The digital revolution is reshaping industries across the globe, with data analytics being a key driver of this transformation. Insights gained from data are integral to the strategic decision-making apparatus of companies, enabling cost reductions as well as revenue growth.
Among the industries with the potential to benefit most from this data-powered digital transformation, Financial Services is consistently ranked at — or close to — the top. Whether in determining future product offerings, getting a better handle on risk and credit worthiness, or in cutting costs in the customer acquisition process, the use of data is beginning to redefine banking across the globe.
Data is Enabling Consumer-centricity
According to EY’s Global Consumer Banking Survey, 70% of consumers from around the world are willing to provide more data on themselves, if it results in more relevant products and services being offered to them. Consumer banking is taking the lead in leveraging data, in large part due to the proliferation of relevant data sources. For instance, banks are utilizing customers’ social media feed to determine what products and services to offer. Diverse data points such as social media friend-lists, online shopping behavior, and telecom bill-payment history are used to rank customers by credit-worthiness.
Indian banks are leading by example in this regard; from large players like HDFC and ICICI to smaller regional players, the systematic use of consumer data is resulting in vastly reduced credit disbursement cycles, lower risk, and superior customer relationships. In addition, government initiatives such as JAM (Jan Dham Aadhaar Mobile) are decreasing the information gap between banks and their customers, further enabling the move toward a data-driven future.
On the commercial banking side, though, the picture is not so rosy.
Commercial Banking – The Data Deficit
India Inc. is massive, fast growing, and very opaque. And largely unlisted. While the importance of incorporating data into commercial sales and lending decisions is well appreciated, the sheer lack of access to real-time, high-quality information has been a hurdle for banks. Information on companies — particularly unlisted companies, that make up 99% of the economy — has traditionally been:
Unreliable — Given the unavailability of third-party validated data, banks rely on documents provided by the very companies they are evaluating, exposing themselves to potential fraud. In addition, the information gathered is often out-dated.
Incomplete — To gain a solid handle on credit risk, a variety of information is required — from financial statements and ownership structures to legal and compliance documents and more. Banks find it hard to pull together all of these data-points, resulting in an incomplete picture.
Fragmented — The information that banks are looking for is spread across various disconnected sources. Credit teams spend long cycles pulling together notes from MCA, credit bureaus, ratings agencies, etc.
This information gap explains why the cost of credit to business borrowers in India is significantly more than that to individual borrowers. It also partly explains the headlines in our business papers, which talk about the large NPA (non-performing assets) problem facing the country.
Why is information-driven efficiency important for banks?
In Part II, we will pick apart the numbers that make up banks’ bottom-lines, to understand why information-driven efficiency is not just a luxury but, in fact, a necessity.
