Insurance
Insurance Regulation and Software Testing Evidence

Rishabh Kumar
Published On

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None of these regimes prescribes a software testing method. Each expects something that software testing evidence can show: Solvency II and Solvency UK expect controlled change to critical systems, the Consumer Duty expects good customer outcomes to be delivered and monitored, IFRS 17 expects reliable data behind the numbers, and the NAIC AI bulletin expects AI systems to be validated and tested.
What Does Solvency II and Solvency UK Expect of Software Change?
Solvency II requires an effective system of governance, including clear allocation and segregation of responsibilities, internal control, risk management, outsourcing oversight and contingency planning. In the UK, the PRA’s restated rules took effect on 31 December 2024 (PRA PS15/24). Testing evidence shows that changes to critical systems are controlled.
Requirement | Evidence artefact | Who signs |
|---|---|---|
Segregation of responsibilities | Requirements and go-live approved by people independent of the build | Business owner, release approver |
Internal control over change | Per-release scope, results against an identified build, exceptions | Head of QA, risk owner |
Outsourcing oversight | Vendor and SaaS release regression results against the insurer’s requirements | Platform owner |
Continuity | Results of fall-back and recovery path tests for critical systems | Operational resilience lead |
What Does the Consumer Duty Expect of Software?
The Consumer Duty requires firms to deliver good outcomes across products and services, price and value, consumer understanding and consumer support, and to monitor and evidence those outcomes, with an annual board assessment. It has applied to open products since 31 July 2023 and to closed products since 31 July 2024 (FCA PRIN 2A). Software delivers most of those outcomes. See Consumer Duty and Software Testing.
Requirement | Evidence artefact | Who signs |
|---|---|---|
Products and services work as designed for the target market | Tested eligibility, cover and lifecycle journeys per product | Product owner |
Price and value | Tested pricing rules, including renewal pricing for UK home and motor | Pricing lead |
Consumer understanding | Tested disclosures and documents for each event | Communications owner |
Consumer support | Tested cancellation, complaints, claims and vulnerability journeys, including negative paths | Customer operations lead |
Closed products | Reconstructed rules tested against the platform | Product governance lead |
What Does IFRS 17 Expect of Operational Data?
IFRS 17 measures groups of insurance contracts using data that originates in policy, claims, billing and reinsurance systems, and has applied to annual periods beginning on or after 1 January 2023. Actuarial and finance teams own measurement; testing evidence shows that the data reaching the engine is complete, accurate and correctly attributed after every operational change.
Requirement | Evidence artefact | Who signs |
|---|---|---|
Complete, accurate contract attributes | Attribute checks from operational events to engine inputs | Finance systems owner |
Correct grouping inputs | Tests either side of cohort and portfolio boundaries | Actuarial lead |
Reconciliation | Source to engine to ledger reconciliations by period | Financial controller |
What Does the NAIC AI Model Bulletin Expect?
The NAIC Model Bulletin on the Use of AI Systems by Insurers, adopted on 4 December 2023, expects a written AI Systems Program covering governance, risk management and internal controls, internal audit and third-party AI, including validation, testing and retesting. Around half the states and the District of Columbia have adopted it or similar guidance (NAIC adoption map).
Requirement | Evidence artefact | Who signs |
|---|---|---|
Validation and testing of AI systems | Tests of journeys that include AI-assisted steps, asserting outcomes within approved rules | Model owner, business owner |
Retesting on change | Regression triggered by model, vendor or configuration changes | Head of QA |
Third-party AI oversight | Test results for vendor-supplied AI features in the insurer’s processes | Vendor manager |
Documentation for regulators | Traceable chain from requirement to test to result to approval | Compliance |
EU insurers within Solvency II scope also fall under DORA’s digital operational resilience testing requirements.
What Makes Testing Evidence Usable Across All Four Regimes?
The same five qualities serve every regime: completeness, traceability from source to result, independence of approval, reproducibility and timeliness. Evidence produced as testing happens, rather than assembled for an audit, meets all five. See Release Evidence for Insurers.
How Does Virtuoso QA Touchstone Produce This Evidence?
Touchstone, Virtuoso QA’s agentic QA platform, builds the evidence as the work happens. Requirements are drafted from the firm’s own documents and cite their source; a named person approves each one; tests run on a deterministic engine against identified builds; and changes are traced to the requirements they affect.
The chain from source document to result is available for every release.
Traceability: each requirement cites the rule, policy or specification it came from.
Independence: AI proposes and a named person approves; approval cannot be switched off.
Reproducibility: the same test against the same build gives the same result.
Timeliness: evidence exists before the go-live decision.
Touchstone does not make an insurer compliant with any regime. It provides tested, evidenced control over the software that implements the firm’s obligations.
Frequently asked questions
Do insurance regulators require software testing?
What testing evidence does the Consumer Duty need?
How does Solvency II relate to software testing?
Is IFRS 17 testing a QA responsibility?
Does the NAIC AI bulletin apply to testing tools that use AI?
Written by

Rishabh Kumar
AI Testing & Quality Engineering Contributor
Rishabh leads business development and marketing at Virtuoso QA. He writes about AI-powered test automation, end-to-end testing, self-healing tests, and quality engineering, exploring how these capabilities can improve test coverage, reduce test maintenance, and support reliable software releases.










