Insurance
Policy and claims technology powered by AI, proven in practice
Insurance runs on a chain of decisions: notify, triage, reserve, investigate, negotiate, settle. Every step produces data, and in most operations that data stops at the boundary between systems.
The policy administration system doesn't talk to claims, claims doesn't feed reporting and reserving depends on handler judgement that's never captured. By the time a figure reaches the board, it's been re-keyed twice and is a month old.That was survivable when volumes were predictable and expectations were lower. Neither is true anymore. Policyholders judge your claims journey against their banking app, not your competitors, Consumer Duty asks you to evidence good outcomes, and boards have stopped asking whether to use AI; they're asking what it delivered last quarter, and who signed it off.Most technology partners can build you a platform. Fewer can build one a handler will actually use, an actuary will trust, and a regulator will accept. We build the ones that get used.
Four shifts are shaping insurance technology investment. Each one changes what a claims platform has to do.
From Replacement to Orchestration
Wholesale core system replacement is falling out of favour. The prevailing pattern is a composable, API-first layer that sits over the policy administration system and coordinates claims, supplier panels, finance and customer channels, delivering change in quarters rather than multi-year programmes, without a rip-and-replace risk profile.
AI Moves from Pilot to P&L
Proof-of-concept budgets are closing. AI investment is now defended on indemnity spend, claims leakage, cycle time and handler capacity. If a use case can't be tied to one of those four, it won't survive the next planning round.
Governance Becomes a Buying Criterion
Model oversight, human review thresholds, explainability and data lineage now appear in RFPs. The procurement question has shifted from what the model can do to who is accountable when it is wrong.
Reporting Becomes Operational, Not Retrospective
Monthly management information is being replaced by real-time claims MI, cohort-level outcome testing and Consumer Duty board reporting drawn from the same data the handler works in, not from a warehouse three transformations downstream.
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Claims AI
Our own product, built for claims operations. Claims AI creates a live knowledge base across policy wordings, claim files, correspondence and attachments, and lets handlers interrogate it in natural language using a retrieval-augmented model. It transcribes and summarises claimant calls, generates keywords and next actions, and surfaces email and document content directly in the file, removing the reading, searching and re-keying that consumes a handler's day. Available as SaaS or deployed into your own tenancy, with the retrieval trace behind every answer retained for audit.
Claims Platforms
AI built into the claims lifecycle rather than bolted alongside it: digital FNOL, automated triage and segmentation, claims query handling, predictive reserving, litigation propensity and straight-through settlement for low-complexity claims. Each use case sits at the point in the handler workflow where the decision is actually made, with defined human review thresholds and a complete audit trail.
Integration and the Data Layer
API-first integration across policy administration, claims, finance, supplier panels, telematics and third-party data. We treat data quality as a deliverable rather than a by-product, so the number in the reserve is the same number in the board pack.
Reporting, MI and Consumer Duty Evidence
Operational dashboards for team leaders, portfolio MI for claims directors, and outcome reporting that gives your Consumer Duty board report an evidence base rather than a narrative, built on the same data model your handlers work in.
Cloud, Security, and Managed Operations
Claims platforms running on Azure, AWS or GCP with the uptime and scalability multi-entity, multi-region operations demand. ISO 27001:2022 and Cyber Essentials Plus are the baseline on every engagement, with 24/7 monitoring, managed operations and genuine data and AI sovereignty where regulation requires it.
AI Readiness and the Business Case
Before anything is built, we map where AI would move indemnity spend, handler capacity or cycle time in your operation, size the benefit, and sequence delivery so the first release helps fund the next. Vendor-independent by design, because procurement decisions in this sector carry multi-year consequences.
“We could not be more pleased with the exceptional partnership we have developed with Abstract Group. Their proactive approach, attention to detail, and ability to translate complex business requirements into effective technical solutions have had a significant positive impact on our complex insurance platform architecture, build, BAU and AI automation. We have absolute confidence in Abstract Group's capabilities and are delighted to recommend them as a trusted and valued AI-first software development partner”
Why insurers choose Abstract
Sector-proven
Abstract has built and run claims systems through the full lifecycle of a claim, across insurer, TPA and loss adjuster operating models. That experience shapes how systems get designed; what a handler needs at file level, what a claims director needs at portfolio level, and how those two things connect without leaving a gap in between.
AI readiness before AI spend
We identify the high-return AI use cases in your claims operation before anything is built, develop the business case, and sequence implementation, so you invest in the use cases that move indemnity and capacity, not the ones that demo well.
Governed and vendor-independent
The AI we build is model and vendor independent, with governance, explainability and human oversight designed in rather than retrofitted. It matters in a sector where the regulatory position on AI is still developing and platform choice is a five-year commitment.
Accountable, flexible delivery
UK-led on every engagement, which means the people who scope your platform are the same people accountable for it in production. Take a full outsourced squad, engineers embedded alongside your own team, or a right-shored blend. The delivery model flexes, the accountability doesn't.
Book an AI Readiness Assessment
We'll map the three highest-value AI opportunities in your claims operation, size the business case, and set out what production actually looks like. You'll leave with the map, whether you build it with us or not.
Let's talkFrequently asked questions
Can we use AI in claims decisioning and stay compliant?
Yes, with the right design. That means defined human review thresholds, explainable outputs, retained decision traces and clear ownership under SM&CR. We build those controls in from the first release rather than adding them before go-live.
Do we have to replace our policy administration system?
No, most of the value sits in the orchestration, integration and AI layers above the core system. We work with the estate you have and modernise where the return justifies it.
How quickly does this show a return?
The first AI use cases in a claims operation, typically triage, summarisation and query handling, tend to reach production and measurable benefit within a single planning cycle. We sequence delivery so early releases build the case for the next phase.
Our claims data is inconsistent. Is that a blocker?
It's the starting point, not the blocker. Data quality work is part of the delivery, and the AI readiness assessment tells you honestly which use cases your data can support today and which need groundwork first.
Book a Discovery Call
30 minutes with an Abstract expert to uncover the next steps in advancing your policy and claims technology.