BUSINESS INSURANCE
jumped 3,000 % year-on-year between 2022 and 2023 , according to Onfido .
Machine learning algorithms are now being deployed to analyse vast troves of claims data and identify subtle patterns that human underwriters might miss – Allstate Insurance achieved a 40 % reduction in claims processing time and a 25 % improvement in underwriting accuracy through the use of predictive analytics , while JPMorgan Chase implemented AI-driven analytics tools , leading to a 30 % reduction in fraud-related losses and a 20 % increase in customer satisfaction .
James adds : “ AI-powered tools can automate claims processing , reducing manual tasks and speeding up response times . This not only improves efficiency but also enhances customer satisfaction by enabling quicker pay-outs and more accurate policy pricing . Additionally , predictive analytics help insurers anticipate future claims trends , further refining the underwriting process .”
Quantifying the unquantifiable : The challenge of systemic risks One of the most significant challenges facing cyber underwriters is accurately quantifying potential losses from systemic events and aggregation risks . The interconnected nature of modern IT systems means that a single vulnerability could potentially impact thousands of policyholders simultaneously .
To address this , insurance firms are moving away from simplistic questionnaire-based underwriting towards continuous , API-driven risk assessment . Advanced models can now
128 November 2024