AI Challenges and Limitations in Finance Course
Master AI applications in credit risk management while addressing bias, model failures, and compliance challenges. This course covers practical machine learning methods, fairness assessment tools, data management controls, and governance frameworks to develop transparent, regulator-approved credit models that support secure and intelligent lending practices. Participants gain expertise in creating robust models that endure scrutiny and enhance decision-making in finance.
flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This focused course teaches building and managing AI-driven credit models responsibly, including bias detection, fairness metrics, and mitigation strategies. Learners will master essential risk modelling techniques, data quality assurance, explainability methods, and model governance practices. Acquire hands-on skills for compliant model deployment, ongoing monitoring, and thorough documentation to meet internal audits and regulatory standards effectively.
Elevify advantages
Develop skills
- Fair credit modelling: identify, evaluate, and reduce bias in lending processes swiftly.
- Credit ML design: construct, verify, and fine-tune PD and risk models reliably.
- Regulatory-ready AI: prepare documentation, provide explanations, and justify models to auditors.
- Data and drift control: maintain data integrity, track model drift, and respond promptly.
- Model risk governance: organise inventories, implement controls, and establish secure deployment processes.
Suggested summary
Before starting, you can change the chapters and the 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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