Insurance · Illustrative engagement
A Solvency II data quality framework the board reads
A data quality framework and board scorecard aligned to Solvency II data requirements, with root-cause fixes that removed most recurring defects in reserving data.
- Client
- A multi-line general insurer
- Region
- United Kingdom
- Disciplines
- Data Quality, Stakeholder Engagement
The situation
The actuarial function relied on manual adjustments to policy and claims data each quarter, and internal audit had rated data quality controls for the internal model as needing improvement.
Quality was discussed anecdotally; there was no shared definition of what 'appropriate, complete and accurate' meant in practice.
Our approach
- Defined a data quality standard using the six dimensions, with thresholds agreed by actuarial, finance and underwriting owners.
- Profiled 180 critical data elements and wrote 410 business rules, implemented as automated checks in the data platform.
- Ran structured root-cause analysis on the 20 most frequent defects, fixing them at source in policy administration workflows.
- Onboarded 34 data stewards with a role-based programme and introduced a one-page board scorecard.
Results
reduction in recurring defects on reserving data
saved per year in manual actuarial data adjustments
rating at the subsequent internal audit review
More case studies
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- From shelfware to a catalogue analysts rely on
- Rationalising data policy across a public body
Case studies describe representative engagements. Client names, figures and identifying details are anonymised.
Start with a conversation, not a proposal
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