Wokingham, United Kingdom — Financial Stability Board (FSB), an international body responsible for monitoring and making recommendations concerning the financial system worldwide, publishes a new 2020 report on the usage of SupTech (supervisory technology) and RegTech (regulatory technology). This report outlines the opportunities, challenges, and outlook of SubTech & RegTech based on the FSB members’ perspective.
The Financial Stability Board Report covers prior developments in SupTech & RegTech. Essentially, RegTech refers to the latest technologies that streamline the dispatching of regulatory requirements. On the contrary, SupTech indicates the usage of technology to aid supervisory agencies in executing their regulatory functions.
Below are some key insights from the FSB Report:
Key Demand & Supply Drivers of SupTech Implementation
Most important demand drivers:
- Enhancing efficiency & effectiveness
- Improving Insights
Most Important supply drivers:
- Artificial intelligence techniques
- Machine-readable data
- Data strategy
Risk & Challenges of SupTech for Members
Members are facing issues related to:
- Data localization
- Data quality
- Data standardization
Key Factors To Implement SupTech Strategies Successfully:
- Involving Front-line supervisors
- Implementing ‘fast fail’ tactics
- Attracting relevant SupTech talent
- Collaborating with external parties
The implementation of RegTech has been positive among authorities & regulated establishments. Survey results found that about one-third of the members were implementing RegTech tactics.
Typical applications target include:
- Fraud detection
- Anti-Money Laundering (AML)
- Risk management
- Regulatory reporting
Authorities continue to have concerns regarding the operational & cyber risks pertaining to RegTech implementation by regulated members. They are leveraging RegTech increasingly to address certain matters like:
- Identity verification
- KYC (Know Your Client)
- Risk management, monitoring
- Stress testing
Survey results suggest that attracting the appropriate talent remains a matter of concern. Members need potential candidates with relevant technical knowledge and comprehension of regulatory expectations and regulatory fireworks.
Common Data Standard
The study also found that authorities are proposing to create a common data requirement for further streamlining data collection initiatives. Several are now using search engines to scrap open-source data to boost their supervisory intelligence. However, it can also cause unanticipated issues concerning data storage.
Use of ML
Authorities are planning to leverage Machine Learning (ML) to study a large amount of transaction data for AML (Anti-Money Laundering) and Combating the Financing of Terrorism (CFT) purposes. Additionally, they hope to expand the implementation of ML applications for analyzing structures data by scanning public & institution-specific insights.
To read the full report, click here the Financial Stability Board report.