Preparing Customer Data for Generative AI in Insurance
Generative AI is transforming how insurance providers deliver personalised services. To benefit fully from AI, insurers need customer data that’s ready for AI use. This means creating one consolidated record per customer that accurately reflects all their interactions across the business and its brands.
No more fragmented records spread across departments or brands. No errors or valuable data left unused. Achieving this unified customer record is essential to make AI-driven insights and actions truly effective.
Why Consolidated Customer Data Matters
Customer data is a critical asset that sets one insurance brand apart from another. But larger insurers with long histories face the challenge of managing customer data spread across multiple business lines, especially after mergers, acquisitions, and frequent switching by customers.
According to the FCA’s Financial Lives Survey (2022), individuals hold an average of 16 policies, excluding commercial insurance. This volume makes building a 360-degree view of each customer more complex but also more valuable.
With a comprehensive, single view of their customers, insurers can improve pricing accuracy, product recommendations, and claims management. This also supports compliance with the FCA’s Consumer Duty, ensuring fair value and customer-centric service.
Getting Started: Linking and Matching Customer Data
Advanced data science and sophisticated linking algorithms now enable insurers to quickly and accurately match customer data scattered across various systems. Customer identity resolution technology can identify common links across billions of records held in multiple departments and product lines.
The success of this approach depends heavily on the quality and variety of data used to perform matching and linking.
For example, LexID® for Insurance, a solution from LexisNexis® Risk Solutions, achieves high match rates by leveraging a broad range of public and proprietary data. It condenses multiple records into a single unique identifier—a LexID number—creating a “golden record” that updates over time.
This unified record enables insurers to build a single customer view and develop attributes that support underwriting, pricing, fraud detection, compliance, and claims processing.
AI’s Role Across the Customer Lifecycle
A recent white paper by SAP Fioneer highlights how AI can enhance insurance at every stage of the customer experience. Examples include:
- Automated drafting of personalised policies
- Individually tailored product recommendations
- Streamlined claims processing
The potential of AI depends on insurers having high-quality, well-linked customer data ready for AI applications.
Insurance professionals seeking to understand how to prepare their data for AI can explore relevant AI courses and resources to build the necessary skills and knowledge. For practical AI training options tailored to insurance roles, visit Complete AI Training – Courses by Job.