Subrogation recovery
Identifying claims where a third party's liability means the carrier can recover part or all of its payout, and pursuing that recovery. A structurally underworked part of the claims process in US carriers — recovery rates vary widely across carriers of similar size.
The three rungs
Dedicated subrogation adjusters reading closed claim files and flagging candidates by hand; or external recovery vendors working on a percentage-of-recovery fee. Both approaches leave money on the table because the screening happens late.
Built around deep learning or LLMs from day one; tools founded mostly post-2015.
Like fraud detection, subrogation has no dominant modern SaaS layer. The category goes from the legacy manual-review workflow straight to AI-native screening. Shift Technology's 2025 agentic claims platform explicitly names subrogation as a supported action, applying graph analytics to identify recovery candidates at claim open rather than at close.
Ranked comparison
- 15/2075%
AI platform for insurers focused on claims fraud detection, claims automation, subrogation, and financial-crime detection. 100+ customers across 25 countries; 2 billion claims analysed.
- traction
- 5/5
- maturity
- 4/5
- coverage
- 4/5
- recognition
- 2/5
- 10/1567%
The US property/casualty industry's cross-carrier claims database — 1.8 billion+ claims contributed by 1,850+ carriers, TPAs, and self-insureds (including the top 100 US P&C insurers), used for duplicate-claim detection, fraud scoring, and subrogation lead identification. Subsidiary of Verisk Analytics (NASDAQ: VRSK).
- traction
- 3/5
- maturity
- n/a
- coverage
- 4/5
- recognition
- 3/5