Decision making made simpler with data analytics

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As the Banking and Fintech sector are moving forward in the digital space, there are many key aspects they are looking at to keep an eye on. Data analytics is one of the key technologies that is going to make a crucial difference in moving forward.

“As the digital revolution is transforming the banking and Fintech industry, analytics will play a significant role in various capacities. Customers will continue to experience more personalised content, products and services that will help them take clever buying decisions. Customer Service 2.0 will become more efficient and smarter with the evolving AI assistants and chatbots. Financial Apps will also become more efficient and secure with the integration of AI based services like face and voice-based authentication,” says Dharmesh Kishore, AVP Data Platform, Innoviti Payment Solutions.

Explaining certain core trends in data analytics, Tushar Garimalla, Chief Growth Officer, Capital Float says, “Some of the core uses of underwriting such as credit decisioning (who to give a loan to, how much of a loan to give), collections strategies (how to bring back money from customers who have missed a payment) and insurance premium calculations are already engaging analytics. These well-established usage cases will continue to get deeper in terms of data types and the quantum of data.

For instance, recommendation engines will become more intuitive and get better at predicting usage of financial products like investment options. Other functions will also witness significant advancements in analytics going forward. For example, customer service is likely to experience improvements in terms of higher accuracy in understanding questions being asked and answering them correctly without human intervention.”

Speaking on certain challenges in the sector, Jaya Vaidhyanathan, President, Bahwan CyberTek says, “Challenges in the analytics space include availability of clean data in machine-readable format – something we can emulate from the US banking industry; lack of intelligence and text mining capabilities in local languages in India, which can give valuable insights into rural banking and financial inclusion; and of course, regulation on data privacy, which is still nascent in the country.”