AI Challenges and Limitations in Finance Course
This course explores the challenges and limitations of AI in finance, focusing on responsible development and management of AI-driven credit models. It covers bias detection, fairness, risk modeling, data quality, explainability, governance, and regulatory compliance for safe AI deployment.

from 4 to 360h flexible workload
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 modelling 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 modelling: 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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