Why AI in insurance claims and underwriting will be a game changer in 2026
- BluePond AI
- 2 days ago
- 5 min read
Claims and underwriting sit at opposite ends of the insurance lifecycle, yet they are shaped by the same realities. Rising submission volumes. Increasing policy complexity. Tighter regulatory scrutiny. Higher expectations for speed, accuracy, and transparency.
Across both functions, teams are expected to make confident decisions while working with information spread across dozens of documents, systems, and formats. Claims handlers reconcile FNOLs, policies, endorsements, assessments, and invoices. Underwriters review loss runs, schedules, broker terms, guidelines, and risk disclosures. The pressure to move faster has never been higher, but the margin for error has never been smaller.
These challenges are not new. What is new is the scale at which they now exist.
AI has the ability to tackle these challenges directly. Not by simplifying insurance work, but by bringing structure, context, and consistency to some of the most complex decisions insurers make. This is why AI in insurance claims and underwriting will become a defining capability by 2026.
In this blog, we take a closer look at:
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Understanding the claims and underwriting process
Claims processing begins with the FNOL, but then the actual labor begins. Claims teams must assemble data from policies, endorsements, assessment reports, invoices, and supporting documents that arrive at different times and in various forms. Details are frequently absent or imprecise, requiring claims specialists to spend a significant amount of time reconciling facts before making a conclusion. While claims processing software can help organize data and track work, the duty for assessing coverage and validating facts remains primarily with humans.
Underwriting faces the same difficulty earlier in the insurance lifecycle. Submissions rarely arrive in a full, well-organized package. Loss runs, schedules, broker terms, standards, and risk disclosures are distributed among several documents, each of which must be carefully reviewed. Underwriters must evaluate exposure, and follow appetite guidelines while balancing speed and accuracy. Much of this work is still done manually, which reduces reaction times and causes discrepancies in how equivalent threats are assessed.
As the amount of submissions and claims grows, it becomes increasingly challenging to rely solely on task-based automation and manual review.
Why traditional approaches are breaking down
At higher volumes, manual review and task-based automation no longer scale effectively. Adjusters and underwriters spend countless hours gathering paperwork rather than exercising judgment. Important signals are buried in paperwork. Inconsistencies appear too late, usually after payment or commitment.
While automated claims systems have improved routing and data collecting, they are worthless without context. Insurers today want intelligence that reads, reasons, and connects information throughout a case.
By 2026, AI in insurance underwriting and claims will have transformed into a game changer.
How AI helps claims and underwriting work better
AI adds intelligence to workflows by linking information across documents, using consistent logic, and revealing insights early. Instead of evaluating data individually, AI systems assess entire instances holistically.
In claims, AI may analyze FNOLs, policies, endorsements, assessments, and invoices to discover coverage eligibility, missing information, and any anomalies. In underwriting, AI may combine loss history, exposure data, guidelines, and external context to help with more confident risk assessments.
This change allows insurers to save manual work while increasing consistency, auditability, and decision confidence. Automated assertions grow more credible. Underwriting decisions become more defendable. Teams concentrate on judgment-based tasks rather than data preparation.
Claims CoPilot: Bringing intelligence into automated claims
Claims CoPilot supports claims teams from intake to payout by applying automation grounded in insurance logic. Built on BluePond.AI’s P&C CoPilot platform, it creates a connected and auditable claims flow that supports faster and more consistent decisions.
Intelligent document intake
Claims CoPilot starts by reviewing FNOL forms, policies, endorsements, medical or police reports, assessment records, and invoices. It works with both structured and unstructured files without templates, enabling it to adapt to various claim types, formats, and data sources.
Consistent data evaluation
Once documents are ingested, Claims CoPilot performs a systematic evaluation across more than 40 data variables. Each data point is assessed using standardized logic, reducing subjective interpretation and ensuring consistency across claims teams and regions.
Coverage and loss cause analysis
Claims CoPilot creates loss cause hierarchies and compares coverage eligibility with policy terms, deductibles, exclusions, and endorsements. This review is supported by a claims library comprised of over 10,000 historical cases, with rules that adapt when new patterns develop.
Context-driven claims triage
Claims are prioritized based on urgency, complexity, and internal guidelines, with clear rationale provided for each routing decision. Straightforward claims move forward efficiently, while complex or unclear cases are directed to the appropriate desks early in the process.
Proactive anomaly detection
Before payment, Claims CoPilot detects anomalies between assessments, invoices, and regulatory requirements. This early detection allows insurers to correct errors before they become apparent during post-payment audits.
Overall impact
For insurers, the impact is practical and immediate:
Faster initial claim assessments
Reduced manual review and data preparation
Early identification of missing details and exclusions
Pre-payment leakage prevention
Stronger compliance and defensibility
Claims handlers focus on complex cases while routine claims move faster and with greater confidence.
Underwriting CoPilot: Smarter decisions from submission to quote
Underwriting CoPilot streamlines one of the most demanding parts of underwriting by bringing structure to scattered information. It automates the submission-to-quote journey while allowing underwriters to remain fully in control of decision-making.
Unified document ingestion
Underwriting CoPilot reads structured and unstructured documents including loss runs, schedules, broker submissions, manuscripts, and policy files. Information from all sources is evaluated together, providing a complete view of the submission from the outset.
Triage against underwriting guidelines
Underwriting CoPilot can ingest complex underwriting guidelines and appy them to unstructured documents and broker asks to analyze fit, and highlight to the underwriter which applications clearly do not fit the appetite, vs those that are high priority and those that require manual review
External risk enrichment
Submissions include external context such as financial stability indicators, operational signals, hazard exposure, and risk data. This added insight allows underwriters to spot potential issues earlier in the assessment process.
Submission scoring and prioritization
Each proposal is given a risk, appetite, and broker performance score. These scores assist underwriters in prioritizing prospects that correspond with portfolio objectives and directing attention to the most important areas.
Correlated case insights
Insights from all internal and external sources are brought together in a focused case summary. Key drivers, concerns, and supporting evidence are clearly presented, making it easier to review, validate, and act with confidence.
Overall impact
Insurers see measurable results:
Same-day submission-to-quote cycles
Over 75% reduction in manual effort
Lower processing costs
Improved hit ratios
Stronger portfolio quality
Underwriters spend less time gathering information and more time applying judgment.
Why this matters in 2026 and beyond
By 2026, insurers will be judged not just on price, but also on speed, transparency, and decision quality. AI in insurance underwriting and claims will decide how effectively firms balance efficiency and control.
BluePond offers Claims and Underwriting CoPilot.AI adds structure and consistency to complex, high-stakes decisions. They enable insurers to operate more confidently as volumes increase and demands rise.
BluePond.AI, with its new Claims CoPilot and Underwriting CoPilot, is the next generation of claims processing software and underwriting intelligence, built to support real-world insurance operations with accuracy, auditability, and scale.
