Analytics in Banking

Written by Pradeep Rao

Introduction:

With the unprecedented growth in both banking and payment transactions in digital form, banks have been becoming repositories of large volumes of varied data piling up at a great velocity. The more the data available, more informed the decisions would be, provided the data is analyzed quickly and meaningfully. More importantly, the hidden patterns are to be recognised and appropriate alerts raised in a useful and usable way. Analytics provides banks with more marketing muscle. Functional areas like Risk, Compliance, Fraud, NPA monitoring and Calculating Value at Risk can benefit greatly from Analytics to ensure optimal performance and to take crucial decisions where timing is very important.

 

Day-to-day functionalities in a banking environment will be severely limited and handicapped if analytic tools were not made available to them. The use of Analytics can help banks differentiate themselves and remain competitive in the future.

 

Analytics can be used in following areas in the Banking function:

Credit risk and Collection

• Lend to right type of customers.
•  Monitor collections.
•  Predict and reduce delinquencies.
•  Reduce NPA and increase profitability.

HR and performance management.

•  Track performance V/s business objectives.
•  Get the best out of people.
•  Reduce attrition.

Finance and treasury

•  Determine interest rates and forecast NII .
•  Monitor and control interest rate risk.
•  Establish risk tolerance levels and submit Intelligence to ALCO.
•  Manage overall funds situation and FTP.

Marketing and sales

•  Design products and make customers aware through various marketing channels.
• Maximize sales at minimum cost through optimizing revenue.
•  Increase customer loyalty and reduce attrition.

Fraud Analytics

Social Media Analytics

 

Benefits of Analytics:

Ø  Analyse deeper into customer experience

Ø  Customer retention

Ø  Improve employee performance

 

Conclusion

Statistical data analysis is taking a huge step forward becoming data analytics by merging with computer science via Machine learning and operation research, which is playing a vital role in many industries, especially service. All types of analytics found immense applications in BFSI sector with some astonishing results. Banks are making big investments for big data and analytics to stay competitive.  While previously the cost of investment was one of the barriers for enterprise wide analytics implementation, it no longer is the case with open source technologies.

 

Source :

1. Article by Sri. Vasudevan, Wipro. https://www.wipro.com/en-IN/banking/banking-on-analytics/
2. Article by IDRBT, Hyderabad https://idrbt.ac.in/assets/publications/Staff%20Papers/Analytics.pdf