Subject Overview

An advanced study of end-to-end insurance claims management and fraud diagnostics across major insurance lines. The subject integrates claims principles, operations, coverage analysis, reserving, settlement, litigation, fraud risk, analytics, technology, governance, ethics and strategic performance management.

Learning Goal

Enable students to design, manage and improve fair, compliant and cost-effective claims systems; make evidence-based claim decisions; diagnose and control fraud; apply analytics and AI responsibly; and lead contemporary claims transformation.

Syllabus

1. Foundations of Insurance Claims Management

Learning Objective: Explain claim terminology, indemnity, insurable interest, proximate cause, subrogation, contribution, utmost good faith, claim stakeholders and the strategic role of claims in the insurance value chain.

Category: foundation

2. Insurance Products, Coverage and Claim Triggers

Learning Objective: Interpret policy wording, exclusions, warranties, deductibles, limits, endorsements and claim triggers across property, casualty, motor, health, life, liability, marine and specialty insurance.

Category: foundation

3. End-to-End Claims Lifecycle

Learning Objective: Manage notification, registration, triage, investigation, documentation, liability determination, reserving, authorization, settlement, recovery, closure and reopening using effective workflows and controls.

Category: core

4. Claim Investigation, Evidence and Loss Assessment

Learning Objective: Apply interviewing, statement analysis, document verification, site inspection, medical and technical evidence, expert reports, chain-of-custody principles and loss-adjustment methods.

Category: core

5. Claim Evaluation, Negotiation and Settlement

Learning Objective: Make defensible coverage and quantum decisions; evaluate damages; negotiate settlements; manage repudiation, partial payment, ex gratia decisions, alternative dispute resolution and claimant communication.

Category: application

6. Claims Reserving and Financial Management

Learning Objective: Establish and revise case reserves; understand IBNR, development patterns, reserve adequacy, leakage, recoveries, reinsurance claims, salvage, subrogation and the financial-statement impact of claims decisions.

Category: core

7. Legal, Regulatory and Conduct Requirements

Learning Objective: Assess claims obligations under insurance, contract, tort, consumer protection, privacy and limitation laws while addressing fair treatment, complaints, ombudsman processes, litigation and jurisdictional differences.

Category: core

8. Fraud Foundations and the Insurance Fraud Ecosystem

Learning Objective: Distinguish opportunistic, organized, internal, application, premium and claims fraud; analyze fraud drivers through fraud triangle, diamond and rational-choice perspectives; and map actors, typologies and vulnerabilities.

Category: foundation

9. Fraud Risk Assessment and Diagnostic Frameworks

Learning Objective: Design fraud-risk assessments, red-flag libraries, fraud scoring, referral criteria, link analysis and investigative hypotheses while controlling false positives and distinguishing fraud from error or legitimate complexity.

Category: core

10. Claims Data, Analytics and Decision Science

Learning Objective: Use descriptive, diagnostic, predictive and prescriptive analytics for segmentation, severity forecasting, anomaly detection, leakage analysis and workload prioritization; evaluate models through suitable performance and business metrics.

Category: application

11. Fraud Investigation and Response Management

Learning Objective: Plan lawful investigations, conduct interviews, analyze financial and digital evidence, collaborate with special investigation units and authorities, document findings, pursue recovery and select proportionate civil, criminal or contractual responses.

Category: application

12. Claims Operations, Performance and Customer Experience

Learning Objective: Design operating models, service standards, authority limits, vendor networks and quality assurance; manage cycle time, accuracy, expense, leakage, litigation, customer outcomes and employee productivity through balanced KPIs.

Category: strategic

13. Digital Claims, Automation and Artificial Intelligence

Learning Objective: Evaluate digital intake, mobile evidence, telematics, IoT, geospatial tools, robotic automation, computer vision, NLP and generative AI; govern human oversight, explainability, bias, cybersecurity, privacy and model risk.

Category: contemporary

14. Claims Strategy, Governance and Emerging Risks

Learning Objective: Develop claims strategy, governance, audit and fraud-control frameworks; lead transformation and crisis response; and evaluate climate events, cyber claims, embedded insurance, ecosystem fraud, synthetic identities and future workforce requirements.

Category: strategic