i卡會員

The arrival of the new economy and digital technology creates opportunities for new business models and comes with new risks as well. For example, the emergence of Fintech has brought about new business models, a diversity of transaction patterns and changes in consumer behaviour in the financial industry. There are the key types of Fintech such as Peer-to-peer (P2P) lending, P2P crowdsourcing and initial coin offering (ICO) and etc. The rise in digital products/services has increased data breaches, cyber hacks, money laundering, and other fraudulent activities. Even though the governments and regulators impose stringent laws and heavy penalties, many financial institutions still paid a lot fines for non-compliance every year.

This is the reason why regulation technology (RegTech) came about. RegTech assists in ensuring regulatory compliance by leveraging a plethora of new technologies. For instance, machine learning and artificial intelligence can automatically processing and analyzing a large volume of structured and unstructured data, and increase the predictive accuracy of risk assessment. With improvements in biometrics technology for identity verification, it can provide an efficient and safe way to know your customers. Furthermore, blockchain allows financial institutions to develop more efficient transaction platforms, payment systems and information sharing mechanisms.

RegTech market size continues to grow

The compliance burden has been constantly increasing over recent years. RegTech is essentially the use of new technologies in the context of regulatory regimes to lower supervisory risks for governments and regulatory bodies, and allows flexibility in compliance management and control. This enables the industry to find a balance between regulation and innovation. It is hardly surprising that RegTech is developing into a huge market with great business potential and investment opportunities.

According to Markets & Markets’ report, it indicates that the global RegTech market in 2018 totaled US$4.3 billion and is expected to reach US$12.3 billion in 2023, at a CAGR of 23.5%. North America remains the biggest market, followed by Europe, Asia Pacific and other regions. The issue that companies care about the most is the regulatory oversight on the application of information and intelligence.

With the evolution and advancement of digital technology, financial institutions hope to quickly deploy models capable of accurate forecasting and risk control, in order to detect possible fraudulent activities. However, regulatory complexity and frequency of updates could increase risks for industry. Below is an introduction of the two big data startups and the application of RegTech in the financial market.

Offering compliance information and intelligence for financial institutions is the main business for Ayasdi, established in 2008. Ayasdi AI’s unique technology, topological data analysis, is exceptional at surfacing hidden relationships that exist in the data and identifying those relationships that are meaningful without having to ask specific questions of the data. Meanwhile, the models constructed by Ayasdi across regions and time zones by analyzing data from different markets around the world boost higher accuracy in forecasting compared with traditional market models. In fact, the building of traditional risk models is time consuming as analysts need to keep adding variables to capture different impacts. In contrast, Ayasdi accelerates the process of risk model construction by taking into account all the variables at the outset. For example, the deployment of a Comprehensive Capital Analysis and Review (CCAR) model takes 1,800 person months whilst Ayasdi’s approach takes 6 person months.

Effective identification of transaction risks

Another international RegTech company, Neurensic, focuses on the identification of transaction risks by using big data analytics and machine learning. The purpose is to assist financial institutions, trading companies and regulatory bodies to monitor any fraudulent transactions and illegal activities. Neurensic’s surveillance system uses artificial intelligence to classify the massive amount of daily trading data at counters. By constantly learning and adapting to the behavior and habits of traders, the system understands the preferences of each trader. This means Neurensic’s system can self-adapt and learn about new data. Even if the market and the regulatory scheme change over time, the system can adjust and still enhance its accuracy. Also, the surveillance system can identify highly risky behavior from monitored cases and investigations. This effectively helps compliance personnel to lower costs, mitigate risks and boost efficiency.

RegTech is not as well-known as FinTech or blockchain, and FinTech is still struggling to gain a strong foothold in Taiwan, as stringent regulatory controls and oversight, as well as lack of smooth coordination among government departments, often smother rather than foster development. All these factors have indirectly impeded the development of RegTech in Taiwan. However, the startups in Taiwan boast good technical potential. It is suggested that financial service providers can increase their cooperation with startups to access new technologies and explore new business models. This will help startups to grow, set the stage for the demonstration of new technologies and establish an industry ecosystem offering prosperity for all.