The integration of artificial intelligence (AI) opens up the possibility of saving as much as 22 per cent in costs for financial institutions and saving 30 per cent of the government’s time. India already has lending firms using AI and computer vision to detect scammers through facial recognition tech. Its stock market regulator SEBI is also planning on deploying AI, which can look for abnormal trades to bust insider trading rackets. The RBI has also followed suit and is looking for experts who can build AI that monitors banks and NBFCs round the clock.
Push for a tech savvy administration
A month back, India’s Finance Minister Nirmala Sitharaman had recommended AI and Web 3.0, among other technology, for banks to ensure compliance. Machine Learning is already being used by RBI for supervision, and now it wants to develop advanced analytics for the purpose. The strategy is to use machine learning models for supervisory examinations of NBFCs, payment banks, local banks, and small finance banks.
To enhance on-site and off-site monitoring, the RBI has already sent out an expression of interest for consultants who can work on analytics and machine learning for collecting inputs. Although AI techniques used by global banks for compliance are still exploratory, they are gaining traction, and analytics are detecting issues such as liquidity risks, market risks, and misconduct.
Smart tech to safeguard investments
On the other hand, SEBI is reportedly discussing the use of AI, which allowed casinos in Las Vegas to spot gamblers trying to pull off scams. The tech is considered better than the traditional analytics that are being used by institutions to detect fraud. AI can flag synchronised trades, which are a sign of insider trading, where sales and purchases of stocks are made based on leaked confidential information.
Algorithms that link entities and individuals are already helping SEBI to prove that insider trading took place, with lack of direct evidence. More than 20 million trades are processed by SEBI every day, to look for investors possibly involved in such scams.
