Provisional Holds Model
Description
This solution will enable the FDIC to proactively manage financial risk by providing the ability to estimate potential overpayments, even without real-time account-level data. The strategic insights gained will allow for the optimization of financial holds, minimizing both overpayment risk and operational inefficiencies.
Detailed example
This solution will enable FDIC to proactively manage financial risk by estimating potential overpayments under different levels of provisional holds in the absence of current account-level data and provide strategic insights needed to optimize our financial holds.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The model supports the provisional holds process by estimating potential overpayment. Appropriate provisional holds allow depositors access to their funds in a timely manner, while controlling risks to the DIF from overpaying uninsured depositors during a bank failure.
Controls / human review
ATO: Not reported; PIA: Not published