How can we make compliance more effective? Banks, financial service providers and insurance companies are grappling with that big question. In this context, the buzzword “RegTech” is often heard. RegTech is synonymous with the implementation of regulatory requirements with modern software.
RegTech connects Regulatory Systems with Technology
RegTech’s name combines the words “regulatory” and “technology”, and RegTech itself links specialist knowledge of regulation with technology. New software technologies boost agility, speed, and data quality for compliance to achieve better data at lower cost.
To this end, RegTech offers several components:
- Combine the specialist knowledge of the compliance officer with self-learning data knowledge (machine learning)
- Automate processes such as monitoring and clarifications
- Provide external hosting by migrating data storage to the cloud
- Analytics for recognizing unusual patterns in data
What do Financial Service Providers and Insurers expect from RegTech?
Companies expect to integrate regulatory requirements into business departments and IT more easily and to achieve increasing efficiency. One challenge is certainly the amount of data, which continues to increase. In 2006, about 300,000 people were on sanctions lists. Today that number is three million. Automation represents the only hope of handling the data in a structured manner. The core of RegTech is allowing increasingly precise decisions to be reached almost in real time with growing volumes of data.
Compliance Application Cases with RegTech
The automation of monitoring – comparing sanctions lists with customer data, monitoring transactions and securities trading, and assigning customers and business partners to a risk class – has already become an almost classic feature. Concrete objectives are:
- Automate processes to reduce manual processes
- Minimize false positives in order to avoid complex clarifications
- Use multiple sanctions lists to ensure the greatest possible security
- Support suspicious transaction reports via automated report generation
- Ensure data protection in all systems
- Detect fraud (internet fraud/market abuse/identity theft, etc.) via analysis of fraud patterns, including with machine learning
How will the Development continue?
Digital transformation with artificial intelligence, machine learning, blockchain, cloud, etc. will affect the financial industry slowly but surely. Relationship Managers will increasing turn to automated clarifications, giving them more time for consulting. Compliance officers will need to clarify fewer false positives, allowing them to spend more time combining their specialist knowledge with the components of machine learning.
Quo vadis, compliance transparency?
Compliance in particular still has uncertainty regarding transparency, however. The core question is: What compliance decisions can be automated with what technology without sacrificing transparency, which is important for regulators? Only the concepts that always give the compliance officer and the regulator the capability of understanding what decision was made for what reason will prevail.