: Paddy Tan, Managing Partner of Blackstorm Consulting; See Wai Hun, CEO of JurisTech and iMoney; and Salim Dhanani, CEO and co-founder of BigPay

On 26th October 2022, UOA Group in collaboration with Malaysia Digital Economy Corporation (MDEC) invited our CEO, See Wai Hun to an event called “Up Close and Personal with Successful Fintech Technopreneurs.” Wai Hun and Salim Dhanani, both panellists, together with Paddy Tan, the moderator, shared their journey as an entrepreneur in the Fintech industry. 

One burning question that Paddy, the moderator asked the panellists was on how data would change the Fintech landscape. Wai Hun shared that with new Fintechs emerging and embedded finance slowly becoming the next big thing, offering financial services to the B40 group in Malaysia will not stay far-fetched for long. Fintechs use non-traditional ways of doing credit scoring, such as making use of alternative data to rate an individual’s creditworthiness. With that, we are one step closer to achieving financial inclusion as a whole. Wai Hun also adds that with data mastery, companies or organisations will be able to use it to their advantage, such as creating a hyper-personalised customer experience for various customer segments. Just imagine being able to recommend a product before your customer even realises they need them — the data will tell you just that!

Now that we know data plays an important role in enabling digital and financial inclusion, Paddy asked, “What are the challenges for banks to cater to the B40 group in Malaysia?” According to Wai Hun, the brick-and-mortar banks do not have as much alternative data as many Fintech players. For example, certain Fintech companies have a marketplace that is accessible to all income groups. Hence, they would possess data such as an individual’s spending patterns and behaviour, which greatly helps those with no credit history. As traditional banks lack such data, targeting individuals from these income groups would be a lot more challenging. Salim also adds that it is not actually hard to offer financial services to these individuals — what is hard is ensuring profitability and making money from them.

The audience then asked the panellist what Fintech trends they are most excited about, to which Wai Hun replied, “Artificial intelligence (AI).” Wai Hun believes that AI will be able to make an impact in the financial industry, especially when it comes to serving the unserved and underserved market. Through artificial intelligence (AI), alternative data which comes from non-traditional sources such as financial transactions, web traffic, mobile devices, and public records can be used to assess creditworthiness. Each individual has a lot of data that can be harnessed, and by incorporating AI, companies, organisations, and financial institutions will then be able to identify behavioural patterns of said individuals. 

“Let the data tell you the story,” — CEO of JurisTech and iMoney, See Wai Hun

On the other hand, Salim said he’s excited for cryptocurrencies. He believes that digital currency will be the future of money. Digital currencies have the potential to change how society thinks about money. In fact, some countries are already in the phase of experimenting with them!

Image credit: UOA Group

At the end of the session, the organisers extended their sincere gratitude to the panellist and the moderator for sharing eye-opening insights into their journey as technopreneurs in the Fintech industry. 

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 How Would Data Change the Fintech Landscape? appeared first on JurisTech.

Image credit: Unsplash

What is one of the most common mistakes data scientists make? Overfitting. 

What is overfitting?

Overfitting is one of the biggest concerns in machine learning (ML). It is a concept in data science whereby a machine learning model performs very well for training data but gives a poor performance with new data. For instance, when the AI model trains far too long or too complex on the training dataset, the model can start to learn the “noise,” or irrelevant information. What happens is that when the model memorises all the “noise” and fits too closely to the training set, the model becomes “overfitted”. Thus, unable to generalise well to a completely new or unseen data to make accurate predictions. This becomes a serious issue for machine learning models that are used to make predictions. 

This is where ensemble learning comes into play.

What is ensemble learning?

Ensemble learning is a popular machine learning technique that combines several models to improve the prediction accuracy, generalisability and its robustness. Noise, variance, and bias are the main sources of error in machine learning models. Ensemble methods play a huge part in reducing these error-causing elements, ensuring the accuracy of the machine learning algorithms. There are three types of ensemble learning — bagging, boosting, and stacking.

Bagging: A method where multiple versions of a predicted model, which is usually a weak model, are aggregated and each model is trained independently.

Boosting: A method that combines a set of weak learners into a strong learner to minimise training errors. Unlike bagging where each model runs independently, boosting requires the algorithms to “work together”. Every model that runs will determine what features the next model will focus on.

Stacking: A technique that combines different families of algorithms together to strengthen the model’s robustness. Instead of just selecting the best individual algorithm as the final model, the model will select other algorithms that perform almost as good as the best algorithms do during the optimisation process. 

And all these algorithms are supported in Juris Mindcraft!

Juris Mindcraft, effortless AI for intelligent business decisions

Juris Mindcraft is our very own proprietary artificial intelligence (AI). It is an automated AI system that uses advanced machine learning techniques to build powerful AI models. We developed this technology with one goal in mind — to assist enterprises, especially banks and financial institutions to make intelligent business decisions and gain insights to solve real-world problems. 

Juris Mindcraft automates the end-to-end machine learning model development process from importing data, data pre-processing, ML modelling, all the way to deployment. It empowers business users and data scientists to take action on explainable AI recommendations, achieving critical business objectives.

How does Juris Mindcraft solve overfitting?

“Juris Mindcraft uses multiple well-known ensemble learning techniques to achieve a supreme model.”

Juris Mindcraft is able to use advanced machine learning techniques to learn from historic data and recognise patterns to build powerful predictive AI models. It also goes one step further by implementing weighted model stacking, where every selected algorithm is given a different weight based on its performance. The higher the weightage of the prediction models, the higher the priority and the importance of the algorithm. As a result, a combination of multiple weighted top models is built — an entity which we like to refer to as a supermodel. 

The supermodel is more robust and less prone to overfitting, thus outperforming any single best performing AI model! This has also led to Juris Mindcraft being capable of continuous and autonomous self-learning to improve its prediction accuracy. Besides that, Juris Mindcraft is also able to automatically update and improve itself whenever new data gets fed into it. Once the AI model goes live, the system will track the model’s performance over time and will automatically replace the existing predictive model with one that yields better accuracy (with human consent, of course!).

AI Supermodel in action!

The pandemic has triggered specific implications such as managing and mitigating credit risk. For instance, the risk of loss arising from a borrower being unlikely to pay its loan obligations in full may impact all credit-sensitive transactions. This includes loans, securities, and derivatives. Changes in creditworthiness differ by sectors and subsectors to a greater degree than they did in previous recessions. Thus, it has become a huge challenge for banks and financial institutions to accurately identify credit risk during the scoring and loan approval stage.

Juris Mindcraft, however, will be able to make a difference. As mentioned above, Juris Mindcraft uses machine learning modelling as a basis to better predict the potential risk and likelihood of a customer defaulting. Furthermore, if Juris Mindcraft is 90% confident that a customer with a good credit rating will be able to pay back the loan without any complications, the application can be approved instantly without any human intervention!

If you are not confident in its decisioning, rest assured — the decision(s) made by Juris Mindcraft is not black-boxed. Juris Mindcraft is an explainable AI, where explanations are given behind every decision reached. The supermodel in Juris Mindcraft enables the system to adapt as more data gets fed into it. Hence, the more data you input into the model, the more likely it is for its prediction accuracy to improve. With Juris Mindcraft and its AI-based algorithm, banks and financial institutions can now crunch huge quantities of customer data in a few seconds to verify customers’ creditworthiness and determine whether to grant them a loan. Thus, enriching the credit risk management process by reducing time-to-market and ensuring accurate credit scores. 

Sounds amazing? That is only the tip of the iceberg! There is so much more to what Juris Mindcraft can do.

When we use the term ‘Artificial Intelligence’, we really mean it

We have a dedicated team for Juris Mindcraft that is in charge of making our AI as accurate and intuitive as possible, so that your data scientists and business experts can put more focus on things that matter — getting insights to solve real-world problems. With Juris Mindcraft, you can now leverage the power of predictive analytics and artificial intelligence to make intelligent business decisions. Do hit us up if you are keen to know more! 

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, which helps banks and financial institutions to transform their digital landscape.

The post Overfitting and How Juris Mindcraft Solves It appeared first on JurisTech.

Image credit: Unsplash

Debt collection is not easy, and that is why you need a holistic debt collection process to increase your collection rate. NexColl, a debt collection solution made especially for debt collection agencies (DCAs), and designed to increase your organisation’s efficiency by using fast-paced predictive dialling, and providing you with a bird’s eye view of your collection performance.

Here are some frequently asked questions asked about our DCA debt collection system.

1. What software is needed to install NexColl?

No extra software is needed! All you need is your computer, internet browser and internet connection. Our debt collection software is fully web-based, which means you can access the software anytime, anywhere. There is also no hardware installation involved so you don’t need to fuss about hardware setup and maintenance costs anymore.

2. How long does it take to learn NexColl?

We understand how crucial it is that new staff are able to learn and use the software in the shortest time possible. Our priority is to allow your agents to be effective and productive as much as they can. NexColl is simple and easy to use; all you have to do is log in via the NexColl website, and you’re good to go! 

3. What file formatsare accepted when uploading files in NexColl?

Our debt collection software accepts bulk file uploads in XLSX and CSV format. 

4. Can we send SMS and email in NexColl? 

Yes, you can send email, SMS and also make calls in NexColl. Sending emails are free, however charges will be incurred for sending messages and making phone calls. Streamlining all the activities in NexColl itself will help you save time. 

5. About the smart dialler, are inbound calls available?

If you wish to have inbound calls enabled, do let us know so that we can configure it for you. Once it’s enabled, incoming calls will be directed to campaign agents, or you can provide us with a phone number that you wish incoming calls to be directed to.

6. Can I record calls on NexColl?

Yes, call recordings will be stored in a report. You can opt to listen to all the recordings or download them in bulk into a ZIP File.

7. If I forget my password, can I reset it myself? 

Yes, you can do it yourself through the website. If you are still facing issues with resetting your password, we will also be able to help!

8. What’s the pricing model like for NexColl? 

We charge a monthly subscription fee for NexColl, and the fee includes services such as hosting and software updates.

9. What kind of tech support do you offer?

Top notch tech support! Your satisfaction will always be our priority. Once subscribed, we will onboard you via face-to-face or online training, and also provide you with user manuals to help you get started. 

If you are experiencing issues and require support from our representative, feel free to drop an email to helpdesk@juristech.net. Our helpdesk personnel will always be ready to provide you the help you need. Regardless if it’s a simple question or you’d like to deep dive into technical questions, you don’t have to be shy to ask us for help!

10. What makes NexColl different from other debt collection software?

• NexColl is intuitive in debt reconciliation, which makes it easy to facilitate the reconciliation process as NexColl will pinpoint any discrepancies in any payment amount, enabling you to compare and contrast the large amount of payments created by your agents.
• NexColl comes with a built-in workflow engine that will help you carry out collection in the most automated manner possible, from managing delinquent accounts to consolidating debts in bulk!
• NexColl provides seamless commission management. If you are part of a panel of a financial institution that uses Juris Agency, commission issuance from the institution can be seamlessly handled in NexColl. This allows you full visibility and clarity on the commission transactions involved. 

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. If you are interested in debt collection software for DCAs, check out NexColl, our one-stop software solution that optimises your collection processes through automation. 

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. 

The post Debt Collection Made Easy with NexColl: Top FAQs appeared first on JurisTech.

On 20th July 2022, our visionary CEO, See Wai Hun was invited by LeadWomen to shed light on blockchain and how leaders can leverage this technology for their businesses. LeadWomen is an organisation that elevates women leaders through meaningful connection, leadership development, and advocacy.  

Blockchain has gained huge momentum as the world progresses towards Web 3.0. But most people are still confused about the terminology, often using the terms ‘blockchain’ and ‘Bitcoin’ interchangeably. What they do not know is that blockchain is more than just a technology that powers the existence of bitcoin.

“If you do not fully understand the concept, chances are, you may be missing out on immense business opportunities that this technology can offer.” – See Wai Hun

In simple terms, blockchain is a distributed, write-only ledger that records transactions between participants. The two types of common blockchain options are the public blockchain (permissionless blockchain) and the private blockchain (permissioned blockchain). 

Figure 1: Two types of blockchain technology

Here’s the million-dollar question; should businesses invest in blockchain?

To which Wai Hun answered, “Before you start thinking of investing, you need to really understand it and what it can do for your business first.”

Blockchain brings a lot of benefits to an organisation, enhancing security is at the top of the list.. This is because blockchain stores information across a network of computers rather than a single server, making it difficult for hackers to view data. It also makes it nearly impossible to alter the records, thus preventing fraud and unauthorised activity. Besides that, Wai Hun also shared that blockchain technology enables greater transparency and traceability. For instance, all network participants with permissioned access will be able to see the same information at the same time, providing full transparency. 

However, there are also certain risks associated with blockchain. One of the biggest concerns when it comes to implementing the technology is its sluggish transaction speed. Bitcoin, the world’s leading cryptocurrency that is riding on blockchain technology, recently struggled with over 165,000 unconfirmed transactions. In addition, some of its users have to wait for two full days to get just one network confirmation!

Now that you know the pros and cons of blockchain, should you implement blockchain for your organisation? Below is a decision path by Hyperledger that will help your organisation decide if now is the right time for your business to implement this technology.

Figure 2: Blockchain decision path. Source: Hyperledger

Throughout the talk, Wai Hun shared a few use cases of how blockchain is used in various industries, one of them is the use ofbeing using smart contracts in blockchain to improve business operations. For example, using smart contracts in crop insurance for farmers. Smart contracts are able to utilise the decentralised oracle networks (DONs) to arrive at a consensus about weather events through many different data sources and trigger automatic payouts when the conditions of a policy are met.

So, where is blockchain heading?

The short answer: Blockchain is here to stay. According to Wai Hun, the COVID-19 pandemic prompted executive leaders to accelerate digital business activities, and this is propelling a renewed focus on blockchain and growth opportunities afforded by a more programmable economy. 

Figure 3: Hype Cycle for Digital Business Capabilities, 2021. Source: Gartner

In a Nutshell,

Keeping up with technology’s rapid evolution can be challenging, but it is also important that businesses stay up-to-date with emerging technologies like blockchain. This is so that businesses will be able to take advantage of and integrate these developments at the opportune time. Just because you don’t understand the technology, does not mean that it is not coming.

“Embrace the technology to explore strategic business initiatives, but avoid falling for the hype.” – See Wai Hun

The event ended with a fruitful Q&A session, followed by a warm appreciation and gratitude to Wai Hun for imparting invaluable knowledge to the audience.

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 “Blockchain for Businesses: What You Should Know,” by CEO See Wai Hun appeared first on JurisTech.