AI Challenges and Limitations in Finance Course
Master AI in credit risk while avoiding bias, model failures, and compliance issues. Learn practical ML techniques, fairness tools, data controls, and governance to build transparent, regulator-ready credit models that drive safer, smarter lending decisions.

flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This concise course shows how to build and manage AI-driven credit models responsibly, covering bias detection, fairness metrics, and mitigation techniques. You will learn core risk modeling methods, data quality controls, explainability tools, and model governance. Gain practical skills for compliant deployment, monitoring, and documentation that withstand internal review and regulatory scrutiny.
Elevify advantages
Develop skills
- Fair credit modeling: detect, test, and mitigate bias in lending decisions fast.
- Credit ML design: build, validate, and calibrate PD and risk models with confidence.
- Regulatory-ready AI: document, explain, and defend models to auditors and regulators.
- Data and drift control: ensure clean inputs, monitor model drift, and act quickly.
- Model risk governance: structure inventories, controls, and safe deployment workflows.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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