"The collaboration was very well managed from start to finish."
James Foskin
Founder & CEO, TiAiMe Limited
RPA in Insurance Services
RPA in Insurance
Insurance operations run on structured, rule-based work. Claims intake, policy administration, underwriting data collection, compliance reporting, broker communication. The volume is high, the data is structured, and most of it follows the same logic every time.
RPA in insurance moves that work off your team. We build robotic process automation for insurers, MGAs, and brokers across claims processing, policy administration, underwriting support, and regulatory reporting, so your operations team handles the judgment calls, not the data entry.
Claims intake and processing automation from first notice of loss to settlement
Policy administration automation for renewals, endorsements, and cancellations
Underwriting data collection and submission to carrier portals
Compliance and regulatory reporting assembled automatically from your systems
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
Trusted by
The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
01
Claims team spending hours on data entry for each new claim instead of assessing it?
02
Policy renewal processing backlog causing lapses your operations team is firefighting?
Plain answer
RPA in insurance automates high-volume, rule-based operations: claims intake, policy administration, underwriting data collection, and regulatory reporting. Bots extract data, update records across systems, and produce complete audit trails, so adjusters and underwriters handle judgment calls instead of data entry. RaftLabs scopes each process and agrees a fixed cost before development starts.
What to remember
- Insurance RPA automates the high-volume, rule-based work: claims intake, policy administration, underwriting data collection, and regulatory reporting, so adjusters and underwriters spend their time on judgment calls.
- We integrate with Guidewire, Duck Creek, Applied Epic, and Majesco via API, and with legacy systems through UI automation where no API exists.
- Regulatory reporting automation covers Solvency II, Lloyd's bordereaux, FCA returns, and US state filings, with validation reports that flag exceptions before compliance review.
- Every automation produces a complete audit trail that supports regulatory examination, and straight-through processing clears simple claims without adjuster time.
- We scope each process and agree a fixed cost in writing before development starts. A first automation can launch as a validated v1, then expand across processes.
Proof
- shipping production software for regulated industries
- Since 2015
- RaftLabs delivery record
- scope and cost agreed in writing before development starts
- Fixed price
- Every RaftLabs engagement
The first decision is not what to build.
It is whether RPA is the right answer at all. We use four possible recommendations before discussing a development scope.
- 01
Buy
Choose a maintained product when it handles the core workflow and the remaining gaps can be solved with configuration, a connector, or a small process change. Paying for RPA bots you do not have to maintain is often the better trade.
- 02
Repair
Keep the existing product when users still get value from it and the code can be understood safely. Start with evidence: where the code lives, how the data is organized, what is tested, which outside services it depends on, who can access what, and how updates go live.
- 03
Build
Own RPA bots when the workflow shapes margin, customer experience, speed, or a product customers pay for. Start with one complete path and the system connections that path cannot work without.
- 04
Wait
Do not turn a changing policy into permanent software. Stabilise the rules, name the workflow owner, and measure the cost of the current process before paying for a product.
Not sure which path is yours? Bring it to a 30-minute call. Leave with the answer in writing.
Claims speed is a competitive advantage. Manual processing wastes it.
Policyholders judge their insurer at claims time more than at any other point. A claims process slowed by manual data entry, cross-system reconciliation, and paper-based workflows creates the exact experience that drives churn at renewal.
RPA in insurance automates the structured data work in claims processing: intake, record creation, document requests, and status updates, so adjusters spend their time on assessment and settlement, not administration.
McKinsey has projected that a quarter of insurance-industry work, processing claims, underwriting tasks, and other filing activities, would move onto automation workflows. For carriers and MGAs running high volumes, that shift is now the operational baseline their competitors are already building toward.
Capabilities
Insurance processes we automate
Claims intake and processing
Automated first notice of loss (FNOL) processing that extracts claim data from email, web forms, and document uploads and creates claim records automatically, with low-confidence extractions routed to staff review. Status updates, document requests, and settlement letters for low-complexity claims run automatically, so adjusters move from data entry to assessment sooner.
Policy renewals and endorsements
Automated renewal processing that works through the policy admin backlog during peak seasons. The bot pulls policy data on the standard 90-60-30-day renewal cycle, checks for material risk changes, re-rates, and routes the renewal pack, while endorsements recalculate pro-rata premiums and cancellations trigger lapse and refund workflows.
Underwriting data collection
Automated collection of underwriting data from third-party sources, so underwriters review complete risk packs instead of gathering data across portals for every submission. Property, credit, catastrophe exposure, prior claims, and Motor Vehicle Record pulls assemble into a structured pack in your underwriting system, ready for a decision.
Regulatory and compliance reporting
Automated assembly of regulatory submissions from your policy, claims, and financial systems, replacing the multi-day compilation that occupies compliance and actuarial staff before every deadline. Every submission includes a validation report confirming fields, totals, and year-over-year movements, so compliance review focuses on exceptions, not arithmetic.
Broker and agent communication
Automated broker communication workflows that keep distribution partners informed at every policy and claims milestone. Quote packs, policy documents, renewal reminders with one-click acceptance, commission statements, and submission acknowledgements all deliver automatically, reducing follow-up calls.
Fraud detection data processing
Automated data gathering for fraud screening at first notice of loss, so investigators receive a structured indicator report alongside the claim record. Each flag links to the data point that triggered it, and high-score claims route to your SIU queue automatically, replacing the multiple systems an investigator previously checked per claim.
What it costs
Every project starts at $10000.
The first phase automates one structured claims workflow: intake, record creation, document requests, and status updates.
Starting investment
Starts at $10000
Workflow volume, systems involved, exception handling, and review needs set the scope. After a 30-minute call, you get a written build, buy, repair, or wait recommendation plus first-phase direction. Free, whether or not you build with us.
Proof
Related delivery: document extraction at volume
- 01
AI OCR for gas station operations
- 02
InvestIQ gets 5,000+ active users in 90 days by replacing five-tab research sessions with one feed
InvestIQ tracks every open and upcoming IPO, buyback, and OFS across Indian markets so retail investors never miss a deadline or a gray market move.- active IPO tracker users in first 90 days
- 5,000+
- fewer browser tabs per research session
- 90%
- subscription data refresh during active windows
- 30 min
- 03
ULT Movies reaches 4,000 remote theaters with custom OTT app
Leading Indian movie distributor, ULT Movies, solved the challenge of delivering new releases to remote theatres with an Android app for STBs. Now, the distributor delivers smooth movie access even in areas with limited internet connectivity.- reduced network and infrastructure costs
- 60%
- screens reached via Android STBs
- 4000+
- increase in average watch time
- 45%
Own RPA bots when the workflow shapes margin, customer experience, speed, or a product customers pay for.
RPA for high-volume, rule-based insurance operations, so adjusters and underwriters handle judgment calls.
A fit
Claims intake, with first notice of loss data extracted and claims records created across systems.
Policy administration and underwriting data collection, with complete audit trails.
Regulatory reporting, including Solvency II, IFRS 17, Lloyd's of London reporting, FCA returns, and US state-level requirements.
Not a fit
A maintained product already handles the core workflow and the remaining gaps can be solved with configuration, a connector, or a small process change.
Keep the existing product when users still get value from it and the code can be understood safely.
The work is judgment calls, not structured data work: coverage assessment, liability determination, settlement negotiation, and fraud investigation stay with adjusters.
RPA or API?
| RPA | API | |
|---|---|---|
| Build cost | Cheaper and faster to build | Slower to build |
| Run cost | Costlier to maintain, because bots are screen-brittle | Cheaper to run and more reliable at scale |
| Use it when | The only interaction is the front-end screen | A backend integration is needed |
| Switching | When a reliable API appears later, compare bot-maintenance cost against switching | The backend integration, once built |
Process
How we work
- Phase 101
Discovery and scope
We map the workflow, the systems it touches, and the outcome it has to produce, then agree the scope of the first phase before any build starts.
- Phase 202
Design and architecture
We design the workflow, the data, and the integrations, and agree what done looks like, so the build starts with no open questions.
- Phase 303
Build and integrate
We build the first phase in working increments, connected to your systems, and test it against real cases before it goes live.
- Phase 404
Launch and handover
We launch the first phase, train the team that runs it, and hand over the documentation and ownership, then expand to the next process.
Proof
What clients say about working with RaftLabs
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
RaftLabs has been an exceptional partner. From the start, they became more than just a service provider, they embraced our vision with their expertise and dedication. We're proud of the result.
Jennyfer Ngueno
CoFounder & CEO, Sekou
Work with us
Tell us which insurance process consumes the most operations time.
Process, current systems, and volume. We'll design the automation and give you a fixed cost.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
Common questions
The best insurance automation candidates are high volume, rule-based, and involve structured data from identifiable sources. Top processes: claims intake (extracting first notice of loss data and creating claims records across systems), claims status updates (checking carrier or third-party systems and updating your claims management platform), policy renewals (preparing renewal packs, updating records, and triggering communication workflows), endorsement processing (updating policy records based on mid-term change requests), underwriting data collection (pulling risk data from third-party sources for underwriting review), and regulatory reporting (Solvency II, Lloyd's reporting, FCA submissions).
We integrate with insurance platforms via API where available or UI automation where not. Common integrations: Guidewire (PolicyCenter, ClaimCenter, BillingCenter), Duck Creek, Applied Epic, Majesco, and custom-built policy administration systems. For legacy systems with limited APIs, UI automation handles the integration. We also integrate with external data sources, credit bureaus, property databases, weather data feeds, and public records, that underwriting and claims teams currently access manually.
Yes. Insurers face significant regulatory reporting obligations, Solvency II, IFRS 17, Lloyd's of London reporting, FCA returns, and state-level requirements in the US. RPA can automate the data extraction and compilation for these reports, apply the required transformations and calculations, validate outputs against regulatory templates, and deliver submission-ready reports to the compliance team for final review and sign-off. The bot handles the data work; the compliance team handles the review and submission. Audit trails from the automation process support regulatory examination.
RPA automates the structured data work in claims, intake, record creation, status updates, document requests, and settlement letter generation, while claims adjusters focus on the judgment-intensive work, coverage assessment, liability determination, settlement negotiation, and fraud investigation. Straight-through processing for simple, clear-cut claims lets adjusters concentrate their capacity on complex and high-value claims.
The wrong-process frame: targeting the wrong business process is the named reason RPA projects fail. Good candidates are high-volume plus repeatable, rules-driven, calculation-intensive, compliance-check-heavy, error-prone, and cycle-time-critical. Insurance targets: underwriting, claims, agent and customer onboarding, info updates, queries and complaints, document and report generation. The pilot rule: prove RPA value through a pilot focused on one localized process before expanding company-wide.
The mechanism-fit rule: choose the mechanism that fits the task and its available connection. RPA is cheaper and faster to build, costlier to maintain (screen-brittle); API is the reverse: slower to build, cheaper to run, more reliable at scale. Use RPA where the only interaction is the front-end screen; API where a backend integration is needed. When a reliable API appears later, compare bot-maintenance cost against switching. A payer can redesign a portal or change a login flow, leaving a queue stalled until someone fixes the bot, so name the bot owner before launch.
A focused insurance automation covering a single process, such as claims intake and record creation from first notice of loss, is smaller and faster to deliver than a multi-process programme spanning claims, policy renewal, and compliance reporting. Cost depends on the number of processes, the complexity of your policy and claims system integrations, and the regulatory reporting requirements. We scope every project and agree a fixed price in writing before development starts.