Risk management covers a wide spectrum of disciplines for a financial institution and its CRO, with different types of organizations focusing more heavily on different areas of risk. For example, according to a report by The Economist, retail banks worry most about credit risk, commercial banks about market risk, and investment banks about operational risk. In the same survey, 80% of banks overall consider data science a viable option to measure and mitigate risks. While credit and liquidity risks scare the industry most as a whole, organizations are grasping the potential of big data analytics to link seemingly unconnected events and warn against a possible liquidity crisis. 11 With the power to make more accurate predictions by analyzing a broader set of data points, data science tools help financial organi- zations understand their risks more clearly, model them more effec- tively, and cope better with regulations. 12 Consequently, almost all banks are now investing in data science to improve risk management. Notably, commercial and investment banks especially are looking to not only expand but also centralize their data science operations to drive common standards and best practice across the organization. It’s a wise move, as the same big data infrastructure can empower banks to both mitigate risks and pursue new sources of revenue. 13
4 RI SK
MANAGEMENT
of banks overall consider data science 80%
a viable option to measure and mitigate risks.
© 2019 PROVENIR ALL RIGHTS RESERVED
Made with FlippingBook Digital Publishing Software