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Artificial Intelligence and Regtech: The changing face of compliance in banking

Regtech is often referred to as the "little brother of Fintech". Little wonder then that much like Fintech, Regtech is rife with action. While Fintech was born out of the need to redefine customer experience that traditional financial services offered, Regtech rose after the financial crisis of 2008, when several banks faced heavy fines.

Financial institutions of today are grappling with a complex regulation and compliance landscape. They need to store and provide data to regulators in ways that are faster, reliable and cost efficient. And technology is increasingly becoming the default answer to this complexity.

Artificial intelligence in banking, though it has been around for some time, is finding several applications in the risk and compliance space. This is mostly because AI cannot only sift through massive amounts of data in seconds, but it can also establish connections in totally unrelated or unstructured data sets. Case studies of AI being deployed to smoothen the compliance process are emerging rapidly. Deutsche Bank recently deployed AI to sift through volumes of recordings - both voice and video - to ensure compliance. The technology can automatically search for terms that auditors monitor, saving the bank hours of manual intervention.

One of the biggest regulation challenges that AI is helping financial institutions deal with is completing regulators' "stress test". This involves modelling, scenario analysis and forecasting and is both a time and cost intensive process. Citigroup recently deployed an AI system from Ayasdi, a Stanford University spinout, to help it go through the US Federal Reserve's stress test. This system uses topology to recognize data patterns and identify complex relationships.

Another important area that AI is addressing for financial institutions is managing customer identity. AI based systems are helping banks onboard customers faster, and bringing in more accuracy in Know-your-Customer (KYC) processes. By automating these processes and achieving orchestration between siloed processes like client on-boarding, legal, technology and compliance, financial organizations can achieve a reduction of 60-80% in their client on-boarding time.

Risk-data aggregation is the other compliance area where banks are deploying AI. Since this involves real-time analysis of huge amounts of data, AI seems like a perfect solution. Machine learning algorithms can help financial institutions identify repayment patterns and predict the chances of default. A good example here is the Aidyia hedge fund, which uses AI to drive all its trades, without any human intervention.

Apart from helping financial institutions improve several compliance processes, AI is also acting as a bridge between Regtech startups, regulatory bodies and financial organizations. The entire ecosystem is coming together to collaborate on not only making compliance effective, but also to drive data driven decisions. Since compliance processes require collection and aggregation of a huge amount of data, Regtech startups are going a step ahead and helping banks derive value from this data.

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