Developing a Single Data Asset for Broker Business at Aviva

A dedicated project team was formed to conduct an in-depth review of closed claims, with support from the Data Insight team. A statistically valid sample of 1,200 claims was analysed to determine the extent of missed recoveries. The findings were remarkable: High-propensity claims for recovery were identified, including: Escape of water Fire Third-party property damage The audit findings supported a business case estimating an annual recovery opportunity of £4m, requiring an initial investment of £250,000. With leadership approval secured, the next step was to build the right processes and teams to capitalize on this opportunity.

Since there were no system flags to identify recoverable claims at notification, a data-driven approach was developed. A data mining program was built with support from data specialists, using machine learning to scan claim files for key indicators of subrogation potential. A data dictionary was developed and refined monthly over a six-month period to improve accuracy and capture new claim patterns. This program was used to triage recovery opportunities within 24 hours of notification, significantly reducing manual workload. To create an immediate pipeline of cases for the recovery team, the data mining tool was run across historical claims, uncovering £1 million in recoverable losses.

To execute on recoveries, RSA needed skilled specialists who could manage legal negotiations and settlements. A partnership was formed with one of RSA’s preferred legal firms to recruit newly qualified law graduates eager to gain corporate legal experience. Graduates received specialised training from RSA’s panel law firm, equipping them with the skills to manage subrogation claims. The team scaled quickly from 6 to 20 members within a year, benefiting from the legal firm's talent pipeline. Retention was high as the role provided valuable legal experience and a pathway to potential training contracts.

To ensure long-term success, it was critical to secure buy-in from frontline claims handlers and field-based loss adjusters. Detailed communication plans were rolled out to explain how accurate claim data would directly improve recoveries, reinforcing the importance of quality information capture. Project team members attended operational team meetings to share updates, celebrate early wins, and address concerns about role devaluation. Live audits by team managers helped monitor missed opportunities and drive continuous improvement. Loss adjusters embraced the initiative, seeing it as an opportunity to showcase their value by securing evidence that would strengthen recovery claims.