With Artificial Intelligence (AI) making inroads into almost all the major industry verticals, the banking and financial services sector, which automatically generates a lot of data, has the biggest use cases for AI.
AI leverages this huge chunk of data to make decisions thus enabling banking and financial institutions to improve efficiency, offer seamless services to their customers, and reduce time and cost in various processes.
According to a recent study by Markets and Markets, the artificial intelligence market, which was valued at USD 16.06 billion in 2017, is expected to reach USD 190.61 billion by 2025.
With a lot of data captured in every transaction, Harshil Mathur, Co-founder & CEO, Razorpay, feels that if you build a platform that utilises large amounts of data to drive the decisions or make the process more efficient, there’s a lot of scope for AI in this sector.
"Even at Razorpay we are using a lot of Machine Learning (ML) for fraud control. Fraud in general has been a big challenge in India. As digital payments rise, the fraud rises with it too. So, usage of AI and ML is very significant in controlling fraud at the base," he adds.
Razorpay uses AI on its banking platform, Razorpay X, to get business insights about how a business is performing. It uses the bank transaction history and bank data to tell a customer when will his business break even.
"Another use case we are looking at is with our other product Razorpay Capital, for SMEs, which again uses AI and ML to see the customer’s transaction history and help him get a loan. Generally, applying for a loan is a very tedious process in this country where you are required to submit a bunch of papers, balance sheet and go through a whole lot of process. But with AI and ML, lending can be done much more quickly, and with much minimal effort from a business side," informs Mathur.
Fintech is an important sector which can utilise AI and ML simply because there is already so much data available. Usage of AI and ML in data analytics plays a transformative role in the banking sector.
Abhiram Modak, Chief Principal Consultant, BFSI verticals, Persistent Systems says, “Data analytics on Big Data streams powered by AI is a new playground for banks and insurance companies. From predicting requirement of loan or a working capital or collating minute details to creating a tailor- made insurance policy for a retail customer are the new competition areas for the financial sector. Data Analytics over structured data is a given but mixing this is with unstructured data and using AI is what makes financial enterprises more like ‘Lifestyle Financial Partners’ over and above their traditional roles.”
When we dive deep to understand the importance of AI in the BFSI sector, two areas are likely to benefit the most from the first wave of AI and ML adoption.
Sharing his insights on this, Sudhir Babu, Vice President and Head of Product Engineering at i-exceed says, “The first area is in the way banking is personalized. AI helps banks in gathering unprecedented number of data points on how their customers are using various touch points and how it is in turn used to customize the bank’s applications, products and services to meet customer expectations.
"The second area is in security and fraud prevention. There are ML models that help in creating a behaviour profile of each user based on the way the user interacts. After that, new transactions can be compared with the base profile and an additional authentication mechanism to prevent frauds can be introduced in case of differences,” he adds.
The unprecedented growth of the AI market can be attributed to increasing amounts of data, adoption of cloud-based solutions and applications, demand for virtual assistants and robotics.
Discover the latest Business News, Sensex, and Nifty updates. Obtain Personal Finance insights, tax queries, and expert opinions on Moneycontrol or download the Moneycontrol App to stay updated!
