Data driven approach allows financial institutions to take decisions at scale and reduce the processing time, says Nageen Kommu, Founder and CEO, Digitap.AI, a tech startup that develops API based solutions for Fintechs and Banks using AI – ML technologies. Excerpts from the interview with Nageen Kommu.
CIO AXIS: Please elaborate on Digitap’s distinctive and comprehensive risk management, AI/ML product stack for financial institutions.
Nageen Kommu: Digitap Alternate Data Rule Engine provides in-depth analytics on a user’s financial health and creditworthiness. We take inputs from 7 different data sources, with appropriate permissions from the user. Basis this inputs, we provide a credit score along with variables related to key financials matrices (eg. income, expenses, liability burden, negative scenarios etc…). This score output is the alternative for bureau scores and the variables assist in building rules based decisioning engines. This helps our clients lend to NTC and riskier customers while keeping a check on bad loans. We have seen our clients reduce their NPAs by upto 40% by using our tools.
CIO AXIS: What are the varied alternate data points and their utility for an effective risk assessment and monitoring?
Nageen Kommu: We take input from 7 different alternate data sources:
- Financial Statements (Bank Statements, ITR, among others)
- Device Data (SMS, App Lists, among others)
- Ecommerce Spend Patterns
- Location (geo-tagging based analytics)
- Employment history
- Telecom based analytics (connectivity matrix, account info)
- Social Media presence
Based on these data points, our AI based algorithm creates the score and other user profile based and financial variables. All of these data inputs provide insights on users’ creditworthiness and repayment propensity, along with a sense of overall user profile as well.
CIO AXIS: Why is there a need for a nuanced data driven approach for the BFSI segment at various stages, from customer onboarding to collection?
Nageen Kommu: India is striving towards financial inclusion which means bringing all its citizens access to financial instruments. In order to accomplish this, there is a need for automation in the BFSI segment in order to serve such a huge population. A data driven approach enables the automation to run efficiently and effectively there by enabling the Financial institution to serve the huge population with ease. Data driven approach allows for Financial institutions to take decisions at scale and reduce the processing time.
CIO AXIS: Elaborate on the emerging Account aggregation ecosystem and how it is triggering an UPI like movement in financial service space.
Nageen Kommu: Account aggregators are RBI licensed NBFCs that enable the transfer of information from one Financial institution (FIP) to another Financial institution (FIU) with the consent of the user. Information sharing through AA will be the next big movement after UPI adoption in the BFSI space in India. AA ecosystem will make it easier for users to share their financial information in a fast, secure and reliable manner. The process is extremely user friendly and the user will have total control with regard to what information he wants to share. The adoption of AA ecosystem will be faster than UPI adoption since the entire flow and process is modelled against the UPI payment flow to provide some familiarity to the user.
CIO AXIS: What is the way forward for the BFSI segment and how is the role of data and analytics integration evolving?
Nageen Kommu: Before the advent of digital age, financial institution used to rely on manual processing of data to take decisions on providing access to financial instruments to customers. With the advent of digital age, FIs started relying on data and analytics to take the same decisions but with more accuracy and faster processing time. Currently, FIs are looking to use data not just for taking decisions in providing access to financial instruments but to also cross-sell or up-sell other instruments to users. They are using data and analytics to tailor make customized solutions to users depending on their unique requirements and are able to do this at scale. We can clearly see that the FIs who have access to data and are able to make better sense of that data will be able to grab the lion share of a customer’s financial needs.