Introduction
Claims leakage describes the gap between what an insurer pays on a claim and what should have been paid under the policy. Unlike fraud, claims leakage is not necessarily the result of deception. It can arise from process inefficiencies, missed opportunities, or inconsistent decisions, and it represents one of the largest controllable cost areas in claims operations.
Reducing claims leakage is a priority for most insurers, but the work requires a clear view of where leakage originates.
What Claims Leakage Means (Plain English)
Claims leakage is money paid out on a claim that did not need to be paid, or that could reasonably have been avoided through better information, controls, or processes.
Common causes include:
- Failure to identify fraud or exaggeration
- Missed recovery opportunities, such as subrogation
- Inconsistent application of policy terms or excesses
- Overpayment of supplier or repair costs
- Incomplete validation of claimed losses
Why Claims Leakage Is Hard to Measure
Claims leakage is rarely visible in a single transaction. Each individual decision may look reasonable, but small overpayments and missed opportunities accumulate across thousands of claims, adding up to material losses across the portfolio.
Measuring leakage typically involves sampling claims, applying a structured review framework, and comparing what was paid against what should have been paid under a robust handling standard.
The Relationship Between Leakage and Fraud
Fraud is one source of claims leakage, but it is not the only source. A claim may be entirely genuine and still leak value through poor handling. Equally, leakage controls that focus solely on fraud will miss the wider operational issues that contribute to losses.
This is why mature claims operations treat leakage and fraud as related but distinct disciplines, supported by overlapping data and analytics.
Common Leakage Drivers
Typical drivers of claims leakage include:
- Inconsistent decisions across handlers or offices
- Insufficient time spent on validation of higher-value claims
- Limited use of data to challenge supplier pricing
- Weak processes for identifying subrogation, salvage, or recovery opportunities
- Late identification of fraud, after costs have already been incurred
Reducing Claims Leakage
Effective leakage reduction relies on a combination of data, process, and culture. Insurers that materially reduce leakage typically invest in:
- Consistent handling standards supported by clear workflows
- Data-driven validation of claimed values and supplier pricing
- Early fraud detection at FNOL and through the claim lifecycle
- Feedback loops from leakage reviews back into training and process design
Role of Analytics and Workflow
Analytics support leakage reduction by surfacing patterns that human review alone would miss. Comparisons across similar claims, suppliers, and handlers help identify where standards are slipping and where additional controls are warranted.
Under APRA’s CPS 230 operational risk framework (effective 1 July 2025), regulated insurers are required to identify, assess, and manage material operational risks — a category that explicitly includes risks from process failures contributing to losses. Effective leakage management aligns directly with this expectation.¹
Related Topics
Claims fraud: detection, investigation, and prevention
Exaggerated claims
Risk scoring and prioritisation
Workflow management in fraud and compliance
Sources & further reading
¹ APRA — Prudential Standard CPS 230 Operational Risk Management (effective 1 July 2025)
² KPMG Australia — General Insurance Insights 2025
³ Insurance Council of Australia — General Insurance Code of Practice 2020
⁴ Australian Prudential Regulation Authority — general insurance institution-level statistics
