5 October 2018,
Developed by CNP Assurances, the MPR (Missing Person Recovery) Model took the third position of the 2018 Insurance Awards in the Customer Relations Innovation category at the 2018 Insurance Awards held on 4 October 2018 in Paris. Initially designed to optimise the search for the beneficiaries of escheated life insurance policies, this effective, high-performance technology is now being used in other areas of the company.
Since it was first launched in 2016, the MPR (Missing Person Recovery) model has helped find tens of thousands of beneficiaries of escheated life insurance policies, so the amounts owing to them could be paid. Combining advanced indicators (phonetic matching, geographic cross-referencing, modules for calculating the distance between character strings) with machine self-learning models and recently developed artificial intelligence algorithms, the MPR is a fuzzy matching tool which finds more than 99% of contracts. In the event of any mistakes in entering a person's name, date of birth or any other information about the insured party, the algorithm powerful enough to identify and correct the discrepancy so as to make a comparison between the CNP Assurances insured party and the deceased person.
The MPR model and its fuzzy matching method can be extended to numerous other applications (complete client overview, withholding tax, etc.). These are available from Diwize, a CNP Assurances start-up which provides the market with unique business expertise and tried and tested data science solutions.
"We are delighted to see the work of our team of data scientists recognised. This is the fruit of CNP Assurances’ investment in machine learning across its technical division" says Romain Méridoux, head of CNP Assurances' R&Data’Lab in the CNP Assurances Group's financial performance division.