Market Trends of Big Data Analytics In Banking Industry
Risk Management and Internal Controls Across the Bank to Witness the Growth
- With the use of cutting-edge technologies, banks can reduce credit risk and make better decisions based on a variety of risk criteria. Banks can control credit risk and avert default circumstances thanks to the big data and analytics platform.
- Additionally, a blatant indicator is the retail bank's use of Big Data analytics for credit risk management. It has been demonstrated that applying credit risk indicators based on behavioral patterns in payment transactions allows for the detection of credit events much sooner than conventional indicators based on overdrawn accounts and late payments.
- Real-time fraud detection using data and analytics tools helps reduce credit and liquidity risk by enabling close monitoring of debtors and the ability to foresee loan default.
- Big data can be used to identify high-risk accounts, as demonstrated by The Bank of America. For 9.5 million mortgages, the Corporate Investment Group is responsible for calculating the likelihood of default, which helped Bank of America forecast losses from loan defaults. By cutting the time needed to calculate loan defaults from 96 to 4 hours, the bank was able to increase its efficiency.
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Europe to Expected to Witness Significant Growth
- The most well-known rule governing how financial organizations exchange and safeguard customers' private information continues to be the General Data Protection Rule of the European Union.
- Moreover, data exchange was made possible through open application programming interfaces (APIs) as a result of the Payment Services Directive (PSD2) by the European Union. Due to an environment where data can be shared freely, the capacity to collect, handle, and analyze data has grown in importance.
- Additionally, it is anticipated that both the number of customers and regulatory revisions will rise shortly. The demand for customer analytics and intelligence technologies should consequently increase.
- The UK-based Lloyds Banking Group employed data analytics to meet the needs of diverse client categories while optimizing growth in targeted segments.
- European retail banks are using Big Data analytics solutions due to the "open banking" trend, which addresses problems that traditional financial institutions have faced for decades.
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