Creating effective risk models using machine intelligence


There is an absolute need for financial institutions to have sound models in place that can accurately measure and control risk, proactively detect and prevent fraud, and effectively evaluate capital reserve adequacy. Model failure can be catastrophic to a firm’s financial condition and can lead to serious penalties.

In this whitepaper, you will learn how banks are using machine intelligence to solve their biggest risk modeling, analysis and mitigation challenges, including stress testing, CCAR and Basel III compliance, credit and equity risk modeling, probability of downgrade, loss given default, anti-money laundering, fraud detection and much more. 

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