ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYTICS IN INSURANCE RISK ASSESSMENT: OPPORTUNITIES, CHALLENGES AND THE ROAD AHEAD
Affiliation
| DOI | https://doi.org/10.67313/stanzaleafbookchapter.2026.15 Registered |
| Published In | INSURING EMERGING RISKS ADDRESSING PANDEMICS CYBER ATTACKS AND POLITICAL ISSUES |
| Book Editors | Ramya A J. Deepak Kumar K.M. Anitha R. Srikala J. Chandhini |
| ISBN | 978-81-687720-2-1 |
| Pages | 93-100 |
| Publication Date | 17 July 2026 |
| Publisher | Stanzaleaf Publication |
Abstract
The insurance industry, long dependent on actuarial tables and static underwriting, is being reshaped by Artificial Intelligence (AI) and Big Data Analytics. This paper examines how AI and large-scale data analytics are transforming risk assessment across underwriting, pricing, claims processing and fraud detection. Drawing on secondary data from industry reports, regulatory publications and academic literature, the study traces the shift from traditional actuarial models to dynamic, predictive risk engines using telematics, wearables, satellite imagery and unstructured text. It highlights key benefits — improved risk granularity, faster claims settlement, reduced fraud, and financial inclusion for previously uninsurable segments — alongside challenges such as data privacy, algorithmic bias, poor model explainability, cybersecurity risk, and gaps in India's regulatory framework, with reference to IRDAI guidelines. Drawing on illustrative examples from Indian and global insurers, the paper offers recommendations on explainable AI, data governance, regulatory sandboxes, and consumer protection. It concludes that realising AI's potential in
insurance risk assessment depends on embedding trust, transparency and fairness into algorithmic systems.
Keywords
Artificial Intelligence, Big Data Analytics, Insurance, Risk Assessment, Underwriting, InsurTech, Algorithmic Bias, IRDAI