Point of Sale
Data enrichment is a powerful risk selection and fraud detection tool, which when used effectively can reduce operating cost ratios and allow insurers to price keenly, gaining a competitive advantage over their peers.
Data enrichment is a powerful fraud detection tool
Detecting and analysing suspicious claims in a structured, holistic way assists insurers in understanding the fraud typologies affecting their portfolio and informs their counter fraud strategies and internal counter fraud culture.
Data enrichment is an automated process whereby insurers can validate applicant details by cross referencing multiple data sources including eg. claims history, bureau data and possible linked addresses gathered from multiple sources. The data can also be used to enhance the customer experience by auto filling fields in the application process. Customer expectation dictates that whichever buying route selected, speed is of the essence, and similarly, those insurers selling through price comparison sites must provide quotes in seconds.
Therefore as insurers’ appetite for data grows, the supply chain of technology companies and third party data providers servicing their needs has exploded, with new data sources and new entrants to the market witnessed on a regular basis.
How to take informed decision at point of sale
Thanks to CRIF's services, insurance companies can access a wealth of data sources via a centralised and automated decision hub. Data are aggregated and analytic models applied to deliver a risk rating or response to assist in pricing and underwriting processes. CRIF provides bespoke solutions which respond to individual insurer needs at point of quote and sale, with a suite of data products that can be tailored accordingly.
CRIF analyses how an insurer uses data in the underwriting process and applies sophisticated predictive indicators in order to verify the applicant’s identity, confirm prior claims history and validate the information they provide about themselves and their vehicle or property. Incorporating machine learning, these predictive indicators can evolve and adapt to reflect the behaviours of fraudsters and dynamically block them.
CRIF solutions generate responses which help the underwriter make an informed decision with full control.