Indian Banks going long on Data Analytics

By Manisha Sharma

Big data in banking

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Today companies like Paytm extensively use data analytics to provide an unparalleled experience to customers by extending faster and better services. If Indian banks don’t retaliate there are many other companies waiting in the wings to take away their businesses. Today, the need to build better data-centric products is driving the Banking Industry in India. Customer-centricity, combating cyber threat, compliance and risk management and cost containment are some of the key areas where data analytics is applied.

The first instance of usage of data analytics can be traced back to 2000s when HDFC Bank invested heavily in data warehouses and used descriptive and predictive analytics to track customer’s financial habits. This move created opportunities in the area of cross-selling which is currently one of the biggest tools to retain and attract customers in the Indian banking industry. Complex neural network scoring engine is used to assign a credit score to customers and thus help in reducing money laundering. Another bank that uses Business Intelligence (BI) and analytics to identify serious delinquencies (high risk) and early delinquencies (low risk) loans is ICICI Bank. The bank is using a ‘centralized debtors’ allocation model’ to allocate the right set of delinquent cases to the most appropriate collection channel. ING Vysya Bank created a central data repository via SAP BO in order to provide accurate reports to customers. India’s biggest public sector bank, SBI, is not behind in this quest. The bank uses Social Media Analytics to identify prospective customers and to analyse high delinquencies in loans.

But all that glitters is not gold. According to a latest McKinsey survey, most banks have invested significantly in data infrastructure and advanced analytics but are yet to derive expected results from it. Few common mistakes are not asking the right questions to the algorithms, lack of planning, using analytics on a project by project basis and not deriving the full potential of the tools at a detailed level.

In order to utilize technology for their benefits, banks need to develop two assets: a transformation strategy and a vigorous analytics organization to support the usage of analytics in their day to day activities. Different departments in banks contain a huge amount of data. Complete potential can be realized if small samples of information are brought together. Creating interactive dashboards by making the technology simpler to understand can attract more people to use the tools. Usage of feedback loops can help to market faster than competitors. A deep pipeline of analytics talent should be the top priority of banks.

According to a McKinsey survey, more than 90 percent of the top 50 banks around the world are using advanced analytics. Among other things, a combination of  talented pool of graduates, innovation labs, clear governance plan and robust data quality controls should be some of the significant tools that will help shape a bank’s future in the competitive banking and financial services industry of India.

References:

  • Gupta, B. (2015, February). Analytics in Indian Banking Sector – On A Right Track. Retrieved from: https://analyticsindiamag.com/analytics-in-indian-banking-sector-on-a-right-track/

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