Enhancing Profitability in Property and Casualty Insurance through Analytics and AI
Property and casualty insurers in North America are experiencing enhanced profitability and premium growth through the strategic use of advanced analytics and artificial intelligence. According to a recent survey by WTW, a global advisory and solutions company, insurers that integrate sophisticated analytics see six percentage points lower combined ratios and three percentage points increased premium growth compared to slower adopters from 2022 to 2024.
WTW's Laura Doddington, Head of Personal and Commercial Lines, Insurance Consulting and Technology, North America, highlighted that advanced analytics and AI are evolving from a competitive advantage to a crucial requirement for market viability and sustainable expansion. This significant return on investment emphasizes their growing importance in the industry.
Analytics in Underwriting and Pricing
The survey indicates that the majority of insurers are now utilizing analytics in underwriting and pricing. Approximately 80% of insurers currently employ advanced rating and pricing models, with an additional 11% planning imminent adoption. By 2026, predictive models are expected to become standard practice across the sector, enhancing risk management and pricing accuracy.
Claims Processing and Fraud Detection
In claims processing, although the adoption of analytics has been slower, insurers are aggressively planning to expand usage. The deployment of advanced analytics for fraud detection and severity assessment is expected to rise to 65-70% in the next two years. Additionally, the implementation of straight-through processing in claims workflow is set to increase significantly, driving efficiency and reducing claims settlement times.
Large language models and generative AI are already being utilized by over half of the survey respondents, with another 29% planning adoption within two years. Currently, AI to support human underwriting is at 16%, but 60% of insurers aim to focus on this area by 2028, indicating a shift towards AI-driven underwriting processes.
Challenges and Strategic Focus
Anticipated advancements in AI and machine learning promise substantial increases in their application across underwriting, claims, and customer service by 2028. However, data challenges and IT constraints, such as low-quality data and insufficient IT support, remain obstacles for 42% of respondents. Doddington emphasized that a solid foundational strategy for analytics, strong governance, and high-quality data are critical for insurers to gain a competitive edge in a data-centric market.