Compliance with risk management regulations is crucial for financial firms, especially post the financial crisis. Regtech was, therefore, introduced to simplify compliance and risk management.
At present, a large number of regulators are leveraging technology to boost the efficiency of compliance. Technologies like AI, Machine Learning (ML), and Natural Language Processing (NLP) are enjoying wider reach across risk and compliance.
The adoption of Artificial Intelligence (AI) and Machine Learning (ML) helps regulators analyze structured and unstructured data, save time and control costs.
AI is often used to make reporting efficient. The use of AI is widespread in anti-fraud and Anti Money Laundering (AML) areas.
Decision making is an integral part of crime risk management. And AI has been used to support effective decision making in the FCRM.
AI identifies patterns among the data that humans cannot. Using this data, AI would then track every transaction and determine whether it is a theft.
The accuracy would be significantly higher, and the resources needed to monitor the output would be considerably lower than with a rules-based system. An AI system would, therefore, improve its accuracy automatically.
Other advantages include freeing up regulatory capital due to improved monitoring and automation, reducing $70 billion(approx.) that major financial institutions invest in compliance every year.
Conclusion:
Harnessing the power of AI, ML, and other advanced technologies, Regtech works to stamp out fraud, increase compliance, and reduce financial risk- all of these contributing to approx. $2 trillion yearly loss for the economy.
Regtech is here to stay for good. As AI improves, it is only going to evolve, but, only if professionals across the Regtech market apply it effectively to the areas of risk and compliance.
