PRD Template: Jira + Confluence for Insurance
Insurance product development operates under constraints unique in the software industry: state-by-state regulatory filing requirements, actuarial model dependencies, legacy mainframe integrations, and claims adjudication rules that have evolved over decades. A PRD that ignores these realities will produce a spec that engineering cannot build within regulatory boundaries.
This template adds insurance-specific sections to the Jira + Confluence workflow, ensuring your PRD addresses filing requirements, actuarial dependencies, and claims system integration from the start.
Template sections
5 sections covering the complete prd workflow.
Regulatory Filing and State Compliance
Insurance products must be filed with and approved by state regulators before launch. Each state has different filing requirements, approval timelines, and product restrictions. Your PRD must specify which states are in scope, which filing types are required (rate, rule, form), and the expected approval timeline. Use a Confluence table mapping each state to its Department of Insurance requirements, filing deadlines, and approval status.
New auto insurance discount program requires rate filings in 47 states. California (CDI) requires prior approval with 60-day review period. Texas (TDI) uses file-and-use with 30-day waiting period. New York (DFS) requires prior approval with 90-day review. Phased rollout: launch in file-and-use states first (30 states, Month 1-2), then prior-approval states as filings clear (17 states, Month 3-6).
Tips
- Create a Jira epic per state group (file-and-use vs. prior-approval) with filing milestone dates
- Maintain a Confluence page tracking filing status by state, updated weekly
- Include actuarial certification requirements in the filing timeline
- Build a rollback plan for states where filings are rejected or require modification
Actuarial Model Integration
Insurance features often depend on actuarial models for pricing, risk scoring, and reserve calculations. Your PRD must document which models are affected, what inputs and outputs change, and the actuarial review timeline. Model changes require actuarial sign-off and may trigger additional regulatory filings. Document the model version, validation requirements, and the handoff process between product and actuarial teams.
Usage-based insurance scoring model (GLM v3.2) needs two new input variables: daily mileage from telematics device and hard-braking events per 100 miles. Actuarial team estimates 6 weeks for model recalibration, 2 weeks for back-testing against 24 months of claims data, and 1 week for peer review. Model lift expected: 12% improvement in loss ratio prediction for the 18-25 age segment.
Tips
- Create a dependency link in Jira between your feature epic and the actuarial model update epic
- Include model validation acceptance criteria in every story that uses actuarial outputs
- Document model input/output schemas in Confluence with version numbers
- Plan for a model shadow period where old and new models run in parallel before cutover
Claims Workflow and Adjudication Rules
Claims processing is the core insurance workflow. Any feature that affects how claims are filed, evaluated, or paid must document the complete adjudication flow including automated rules, manual review triggers, fraud detection checkpoints, and payment routing. Insurance claims systems often run on legacy mainframes with batch processing, so real-time features require careful integration architecture.
Self-service claims filing for auto glass replacement. Automated adjudication for claims under $500 with photo verification: user submits 4 photos of damage, AI model classifies damage severity (95.2% accuracy on validation set), automated approval routes to preferred repair shop network. Claims over $500 or AI confidence below 80% route to manual adjuster queue with 24-hour SLA. Expected automation rate: 72% of glass claims.
Tips
- Map the complete claims state machine in Confluence including all exception paths
- Create Jira stories for each adjudication rule with specific test scenarios
- Include fraud detection checkpoints as separate stories with their own acceptance criteria
- Document the batch processing schedule and how it affects feature availability windows
Legacy System Integration
Most insurance companies run core systems (policy admin, billing, claims) on mainframes or legacy platforms like Guidewire, Duck Creek, or custom COBOL systems. Your PRD must specify which legacy systems are affected, what integration pattern to use (API wrapper, event bridge, batch file, or direct database), and the constraints each system imposes on your feature design.
Integration with AS/400 policy administration system via MQ Series message queue. Policy changes published as fixed-width flat files in nightly batch. Real-time quote requires a new CICS transaction (estimated 8 weeks for mainframe team to develop). Workaround: cache last-known policy data in microservice layer, refresh on policy change events with 24-hour staleness tolerance.
Tips
- Include legacy system team capacity and sprint cadence in your timeline estimates
- Document data format constraints (fixed-width, EBCDIC, packed decimal) in technical requirements
- Create integration test stories that validate data round-trips through legacy systems
- Plan for legacy system maintenance windows that may block deployments
Underwriting Rules and Risk Appetite
Features that affect underwriting must document how they interact with the company risk appetite framework. Specify which underwriting rules are affected, whether manual underwriter review is required, and how the feature changes the risk profile of the book of business. Include the underwriting authority matrix showing who can approve what risk levels.
Instant-issue life insurance for healthy applicants under 45 with coverage up to $500K. Automated underwriting using prescription history (Rx data), MIB check, and credit-based insurance score. Decline rate target: 15-20%. Instant-issue criteria: no prescription history flags, MIB clear, insurance score above 700. All others routed to traditional underwriting with 2-week SLA.
Tips
- Document the underwriting authority matrix in Confluence (who approves what coverage amounts)
- Create Jira stories for each underwriting rule with edge case test scenarios
- Include adverse action notice requirements for declined applications
- Track model performance metrics: decline rate, loss ratio by segment, and underwriting time
Copy-paste template
# [Feature] PRD — Insurance (Jira + Confluence) ## Regulatory Filing | State | Filing Type | Status | Expected Approval | |---|---|---|---| | [State] | [Rate/Rule/Form] | [Filed/Approved/Pending] | [Date] | ## Actuarial Dependencies - **Model:** [Name and version] - **Changes required:** [Description] - **Actuarial review timeline:** [Weeks] ## Claims Impact - **Adjudication rules affected:** [List] - **Automation rate target:** [%] - **Manual review triggers:** [Conditions] ## Legacy Systems | System | Integration | Constraint | |---|---|---| | [System] | [Pattern] | [Limitation] | ## Underwriting | Rule | Current | Proposed | Approval Required | |---|---|---|---| | [Rule] | [Value] | [Value] | [Authority Level] |
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