Why data analytics is the lifeblood of BFSI sector in India

Analytics has been one of the key focus areas for the Banking, Financial Services and Insurance (BFSI) companies. The Indian BFSI sector is betting big on data analytics to increase organizational success, increase returns, transform business operations, reduce risks and provide seamless services to its customers.

The usage of data analytics in India has vastly improved over the past few years and obtaining customer intelligence has become simpler.

“Most banks across the Indian banking industry have either struggled with two different points. Either banks haven’t been able to leverage the surplus data which they have collected, or they aren’t able to collect insightful data points from the customer’s touchpoints,” says Anand Subramaniam, Head, Artificial Intelligence Practice, Aspire Systems.

“With thorough digital transformation made complete, it is vital that banks aim to have a thorough data ingestion process, and leverage data to detect patterns and have a predictive analysis model for future problems that the customer wants the bank to solve. Easily put, banks have engaged in improving customer experiences through data analytics,” he adds.

"The banking industry is one of the early adopters of emerging technology in India. Being a data-rich and data-dependent sector, data analytics is of the utmost importance to banks and financial institutions (FIs) and is a significant part of their digital transformation journey. Legacy banks and FIs are investing in analytics to compete and stay relevant in the market. They are cashing in on the business capabilities of analytics for increased profitability and to identify potential customers," says Faisal Husain, Co-founder and CEO, Synechron.

According to NASSCOM, the big data analytics industry in India is expected to reach $16 billion by 2025. By deploying analytics, the BFSI sector aims to solve three major business challenges – performance, risk accessibility and profitability.

“A data-driven approach will help derive actionable insights and achieve persistent and cost-effective customer acquisition. Companies are using data analytics to predict mortgage default risk and for customer authentication,” adds Husain.

Suman Reddy, MD at Pegasystems India lists a few data analytics trends companies are looking at today.

Predictive analytics: Predictive analytics uses current and historical data to predict unknowns like future customer behaviour and activity. For instance, it offers insights into the possibility of customer propensity towards a personalised credit card offer. Its potential is brought out most efficiently when integrated with business processes to draw analytic insights, generating projections that can be used automatically by other systems like a BPM or CRM system.

Adaptive analytics: It allows real-time optimization as customer-specific strategies are automatically adapted to better address customer responses during live customer interactions.

Data visualization: Many organizations hold vast amounts of data, but struggle to discover its business value. Emerging business intelligence and data visualization capabilities will help companies provide actionable intelligence and find discernible patterns within large datasets. Firms can now integrate advanced interactive visualization capabilities within their CRM and digital process automation (DPA) solutions, to uncover hidden patterns, and make smarter business decisions.

Going forward, data analytics will surely change the banking and financial institutions ecosystem.