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SPECIALTY

AI FOR SPECIALTY LINES INSURANCE CLAIMS

Specialty claims vary from straightforward cargo files to complex casualty claims spanning years.

Each requires the right policy wording, endorsements and evidence to be assessed in context, with routine claims processed efficiently and complex cases flagged for specialist review.

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Overview

Consistent coverage checks for claims of all sizes and complexity.

Specialty insurance claims range from routine, high-volume files to complex, high-value losses. Sprout.ai analyses policies, endorsements and evidence to recommend accurate, explainable coverage decisions, helping insurers process claims efficiently and identify cases requiring specialist review.

The challenge

Why specialty insurance claims need a tailored approach

Specialty is handled as though every claim is a casualty file. Most are not, and the ones that are get the least of the specialist time.

Two operating modes, one book

High-volume claims need fast, consistent processing, while complex files require detailed review of evidence and policy wording. Managing both can divert specialist resources from complex claims.

Volume claims become complex claims

Specialty claims range from routine cases to complex disputes requiring specialist review. Early classification can affect costs as claims evolve, with the most costly 1% of marine claims accounting for at least 30% of total claims value annually.

Every policy has bespoke wording

Manuscript clauses, endorsements, exclusions and coverage limits must be assessed against each claim, regardless of size. High volumes limit review time, while complex claims make consistent, thorough assessment challenging.

Evidence has to be read together, not in isolation

Survey reports, bills of lading, pleadings and expert reports each hold part of the answer. Accurate coverage decisions depend on assessing all evidence together and identifying conflicting information.

Claims evidence arrives in different formats

Specialty claims involve complex documents across multiple parties and jurisdictions. Insurers need AI that goes beyond data extraction to interpret policy terms and deliver consistent coverage decisions at scale.

Claims keep developing after the file is opened

New evidence and expert opinions can change coverage and reserves, but policies are rarely reassessed as claims evolve.

sprout.ai understands and interprets

Claim dimension What Sprout.ai contextualizes What it returns
Policy bundle The document payload as it arrives, policy wording, schedules, endorsements and correspondence, across the policy and its renewals What each document is, the coverages and limits stated, the endorsements in scope, and whether anything needed to reach a judgement is missing
Governing terms Manuscript clauses, endorsements, retroactive dates and layered coverage, against the date and circumstances claimed Which wording governs this claim, which endorsement overrides the base terms, and why
Coverage The governing wording, against the circumstances described and the loss claimed Whether the claim is covered or excluded, and the clause that says so
Limits and sub-limits Limits, sub-limits, deductibles and retentions across the layers in place The limits that apply, and any sub-limit that caps the outcome
Cause and circumstances Notification data, loss and damage descriptions, and the supporting account of what happened The cause claimed, what was affected, and where and when it occurred
Specialist evidence Survey and forensic reports, expert opinions, pleadings, financial loss calculations and third-party correspondence The facts that decide the claim, and how the evidence bears on the coverage question
Cross-document consistency Every document in the file, read against the others Where accounts agree, where they conflict, and which conflict changes the coverage position
Claim integrity The parties named on the claim against sanctions and watch lists, and the full file against claim history Sanctions and screening exposure on any party to the claim, plus duplicates and inconsistencies worth investigating
Completeness What was submitted, against what the coverage decision needs Whether there is enough to reach a coverage position, or what is missing and who supplies it
Recommendation All of the above, taken together The recommended coverage position, the governing clause, and the reasoning that connects them

How sprout.ai improves claims performance

One coverage check, run the same way on every claim in the book

Extraction and evidence agent

Classifies and reads every document in the file including policy wording, schedules, endorsements, survey and forensic reports, pleadings, correspondence, across formats and languages, and establishes what the claim actually says.

Triage agent

Reads the account of the circumstances and establishes what happened, then decides whether there is enough here to reach a coverage position at all. 

Policy and coverage agent

Identifies the policy wording governing the claim across renewals, endorsements, retroactive dates and layers.

The recommendation

The agents’ findings resolve into one output per claim: the recommended coverage position, the governing document, the clause applied, the evidence considered, and the reasoning that connects them – traceable back to the document, section and page it came from. 

Evidence analysis agent

Reads specialist evidence against the coverage question, bringing together what the survey, expert opinion and financial evidence show, where they conflict, and whether those differences affect the outcome. 

Claim integrity agent

Screens the parties named on the claim, insureds, counterparties, consignees and intermediaries, against sanctions and watch lists as part of the same pass that reads the file, so a compliance failure surfaces before the claim is worked rather than at payment.

Improves with your team's experience

Adjuster feedback helps Sprout.ai identify gaps and improve recommendations over time. New claim types are tested on a small set of reference claims first, giving your team confidence and control.

The KPIs sprout.ai moves

65%

of cargo damage comes from poorly packed or secured containers. Sprout.ai checks every claim the same way, so routine ones move fast and complex ones surface early.

Source: TT Club, insurance claims record analysis
30%

of annual marine claims value comes from just the most costly 1% of claims. Sprout.ai’s triage AI agent flags high-risk claims before specialist time is committed, not after.  

Source: Allianz Commercial / Nordic Association of Marine Insurers
Only1%

of bills of lading are digital, despite shipments generating up to 50 pages of paperwork. Sprout.ai reads paperwork as it arrives, in any format or language.

Source: McKinsey & Company

What our customers say

“

I had the opportunity to lead the implementation at MetLife Chile, working alongside the Sprout.ai team. It was a great experience of collaboration and innovation, delivering excellent results for customer experience.

Pablo Guajardo

|

Claims Manager & Operational Transformation Lead, Metlife Chile

“

AdvanceCare is continuously looking for innovative ways to improve the insurance claims experience. We selected Sprout.ai as our partner, as they have demonstrated that their technology and approach can take us one step forward in our digitalization and efficiency journey.

Sergio Melro

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Chief Operating Officer, AdvanceCare

“

Our partnership with Sprout.ai is another example of how MetLife is innovating with high tech solutions to address real customer needs.

Venkata Natarajan

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Chief Information Officer, MetLife

“

Our customers highly value the digital reimbursement solution that we provide through our app and web portal. Focusing on efficiency also means focusing on time resolution and the quality of service we provide to our customers. This is why we see AI as a useful tool and look for solutions that contribute to this, such as Sprout.ai.

Liliana Silva

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Operations Director, AdvanceCare

“

We know making a claim can be stressful, so we're dedicated to processing them quickly and smoothly. By partnering with Sprout.ai, we're using cutting-edge AI and NLP to free up our claims handlers, allowing them to focus on delivering empathetic support to customers.

David Russell

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Senior Manager, Claims & Underwriting Strategy, Scottish Widows (Lloyds Banking Group)

“

Sprout.ai can capture much more data, then format it so it is structured, allowing analysis into needs, leakage, and care quality.

Joanne Richardson

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Former Health Director, AXA

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Frequently asked questions

My book is mostly high-volume claims and a handful of very complex files. Which of those does this help with?

Both, and that is the point. The coverage work behind a high-volume claim and a complex one is the same work — read the wording, establish which terms govern, test the evidence against them. Running it on every claim means routine claims stop consuming specialist attention, and the complex ones arrive with the file already assembled and the position already reasoned.
Sprout.ai re-reads the file as evidence arrives and surfaces where the coverage position has moved. That is the point at which a claim being worked as routine needs to be reclassified, and it is normally found late, if at all.
It reads the wording rather than matching it to a template. Sprout.ai identifies which document and which clause governs the claim — manuscript clauses, endorsements, retroactive dates, layered coverage, — then applies the terms and cites the clause it applied. Nothing has to be encoded in advance, which is why it holds up on wording no two policies share.
Yes. Survey and forensic reports, pleadings, expert opinions and financial loss calculations are read against the coverage question and against each other, so the finding includes where two documents disagree, — often the thing that actually decides the claim.
No. Sprout.ai gives specialists a cited view of the wording and the evidence, so less of their time goes on assembling the file and more of it on the judgement. The recommendation is theirs to accept, override or escalate, and the record shows which they did.
Every recommendation records the documents considered, the clause applied, the reasoning, the role of Sprout.ai and the role of the adjuster. That gives you a traceable record of who did what, why and when and is reviewable internally, explainable to an insured or broker, and reconstructable for a regulator or a dispute.
No. Sprout.ai classifies and reads the payload as it arrives, across formats and languages, rather than requiring a standard submission. That variety is what conventional extraction struggles with, and it is worst at volume.
Sprout.ai connects via API to existing claims infrastructure, including Guidewire, Duck Creek and other platforms, without core system replacement. Sprout.ai’s Guidewire Cloud Accelerator is available now.