Insurers globally lose an estimated 5 to 10 percent of total claims payouts to leakage every year. For a mid-size carrier processing $500 million in claims annually, that is between $25 million and $50 million in recoverable margin — lost not to fraud or catastrophic events, but to process failures that compound quietly across thousands of ordinary claims.

Most claims technology investment over the past decade has focused on speed — getting claims opened faster, closed faster, communicated faster. That focus is legitimate, but it has left the underlying workflow architecture largely intact. The result is that carriers are running faster on the same operational rails that produced the leakage in the first place.

This article is for the CIOs, CTOs, and COOs who are responsible for claims technology and operations and who have already invested in platforms, data, and people — but are still watching the combined ratio resist meaningful improvement. The argument here is not that you need more technology. It is that the operational layer between your technology investment and your financial outcomes needs to change.

What Claims Leakage Actually Means — and Where It Comes From

Claims leakage is the gap between what a claim should have cost under optimal handling conditions and what it actually cost. It is not primarily a fraud problem, though fraud sits within the broader definition. Most leakage comes from three operational sources that every claims director will recognise.

Traditional audits catch leakage after it has already happened. Intelligent automation catches it before payment is authorised.

The reason leakage persists despite technology investment is that most audit and reporting processes are retrospective. Leakage is identified in quarterly reviews and attributed to individual claims decisions. That analysis is useful for trend identification, but it does not change the outcome of the claims that produced it. The operational shift required is from retrospective detection to real-time intervention — and that shift requires a different type of platform architecture than most carriers currently have in their claims function.

Why Manual Workflows Are the Root Cause

It is worth being precise about what 'manual workflows' means in the context of a modern claims operation, because most carriers have made significant technology investments and would not describe their operations as manual in the traditional sense. The issue is not the absence of technology. It is the architecture of how technology connects — or fails to connect — to adjuster decisions.

The adjudication gap is the space between what your data knows and what your adjuster acts on. In most claims operations, that gap is significant. An adjuster handling a complex liability claim may be working across a core claims system, a document management platform, a provider billing tool, a communication log, and a spreadsheet-based reserve tracker. Each of those systems may contain information relevant to the claim, but the adjuster is the integration point, not the technology.

When humans serve as the integration layer between disconnected systems, decisions are made without full information, processes are inconsistent across individuals, and errors compound. The specific workflow failures that drive leakage tend to follow recognisable patterns:

How Intelligent Automation Changes the Operational Equation

Intelligent automation in claims is not a feature or a module. It is a change to the fundamental architecture of how claims move through your organisation. The distinction matters because many carriers have implemented point solutions — automated fraud flags, digital first notice of loss, chatbot-based status updates — without changing the underlying workflow model. Point solutions reduce friction at specific touchpoints without addressing the adjudication gap that produces leakage.

A platform-based approach connects the data, the decision logic, and the workflow into a single operating model. The outcomes are qualitatively different from what point solutions deliver:

Why Pega Is the Platform Insurance Leaders Are Choosing

There is no shortage of claims technology vendors, and the market is not short of platforms that promise automation, AI, and operational improvement. The reason Pega occupies a different position for carriers operating at scale is architectural, not feature-based.

Most claims platforms are built around case management or workflow automation, with AI capabilities added as a layer on top. Pega's architecture inverts that model. The decisioning engine is core to the platform, not a feature sitting above it. That means every workflow step, every routing decision, every reserve recommendation, and every compliance check can be driven by the same centralised decisioning logic, operating in real time, across the full claims portfolio.

The Implementation Gap: Why Most Pega Deployments Underdeliver

Many insurers have invested in Pega, or in comparable platforms, and have not seen the leakage reduction or operational improvement that the platform is capable of delivering. The platform is not the problem. The implementation is.

The specific failure patterns are consistent across carriers that have experienced this:

A Pega deployment that is correctly scoped, configured for claims-specific logic, and optimised post‑go‑live delivers measurable margin recovery. One that is not, adds cost without improving the combined ratio.

The difference between a Pega deployment that delivers measurable claims leakage reduction and one that does not is not the platform. It is whether the implementation partner has the claims operations knowledge to configure the decisioning logic correctly, the integration experience to close the data gaps, and the delivery methodology to carry the organisation through the change management challenge that any workflow transformation requires.

IQZ's claims practice was built around exactly this problem. Our implementation methodology starts with baseline measurement — establishing a clear, quantified picture of current leakage sources and handling costs before any configuration begins. It covers claims-specific decisioning logic, a structured change management programme, and a post-go-live optimisation phase where performance against the baseline is measured until the financial outcomes are demonstrable.

Three Questions to Assess Your Current Leakage Exposure

Before engaging with any technology or implementation conversation, it is worth establishing a clear picture of your current exposure. If the answer to any of these is "we don't know" or "it takes too long," the operational gap is real and the leakage is measurable.