Performance and Monitoring of Financial Institution AI/ML Models
This IDC Perspective highlights the awareness of monitoring AI/ML models for performance. Data is the new gold as far as the development and predictability of AI/ML models. Financial institutions are rich in data and are applying it toward more models in all business and risk capacities. Quality data, explainability of the data, and periodic model review are imperative steps to managing models."It is important to review model outputs and metrics of each model on a regular basis to ensure performance meets standards and also satisfy regulator expectations," said Kevin Dolan, research director, IDC Financial Insights.
Please Note: Extended description available upon request.
- Executive Snapshot
- Situation Overview
- Benefits of AI/ML Models
- Building Versus Buying AI/ML Models
- Model Monitoring and Key Risks
- Bias
- Explainability
- Drift
- Measuring Model Control and Performance
- Key Metrics
- Regulator Concerns
- Advice for the Technology Buyer
- Learn More
- Related Research
- Synopsis
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