Despite their $38 Billion dollar size, they still consider themselves a small bank. With only 2 people in their Risk Modeling group they needed to find a way to comply with the DFAST requirements without overtaxing their limited resources. The team satisfied the quantitative data in their models with a third party and felt very confident in their accuracy, but now the pressure was on the key ingredient in the models—the data.
Read the case study to learn how the bank’s risk modeling team used Incisive’s Risk Intelligence Platform to fulfill the regulators’ requirements, as well as:
- Locating and validating spreadsheets that serve as key ingredients for DFAST modeling requirements
- Uncovering over 3,500 results in a single spreadsheet
- Saving over $19K in labor costs
- Locating and risk ranking over 931 spreadsheets in less than 20 minutes