Insurance claims are stressful enough without the friction of a manual, fragmented process. Delays, redundant paperwork, missing documents, and slow responses can frustrate policyholders and overload internal teams. For a multinational insurer operating across the Americas, one that manages its own claims as well as processes claims for other insurance providers through strategic partnerships, these pain points were all too familiar.

In just seven months, that reality began to shift. We partnered with the insurer and redesigned its end-to-end claims experience, streamlining claim creation, enabling smart, self-guided inspections, embedding automation, and laying the groundwork for straight-through processing. The result? A projected 25% reduction in cost to process a claim, a system capable of sub-60-second resolutions, and a projected 6% revenue uplift tied to improved user experience.

This article explores how that transformation unfolded, and how others in the industry can follow suit to build an AI-enabled, automated insurance claims process.

At the outset, claims intake relied heavily on manual entry. Claimants initiated claims by phone, and agents input data into a fragmented system that differed across insurance partners. Inspections were either conducted in person by third-party inspectors or submitted via a self-guided mobile app that was unreliable and underused.

Across the claim lifecycle, multiple operational challenges emerged: 

• Claim creation processes were inconsistent, relying on spreadsheets, emails, and disconnected portals. 
• Agents re-entered information and validated submissions manually. 
• Document submissions were often incomplete, triggering delays and follow-ups. 
• Adjusters and appraisers lacked real-time visibility and audit trails. 
• Systems didn’t share consistent claim identifiers, impeding traceability and reporting.

To complicate matters, each insurance partner had its own set of business rules, introducing complexity, redundant validations, and inconsistent decisions. Without a centralized logic layer, the process was reactive, opaque, and slow.

The solution involved coordinated enhancements across the entire claims journey, anchored by three core components that together delivered greater speed, accuracy, and control: 

1. Seamless, Omnichannel Claim Intake:  A new integrated UI enabled agents to efficiently create claims with system-backed validation and auto-populated policy data. Additionally, a new WhatsApp bot offered digital-first claimants a modern alternative. Unlike traditional rule-based chatbots, this bot is powered by a large language model (LLM), offering flexible, ChatGPT-style interactions that adapt naturally to user input. These tools guide users through claim initiation with built-in validations, streamlining intake workflows, minimizing data inconsistencies, and enabling faster, more complete submissions. 
2. Automated, Rules-Driven Claim Processing: At the heart of the solution is a centralized claim processing engine, a logic layer that codifies decision trees, executes business rules, and governs claim flow from intake through resolution. It automates tedious tasks such as depreciation calculations, letter generation, and information validation. Audit flags and workflow rules enable fast-tracking of simple claims, consistent decision-making, and improved operational control. Letters and status updates are generated automatically, improving both claimant communication and internal efficiency. 
3. AI-Augmented Inspections and Decision Support: Both the self-guided and in-person inspection apps were enhanced with AI and OCR capabilities to validate image and document submissions in real time, classify document types, and extract relevant data. This not only improved submission quality but also reduced rework and manual entry. A built-in feedback loop enables model performance improvements over time. Looking forward, the integration of AI-generated estimates, from piloted vendors that offer damage detection and automated cost estimation, will enable full straight-through processing from inspection to claim resolution.

When all three of these components work seamlessly together, they set the foundation for fully automated claims. Today, claimants can receive an offer letter without manual adjustor intervention after submitting cost estimates. Once AI-generated estimates are integrated, claims can move directly from inspection to resolution in under 60 seconds, provided they meet a predefined set of eligibility rules set by the claim processing engine. Claims that fall outside of these criteria will continue to follow human review pathways to ensure appropriate oversight.

We supported this transformation by piloting three third-party AI estimate solutions using real claim data, enabling the client to evaluate accuracy and operational fit before committing to integration. 

The insurer has built the foundation for transformation. Our conservative estimates project significant value once the client completes several key internal enablement steps, including rollout, training, and ongoing change management.

The two primary areas of projected value are: 

• Cost Efficiency in Claims Operations 
• User Experience Improvements (Claimant and Agent UX)

Cost Efficiency: The insurer is expected to reduce cost per claim by 25%, driven by: 

• A rise in self-guided inspections, enabled by improved app performance and smarter claim routing. 
• Automation of tedious tasks like depreciation calculations and letter generation. 
• Smarter routing and audit flagging logic that reduces manual review and rework.

User Experience: Significant improvements are expected across both digital and agent-driven interactions: 

• For policyholders: a conversational, responsive WhatsApp bot enables faster and more intuitive claim creation. 
• For agents: the new UI helps surface policy data and ensures claims are created correctly the first time. 
• For inspections: both inspectors and claimants benefit from real-time validations, resulting in fewer delays and cleaner data submissions. 

An important metric to measure customer loyalty and satisfaction is the net promoter score (NPS). This is tracked via surveys asking how likely customers are to recommend a company to others. According to a study published by McKinsey, each point increase in NPS can translate to 300 basis points in annual revenue growth. The user experience improvements of our solution are projected to drive a 2-point increase in NPS, which would yield a ~6% increase in annual revenue in the first year alone, with compounding impact over time.

This wasn’t just a technology project, it was a coordinated transformation across functions. Key contributors included: 

• Product and design teams who crafted intuitive workflows 
• Engineering and IT teams who delivered performance, stability, and integration 
• Operations, claims, and audit leaders who codified real-world rules and exceptions 
• Business Intelligence analysts who developed dashboards to monitor usage and performance 
• Executives who created alignment, championed the vision, and enabled change 

Empowering all of these stakeholders to actively participate was critical to success. By creating structured touchpoints and involving each team from the outset, the transformation effort aligned priorities, surfaced risks early, and ensured that the final product reflected the realities of both users and operators. This kind of cross-functional inclusion not only builds better systems, but also fosters adoption, accountability, and lasting cultural change.

1. Start with Rules, Not Models: AI only works well when the decision logic is clear. Start by codifying eligibility, review triggers, and validation rules. 
2. Design for End Users: Better tools for claimants and internal teams yield the highest returns. Focus on usability and clarity at every step. 
3. Treat Workflows as a Living System: Like a digital product, your claims workflow should evolve continuously. Reuse building blocks (e.g., flags, audit trails, letter templates), monitor KPIs, and refine processes over time. 
4. Make It a Cross-Functional Mission: Technology alone isn’t enough. Engage product, engineering, claims, operations, and leadership early and often. 
5. Prioritize the Right Business Metrics: Don’t default to technical outputs. Instead, define and track a few key metrics that reflect real business value; cost per claim and NPS are good starting points. 

This insurer didn’t just digitize its claims screens, it redesigned the underlying logic, touchpoints, and tools that power its operations. With the claim processing engine in place and flexible automation embedded across the journey, the foundation for fast-tracked, straight-through claims resolution is already laid.

What comes next? The insurer must scale adoption across internal teams, train frontline users, finalize a vendor for AI-generated estimates, and integrate that solution to support full straight-through processing. In parallel, the system should be continuously refined based on real-world user data and operational feedback.

For insurers seeking to modernize, the opportunity is clear. Build your own proprietary claim processing engine; pair it with modular, purpose-built user interfaces and automation services; and integrate both programmatic rules and AI models where appropriate. When orchestrated thoughtfully, intelligence can guide every step of the journey, from claim creation to inspection, estimate generation, and payout.