“Non-life insurance poses little to no money laundering risk.” For years, this belief has shaped global regulatory priorities. Life insurance remained under strict anti-money laundering (AML) oversight, while general insurance received limited attention. But as criminal methods evolve, so too must the approach to AML in non-life insurance.
SymphonyAI investigates why non-life insurance can no longer be considered a low-risk sector for financial crime and why AML teams need to adapt their monitoring frameworks.
Historically, non-life insurance appeared low risk because it rarely handles deposits or cash, onboarding is mostly digital, and claims are linked to tangible assets. Regulators focused on life insurance due to its investment-like nature, leaving general insurance largely under the radar.
However, today’s criminal schemes have changed the landscape. What was once considered a reasonable assumption now significantly underestimates the threat.
The reality
Modern laundering strategies no longer rely on cash-heavy transactions. Fraudulent claims, falsified documentation, and policy manipulation now serve as effective avenues for cleaning illicit funds. SymphonyAI identifies several key trends:
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Motor and property insurance fraud is increasingly used to layer criminal proceeds rather than just scam payouts.
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“Crash-for-cash” scams in the UK surged 6,000% in a single year, frequently linked to organised networks.
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Short-term policies and refunds during cooling-off periods allow funds to be circulated with minimal trace.
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Over-insurance of high-value items, followed by staged loss or theft, enables criminals to receive large, seemingly legitimate settlements.
Even without deposits or investment features, non-life insurance offers payout flexibility that is attractive to criminals.
Why it matters for AML teams
Most AML controls in insurance were designed for life products. Indicators like early surrender or beneficiary changes don’t apply to non-life insurance, but other red flags often go unnoticed. SymphonyAI highlights these signals:
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Unusual premium activity, including overpayments, multiple payment methods, or rapid refunds
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Frequent policy cancellations or requests for return of premium shortly after purchase
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Claims that appear excessive relative to the risk or timing of the policy
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Third parties paying premiums or receiving claim payouts, especially for commercial policies
On the surface, these activities may seem administrative, but they can signal layering, concealment of proceeds, or fraud-enabled laundering. AML platforms tailored for insurance, particularly those leveraging AI and cross-policy entity profiling, can detect these patterns early.
Ignoring these risks can result in missed linkages across products, delayed detection of criminal patterns, ineffective compliance resource allocation, and increased regulatory scrutiny.
What organisations can do
SymphonyAI recommends that insurers adjust their AML frameworks to address emerging threats:
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Conduct risk assessments across all product lines, not just life insurance
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Align fraud detection with AML case management
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Deploy AI-powered models that blend structured rules with anomaly detection
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Maintain open communication between compliance, underwriting, and customer teams to flag unusual behaviour in real time
What’s the bottom line?
The risk landscape has changed, and criminals have adapted. While general insurance may be less directly exploited for placement and layering, exposure to criminal proceeds, indirect laundering, and fraud typologies remains real—particularly in high-value commercial lines and global programmes.
Non-life insurance is no longer “low risk”—it is underestimated risk. In financial crime, underestimating risk is exactly what bad actors rely on.
Read the full blog from SymphonyAI here.
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