Active Hackathon

HDFC Bank Uses Advanced Analytics For 10 Second Loan Approvals: Smita Bhagat, Country Head

Smita Bhagat HDFC

Smita Bhagat is Country Head – Government, E-commerce & Startup Banking at HDFC Bank. In an exclusive interaction with Analytics India Magazine, Smita shed light on HDFC Bank’s SmartUp grants initiative, the tech stack at the bank and how HDFC uses data analytics for digital banking and a wide portfolio of financial services in India. 

Edited Excerpts:


Sign up for your weekly dose of what's up in emerging technology.

AIM: Please elaborate on the tech solutions as part of HDFC Bank.

Smita Bhagat: In government and across a lot of institutions, we are understanding the requirements using data and providing end-to-end solutions. For example, the government sector is a complex space and to solve the issues that arise there, we provide government project management solutions where they can have one view of their funds and better manage the funds, and get the best value from the welfare schemes, etc. 

We have also created solutions for government marketplaces, like buying and selling services. In urban local bodies, the entire payment collection can happen through HDFC “My City” app, which is custom made for urban government local bodies. For our agri-tech solutions, the entire agriculture procurement in some of the states and flow of funds to farmers happens through HDFC solutions. We understand the needs of the customers and build solutions accordingly, whether it’s related to IT solutions, stock market related, risk management, fund management, payment collection and more. 

AIM: How does HDFC utilise data analytics and AI?

Smita Bhagat: When we do credit, we use AI/ML and advanced data analytics. Similarly, we are doing for any other segment as well like bill payments, tax collection, fraud management, etc. Depending on the client requirements, we have dedicated analytics solutions embedded in our products. We also have third-party API integration, depending on the needs, and we later do data analytics and machine learning on top of that. We have a dedicated analytics and data science department within HDFC, which performs and manages all those data processes. 

AIM: What is HDFC’s stance Open APIs and open banking for its solutions?

Smita Bhagat: In rural and semi-urban areas, we have used APIs. Our entire loan sourcing is on fintech APIs. We have used APIs to scale up the business faster. In e-governance initiatives, we have used APIs for all products. Loan products are on fintech APIs, and some products are on lead APIs. Similarly, we are using APIs wherever there is business opportunity regardless of the segment. 

AIM: How is HDFC leveraging data to enhance digital banking processes?

Smita Bhagat: There is a lot of work going on with data in banking in India. India Stack is adding a lot of value and data into the economy, particularly the banking sector with account aggregators, bill payments, etc. At HDFC, we use a lot of data analytics for pre-approved loans. We are the only bank in the country, which gives loans to existing customers in 10 seconds, for real-time credit approval. Today, about 35% of our unsecured lending happens in a matter of seconds. 

A lot of data which we have of our customers is being utilised to give them pre-approved offers. We use a lot of data internally to provide a lot of value addition to all our customers, be it enterprise or individual banking users. As far as the general data usage under India Stack is concerned, there is a lot of work being done, and the data laws are still work in progress. A more structured framework for data usage will come in the coming months or so, and that will help a lot as well.

AIM: What are the criteria when you are looking for startups to invest in?

Smita Bhagat: The SmartUp grants are part of HDFC Bank’s endeavour to further deepen our relationship with the startup eco-system in India. Through the SmartUp programme, we are already engaging with the startup community to partner with them in their entrepreneurial journey using smart financial tools, advisory services and technology. We realise that there are startups who are working on innovative solutions to bring a sustainable change in society, be it urban or rural India. Today, rural and semi-urban space is a huge opportunity, and we are using a lot of technology to address it. 

AIM: What are some of the tech segments for startups that you invest in?

Smita Bhagat: When you are a bank, you work in all segments of the economy. So for us, it’s not just fintech startups or payments. We look at fintech, payments, agritech, regulatory tech, legal tech, HR tech, etc. Technology today is improving things in many business verticals, and we are ready for that. We have 9000 startups that bank with us and more than 200 startups, which work with us in different segments. All of those startups possess capabilities in innovation across the board.


More Great AIM Stories

Vishal Chawla
Vishal Chawla is a senior tech journalist at Analytics India Magazine and writes about AI, data analytics, cybersecurity, cloud computing, and blockchain. Vishal also hosts AIM's video podcast called Simulated Reality- featuring tech leaders, AI experts, and innovative startups of India.

Our Upcoming Events

Conference, in-person (Bangalore)
Cypher 2022
21-23rd Sep

Conference, in-person (Bangalore)
Machine Learning Developers Summit (MLDS) 2023
19-20th Jan

Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
21st Apr, 2023

3 Ways to Join our Community

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Telegram Channel

Discover special offers, top stories, upcoming events, and more.

Subscribe to our newsletter

Get the latest updates from AIM

Ouch, Cognizant

The company has reduced its full-year 2022 revenue growth guidance to 8.5% – 9.5% in constant currency from the 9-11% in the previous quarter

The curious case of Google Cloud revenue

Porat had earlier said that Google Cloud was putting in money to make more money, but even with the bucket-loads of money that it was making, profitability was still elusive.