Focus 2021: Accelerated problem detection and pre-emptive action

Sunil Rajguru
New Update

The banking system is on the constant lookout for high-quality data, emerging technologies and a robust FinTech strategy to will assist them, says Jaya Vaidhyanathan, CEO, BCT Digital (Bahwan CyberTek group).


How are we handling the absolute explosion of data of the modern age further pushed by the Covid crisis? What are the kinds of analytic tools that are helping us cope?

In the past, the banking sector has handled customer data primarily within their internal systems like Core Banking System or Loan Origination System. Today, the quantum of data that they can leverage is so enormous and can be overwhelming to make a distinction between good and bad data and to process it towards good decisioning. Even in pre-Covid times, we were using AI to identify NPAs by helping bankers identify large risky accounts and flagging it off for action.

A black swan event like Covid-19 has accelerated the use of AI, Predictive Analytics, Big Data in the banking sector through FinTechs. Bankers now need to quickly measure the impact of a pandemic on their growth and recovery. To depend on even the best of human analytical expertise, this could take months or years to comprehend.


It has opened-up the black-box approach to risk management, offering more accountability and predictability in decision making in the banking system. Today, accessing data is simplified even more through digital sources, by and large, like Credit Bureau information, real-time alerts on corporate actions etc., that synthesize huge volumes of structured and unstructured data sources, thereby making technology inevitable in decision making. This further helped in moving away from orthodox methods to AI based analytics to quickly predict fallouts, quantify data and build recovery measures.

The need for innovation and technology is ever dynamic. Specifically, the banking system is on the constant lookout for high-quality data, emerging technologies and a robust FinTech strategy that will assist them.

Going forward, what will be the role of Artificial Intelligence in all of this? Will AI dominate data and data analytics?


The massive amounts of diversified data from various sources can only be tapped with the use of technology. As we move to 2021, the emphasis will be on accelerating problem detection and pre-emptive action. AI powered technologies can analyze thousands of different data points, based on intelligent pattern matching with a great degree of accuracy within micro seconds. For instance, real-time alerts are essential in preventing high tech frauds possible today in the BFSI industry making it important that the decision-making process is data driven, which requires precise integrating technology through open APIs.

Considering the economy and the financial sector, it is foreseen that banks may aggressively implement AI driven technology systems to control risks. Regulators will now want to intervene before other risks can manifest and thereby push for advances in regulatory guidance for model risks, liquidity risks and operational risks. This will lead to a risk-optimized banking experience which will eventually rely on the strengths of game-changing technologies like AI to redefine the FinTech arena.

Can Deep Tech and local innovation help in ‘Make in India’ campaigns related to sectors like BFSI?


The complex Indian banking sector requires products that are engineered for the Indian market considering the unique gradations that are part of India. Global products that are designed outside India simply may not fit the cultural variations, business complexities and most importantly, the scalability in terms of number of customers/accounts/transactions per day, of this country especially in core areas like NPAs, financial inclusion, payments etc.

We need to look at the technology needs both from the perspective of global regulators and that of the bank. Let us take the case of NPA and the EWS solution for instance—in India, we have alerts that the RBI and other regulators like the DFS have mandated. Over and above, banks depending on their risk appetite, may want to monitor their asset books through custom alerts, focusing on specific sectors or business verticals. To trigger these alerts, the volume, source, and complexity of data have to be considered while engineering the product. Deep Tech and local innovation can definitely help in this regard by coming up with products that are conceptualized for India, designed and made in India and deployed in India.

What according to you is the new normal in the post Covid world and what role does digital transformation play in getting us there?

In a market that is stagnant or in slow growth phase, financial institutions will focus more on risk planning and management. Business cycles during this time may get shorter and new business models will evolve, changing the game. In the new world, conventional technologies will not be able to help stay productive or profitable. When the economy and financial sector revives, the goal will be towards risk mitigation. This holds true particularly when viewed both in the context of banking risks like credit & liquidity risks and in the context of changing regulatory landscape.

Safe and responsive banking will also take the course in the years to come. Accelerated problem detection and taking pre-emptive actions will be emphasized and executed through use of analytics for predictive modelling of macro and microeconomic events, use of Artificial Intelligence to make unbiased decisions with thousands of data points taking the digital realm above and beyond.