Case Study

Insurance's missing millions

How Genpact’s ReFinder solution returned more than $30 million in reinsurance claims for a global insurer

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Who we worked with

A leading global, multiline property and casualty insurance provider

How we helped

Our data experts:

  • Mapped the data requirements
  • Ran the data through our proprietary analytical models to uncover leakage
  • Conducted root cause analysis using proprietary and established tools and techniques
  • Refined the data mapping on a continuous basis

What the company needed

To identify missed or inadequately recovered reinsurance claims and the root causes to prevent future leakage

What the company got

  • Identified and collected more than $30 million in previously lost recoverables
  • Confirmation that its reinsurance claims processes and reserve accuracy are over 99% accurate 
  • Better mitigation strategies against future leaks
  • A trusted partner for periodic reinsurance recovery reviews

Financial leakage in insurance claims operations is common. Most insurers work to eliminate it, but many accept that the occasional loss – such as fraud or human error – is inevitable. In some cases trying to recover this money could mean losing a customer. But reinsurance is a different story. 

Reinsurance receivables are often one of the top three assets on an insurer's balance sheet. Reinsurance contracts are often complex multiparty arrangements and not every insurer has IT systems specifically designed to log, process, and calculate claims due from reinsurers. And even if they do, it's typically manual and prone to errors resulting in reinsurance claims leakage.

Challenge

Find missed reinsurance collectables in legacy data

This leading global insurer came to Genpact with a problem. It knew that its systems and processes for calculating, billing, tracking, and collecting reinsurance claim recoverables were ineffective and that it was leaving money on the table.

The leakage stemmed from three key factors:

  • Multiple policy and claim systems not working in sync
  • Complex reinsurance coverage structures
  • People dependency and significant changes in staffing

This meant the overall process was fragmented, highly manual, and subject to error. On top of this, the client didn't have the analytics capabilities or the staffing capacity to perform the necessary reviews of data that would uncover missed or incorrect reinsurance claims.

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Solution

Analytics modeling to identify and recover reinsurance claims

ReFinder, Genpact's asset recovery solution for reinsurance claims, limits the impact on client resources and leverages a powerful combination of proprietary analytics modeling and industry expertise.

First, we worked in close collaboration with the client's UK, US, and Canada entities to agree the timeline and identify data requirements. Then we modeled the claims data versus the reinsurance structure and compared it with historical cessions. This wasn't a one-time modeling – the process was continuously fine-tuned over multiple iterations.

Then our experts reviewed each high-probability claim and scrutinized the coverage documents before submitting the documented and researched cases to the client for review and verification. Backed by the analysis and research documentation provided by Genpact, the client was able to discuss the results with its reinsurers and collect the additional amounts owed.

Impact

Millions of dollars returned to the client and future leaks plugged too

Over the course of the first 16 months, we identified and collected $20 million in previously missed recoverables. Not only did we recoup leaked dollars, but we also shared root cause analysis and detailed recommendations so the client could fix faulty systems and processes to prevent future leakage. A further 12-month review led to an additional recovery of $10 million. The client is now confident that its reinsurance claims processes are 99% accurate. Going forward, the insurer and Genpact will carry out periodical ReFinder recovery reviews.

With ReFinder's combination of proprietary digital models and expert human analysis, we can mine the value of legacy data so our clients can reclaim cash that goes straight to their bottom line.

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