Centralized anti-fraud databases and issues with compliance

Learn how ClaimShare solves the problem of double-dipping fraud

Summary

• KPMG estimates duplicate claims fraud is a multi-billion-dollar insurance problem
• Despite interest from the industry, centralized national databases are not the solution
• Such projects can encounter problematic compliance issues due to concerns around collusion
• ClaimShare is an unrivaled technological solution to the problem, safely navigating all issues relating to market regulation

Fraud is a major insurance industry problem. Data sharing is needed, but how can insurers safely collect and share data in the fight against potential criminals?

Despite interest from the insurance industry, centralized national databases are not a viable antidote to fraud. On the contrary, they are time-consuming and complicated initiatives that expose insurers to burdensome regulatory problems.

KPMG estimates fraud in the insurance sector is a multi-billion-dollar problem.

We know that it is possible to combat certain kinds of fraud through data sharing. For example, duplicate claims fraud, in which dishonest policyholders submit the same claim to multiple insurers, is preventable through appropriate communication between insurers on claims payouts.

But open cooperation within the insurance sector comes with many challenges. Collaboration projects often encounter friction due to privacy and data security concerns, and business confidentiality considerations.

Despite these issues, one European national association of insurance companies attempted to create an anti-fraud project in 2019. This was to involve national databases and the development of common algorithms that would be used to determine fraud risk indicators.

This would hopefully offer direct cost savings to the insurance industry, extending to cost savings for policyholders. And, of course, there would be societal benefits from reductions in crime.

And yet, though recognizing the importance of reducing fraud, the national market competition authority raised concerns.

Hitting Roadblocks

The competition authority was worried that the development of common algorithms could unfairly influence the strategies of collaborating companies in essential phases of the insurance business. Crucially, it expressed concern that the sharing of large amounts of data could facilitate collusion.

There was concern that insufficient third-party guarantees existed to prevent anti-fraud activity from being carried out for the sole benefit of stakeholders, with the consequent risk of anti-competitive foreclosure.

As a result of the market competition authority’s comments, contributors to the anti-fraud project were forced to make substantive changes.

These amendments included:

• Placing official limits on the possible uses of the databases
• Providing safeguards aimed at guaranteeing their correct use
• And ensuring the widest possible subscription to the anti-fraud project itself

Although the project was given the green light, the association of insurers needed to contend with this unwanted regulatory scrutiny, altering their project and losing time and opportunity dealing with the arbitration process.

What can insurers learn from this episode?

The risk of collusion, as the example above demonstrates, is real: merely the possibility of collusion could be damaging to an anti-fraud project or participating organizations.

To be palatable to market authorities, database-based solutions must have limits placed on them, and they must provide evidence of effective safeguards — creating significant burdens of compliance for participating organizations.

Data sharing in the insurance sector requires specialized technologies. Organizations need to be scrupulous in their approach to handling data. Taking existing tools, such as databases, and adapting them for a business case in today’s data-sensitive world is a recipe for injury.

These types of projects can suffer from long-lasting delays, or complete roadblocks, damaging returns on investment and leading to unforeseen opportunity costs. They can even be permanently blunted in their effectiveness due to mandated changes to the scope or application of the project.

What is the alternative?

ClaimShare is an unrivaled technological solution for data sharing in the insurance industry.

Created by IntellectEU, experts in distributed finance and emerging technologies, ClaimShare makes it possible to compare claims data between insurers without exposing or storing personal identifiable information (PII) in a centralized location.

• ClaimShare does not store the personal data of the claimant or the insurer, so it is not possible to collude based on this data, nor to reverse-engineer pricing models of competitors. This removes many of the issues with compliance.
• ClaimShare is secured with R3 Corda Distributed Ledger Technology, making it safer than a centralized database from a data security perspective.
• ClaimShare uses confidential computing, preventing exposure of PII-data during the matching process.
• ClaimShare needs only a fraction (5–10%) of the PII-data to match claims (using fuzzy-matching), making it vastly more scalable than alternatives.

ClaimShare is the only practical solution to data sharing in the insurance industry. For more information about the technology, please find a short introduction to ClaimShare here.