AI in Insurance
Course Overview
Artificial Intelligence (AI) is reshaping the insurance value chain—transforming distribution, underwriting, pricing, claims, fraud detection, customer experience, and portfolio management. This course offers a practitioner oriented roadmap to designing, deploying, governing, and scaling AI solutions across life & health and general insurance lines. Learners will combine business use cases, data foundations, model selection, responsible AI, compliance, and change management with hands on workshops and implementation playbooks suited to East Africa and global contexts. The program culminates in a capstone where participants design an AI enabled initiative (e.g., straight through underwriting for motor, triage for health claims, or a retention model for retail lines), including metrics, guardrails, and an adoption plan.
Learning Objectives
By the end of the course, learners will be able to:
- Explain core AI concepts (ML, deep learning, NLP, computer vision, GenAI) and map them to the insurance value chain;
- Design data pipelines and feature stores using internal and external sources (policy/claims, telematics, IoT, alternative data) with clear data quality and lineage controls;
- Select, train, and evaluate models for underwriting, pricing, claims, fraud, CX, and portfolio steering; define KPIs and business value;
- Implement responsible AI (fairness, explainability, robustness, privacy, model risk management) aligned to governance and regulatory expectations;
- Build adoption: operating models, skills, vendor selection, change management, and metrics (loss ratio, combined ratio, STP, NPS, retention, fraud savings); and
- Plan and execute an AI deployment with MLOps life cycle, monitoring, drift management, and post production controls.
