AI in Indian BFSI sector: Are we on track?

Usha Prasad

In the last one decade, advancement in technology has had a positive impact on the BFSI sector, with Artificial Intelligence (AI) at the forefront of innovations.

AI surely plays a huge role in redefining the way banking is done, and the banking industry in India is investing big time in machine learning.

Yet to be Mainstream

“While the scope of AI in banking and financial services is tremendous, India is still at a nascent stage when it comes to implementation of AI in BFSI and needs finetuning around customer sensitization and security framework,” says Faisal Husain, Co-founder and CEO, Synechron.

It is expected that AI enabled tools will work in tandem with humans in the coming years. “Private and public banks are already leveraging AI and machine learning (ML) for enhanced customer services and retail payment systems. We anticipate this adoption to only grow in the future and seep into both back-end as well as fraud reducing and security risk operations,” he adds.

Synechron has identified six aspects of AI - NLP, Chatbots, Robotic Process Automation (RPA), Cognitive Machine Learning, Data Science and Robo-advisors, to build 14 accelerators for financial institutions (FI). These reusable applications help the FIs reduce the time-to-market when applying AI to enhance business operations, reduce operating costs and create better client experiences.

“The accelerators streamline processes, allowing them to be elevated to higher-value business tasks and solve complex business challenges,” adds Hussain.

New applications emerge, but challenges remain

"In theory anything that requires ‘less than a minute for a human to think’ can be implemented using AI. Back office is the usual suspect for implementing AI due to its repetitive nature of work. However, a lot of front office functions like Loan Eligibility advice, Wealth Advice are also likely to be taken over by AI to some extent," says Abhiram Modak, Chief Principal Consultant, BFSI verticals, Persistent Systems.

As S. Sundararajan, Executive Director at i-exceed, puts it, “Implementing AI can help banks in getting better insights into their customers’ usage patterns and offering personalised products. It can also play a pivotal role in detecting fraudulent transactions and improving operational efficiency amongst others.”

“However, since it is still a relatively new area, there isn’t sufficient expertise available to address the huge demand. Also, leveraging the available data to build optimal machine learning models that return desired results takes a considerable amount of time,” he adds.