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🧪 '''Regression testing''' is a software quality assurance practice in which previously validated functionality is re-tested after any code change, configuration update, or system patch to confirm that existing capabilities — such as [[Definition:Premium | premium]] calculations, [[Definition:Policy administration system | policy]] issuance workflows, [[Definition:Claims management | claims]] adjudication logic, and [[Definition:Regulatory compliance | regulatory]] report generation — continue to work correctly. In insurance technology environments, where a single [[Definition:Rating engine | rating engine]] miscalculation can ripple across thousands of [[Definition:Quote | quotes]] or where an undetected defect in [[Definition:Billing | billing]] logic can trigger regulatory penalties, regression testing serves as a critical safety net. The practice is especially vital in organizations running [[Definition:Legacy system | legacy]] or [[Definition:Monolithic architecture | monolithic]] systems, where changes in one module can produce unintended side effects in seemingly unrelated areas.

⚙️ A typical regression testing cycle in an insurance context begins when developers modify the system — perhaps updating [[Definition:Underwriting guidelines | underwriting rules]] to reflect new regulatory requirements, integrating a new [[Definition:Application programming interface (API) | API]] from a third-party data provider, or adjusting [[Definition:Tax | tax]] calculations for a specific jurisdiction. The regression test suite, which comprises hundreds or thousands of predefined test cases covering core business scenarios, is then executed against the updated system. Automated testing frameworks have become standard practice, allowing [[Definition:Insurance carrier | carriers]] and [[Definition:Insurtech | insurtech]] vendors to run comprehensive suites in hours rather than the weeks manual testing would require. Test cases typically validate end-to-end processes: generating a quote for a standard risk profile and verifying the output matches expected premium, processing a mid-term [[Definition:Endorsement | endorsement]] and confirming the pro-rata adjustment is correct, or submitting a [[Definition:First notice of loss (FNOL) | FNOL]] and verifying the claim is routed to the appropriate handler. Results are compared against baseline outputs, and any discrepancy triggers investigation.

💡 The consequences of skipping or under-investing in regression testing can be severe across all insurance markets. Pricing errors that escape into production can lead to [[Definition:Underpricing | underpriced]] policies that erode [[Definition:Loss ratio | loss ratios]], or overpriced offerings that drive away profitable business — both damaging to a carrier's [[Definition:Combined ratio | combined ratio]]. In regulated environments, incorrect calculation of statutory reserves or [[Definition:Solvency | solvency]] figures due to a software defect can invite supervisory scrutiny from bodies such as the NAIC in the United States, the PRA in the United Kingdom, or EIOPA across the European Union. As insurers adopt more frequent release cycles — driven by [[Definition:Agile methodology | agile]] development practices and competitive pressure to iterate quickly — regression testing has shifted from a periodic gate to a continuous practice embedded in automated deployment pipelines, ensuring that speed of delivery does not come at the cost of operational reliability.

'''Related concepts'''
{{Div col|colwidth=20em}}
* [[Definition:Quality assurance (QA)]]
* [[Definition:Policy administration system]]
* [[Definition:Legacy system]]
* [[Definition:Straight-through processing (STP)]]
* [[Definition:Agile methodology]]
* [[Definition:Digital transformation]]
{{Div col end}}

Definition:Regression testing - Revision history

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