by Jonathan Leonardelli, FRM | Feb 4, 2019 | Data
An article published by the Wall Street Journal on Jan. 30, 2019 got me thinking about the challenges of using unstructured data in modeling. The article discusses how New York’s Department of Financial Services is allowing life insurers to use social media, as well...
by Jonathan Leonardelli, FRM | Oct 12, 2017 | Regulations
Determining whether an unimpaired asset’s credit risk has meaningfully increased since the asset was initially recognized is one of the most consequential issues banks encounter in complying with IFRS 9. Recall the stakes: The expected credit loss for Stage 1 assets...
by Jonathan Leonardelli, FRM | Sep 5, 2017 | Regulations
Calculating expected credit losses under IFRS 9 is easy. It requires little more than high school algebra to determine the aggregate present value of future cash flows. But it is not easy to ascertain the key components that are used by the basic equation—regardless...
by Jonathan Leonardelli, FRM | Aug 4, 2017 | Regulations
Under IFRS 9, Financial Instruments, banks will have to estimate the present value of expected credit losses in a way that reflects not only past events but also current and prospective economic conditions. Clearly, complying with the 160-page standard will require...
by Jonathan Leonardelli, FRM | Apr 27, 2017 | Business Analytics
The Federal Reserve and the OCC define model risk as “the potential for adverse consequences from decisions based on incorrect or misused model outputs and reports.”[1] Statistical models are the core of stress testing and credit analysis, but banks are increasingly...
