Streamline and optimize L&A insurance underwriting with data science and AI
Customers now prefer to buy life and annuity (L&A) insurance online quickly. Insurers aim to write as many policies as possible within their risk appetite while using new third-party data for pricing, but this requires time and expertise they often lack. Genpact's AI-powered underwriting triage solution uses advanced analytics and integrates third-party data, reducing cycle times and improving decision-making accuracy.
The push for smarter, faster underwriting
L&A insurers face mounting pressure to modernize underwriting processes, meet evolving customer expectations, and integrate advanced technologies like AI and machine learning. However, fragmented data environments, limited resources, and a lack of expertise hinder their ability to harness new opportunities and deliver seamless digital experiences. Insurers are increasingly turning to external partners to modernize underwriting triage and streamline the end-to-end process.
Optimized underwriting with AI and data integration
Genpact's intelligent digital solution uses AI and machine learning to harness diverse data sources, quickly advancing cases and prioritizing high-value submissions within an insurer's risk appetite. The platform integrates seamlessly with existing systems, allowing for efficient modernization. Simple cases are automatically pushed to accelerated underwriting, enabling underwriters to focus on more complex risks, improving decision quality and overall efficiency.
Enhanced customer experience and cost efficiency
The solution delivers a superior digital experience, improving customer satisfaction through seamless online interactions, from application to claim payout. By automating the underwriting process and streamlining workflows, insurers can significantly reduce costs, particularly when acquiring new business. This improved efficiency not only speeds up policy issuance but also enhances engagement, ensuring insurers remain competitive in a rapidly evolving market.
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