This is our story of harnessing advanced analytics through Subrogation-as-a-Service for a leading global insurer. Our approach helped identify and pursue missed recovery opportunities, maximizing revenue and optimizing operational costs.
As we know…
In the fiercely competitive insurance industry, recovery is crucial for maximizing revenue streams. However, it often faces hurdles due to complexities and inefficiencies, resulting in revenue leakage. Insurers lose billions of dollars grappling with challenges such as missed recovery opportunities, cumbersome workflows, fragmented business processes and low referral rates. These obstacles not only impact the company’s bottom line but also strain operational resources and result in higher premiums for policyholders.
To combat these challenges, insurers are increasingly adopting advanced Artificial Intelligence (AI) and Machine Learning (ML) models. When combined with humans-in-the-loop, these models have the potential to revolutionize the subrogation landscape, significantly enhancing cash flow, operational efficiency and overall profitability.
The challenge for our client was…
Missed recovery opportunities in its motor and property (personal and commercial) business lines. About 15 percent of the claims were concluded without pursuing recovery opportunities, resulting in substantial revenue loss. Compounding this issue, the existing manual processes proved inefficient, yielding low referral and conversion rates.
WNS proposed a comprehensive solution aimed at…
Optimizing indemnity spend, minimizing leakage and identifying missed recovery opportunities as a part of our Subrogation-as-a-Service offering. Additionally, WNS committed to a performance-based commercial model, aligning incentives with outcomes.
Our solution was built on four pillars:
WNS’ recoveries as a service model delivered…
Tangible financial benefits and operational efficiencies, effectively addressing our client’s challenges by combining advanced analytics, streamlined workflows, expert intervention and outcome-based pricing.
Key outcomes included:
~- percent uplift
in recovery conversion
~ percent reduction in recovery lifecycle
through early detection of recoverable claims
USD Million
in active recovery pursuit
+ percent accuracy
in detecting recoverable claims