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Banking & Insurance August 31, 2017

How Big Data Analytics Is Redefining Banking Sector

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Data is the new asset. New because using data to drive growth was not possible without the lately achieved success in information technology. Digitization of almost every aspect of commerce has enabled wide capturing of data, its storage and analysis through dedicated tools. Recording of transactions in registers is past now, excel files are the new destination for record-keeping and the same has ushered in a phase where data analytics has become both a job function as well as a profitability driver.

How then the banking and financial sector could remain untouched? Gathering, arranging and analyzing data is a key part of operations in this industry, and we note some of the best uses data is put to.

Curbing Fraudulent Transactions

Recording and studying data on customer behavior is the precursor to thwarting any fraudulent activity on the account. Hackers are all out to target accounts held in the banking system and big data analytics offers an opportunity to tackle this. Customer’s transactional behavior is recorded and any unusual behavior on her account that is not in accordance with the documented pattern, as and when it happens, raises an alarm to appropriate authorities.

Managing Risks

Non-performing assets, breach of Basel norms, sluggish credit growth are all risks that face banking sector at every moment. Data holds the key to the real-time analysis of the health of the banking company. Data analytics can help making a pattern of when and why some borrowers default on their repayments; for instance, a company operating in an agro-based industry may witness downturns after a failed rainy season. Data on the linkage between the central bank and government policies and bank’s credit growth is essential to foresee the impact of a policy decision on bank’s profitability.

Also read: How To Tackle Banking Sector Woes

Targeted Marketing

Gone are the days when bank and NBFC employees would call every customer with an offer for a loan. By breaking down the vast amount of data on money held in a customer’s account, past loan sanctioned and repaid and earning and expenses of the applicant, tele-callers steer clear of wasting their efforts on non-eligible persons. Any inquiry for a loan by a probable borrower is duly recorded that triggers customized solution offering by financial institutions.

Also read: Analyzing the target market

Cutting Costs

This is the field where data and its prudent analysis can yield finest results. How much staff do you need in your office on a particular day of the week can be a question answered effectively by reviewing the recorded data. In the long run, this can enable rationalization of the workforce and also shutting of unproductive branches. The number of insurance policies bought online and customer’s choice of a particular plan during these purchases can pave the way for business model adjustment by increasing online presence over sales executives.

Big data analytics is one of the key components of financial services sector today and most companies have factored in this element in their operations. Productivity and profitability will only enhance once all companies embrace data analytics with arms wide open.

Also read: Do We Really Need More Interest Rate Cuts

Disclaimer – The views or opinions expressed in the article are the personal opinions of the author and do not in any way reflect the views of Suvipra. Suvipra does not assume any responsibility or liability for the same.

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