Insurance

Identity verification in insurance is not a single onboarding step. It is a set of controls used to establish who is applying for cover, who owns and benefits from a policy, and who should receive money when a claim or surrender is paid. The right approach varies by product, channel, risk and jurisdiction.

For insurers, brokers and digital distributors, the challenge is to stop impersonation and financial crime without making legitimate customers repeat intrusive checks. This is particularly important where identity data sits alongside health information, financial details and records about family members.

Why identity verification matters in insurance

At policyholder onboarding, insurers need confidence that an applicant is a real person and that their stated identity matches authoritative evidence. Depending on the product and risk, this can involve document checks, database matching, liveness detection for a selfie or video session, address verification, and checks on the authority of a person acting for a business or trust.

Identity assurance also matters after a policy is sold. Beneficiaries may be added or changed, ownership may be transferred, a policy may be surrendered for cash value, or a claimant may seek a payment years after the original sale. Controls that rely only on onboarding can miss impersonation, account takeover, fraudulent beneficiary changes and changing sanctions or politically exposed person risk.

AML obligations in life insurance and investment products

Anti-money laundering, or AML, rules are especially relevant to life insurance and investment-linked products. Products with cash value, including certain permanent life policies and annuities, can be misused to place funds into an insurer and later withdraw or surrender them. Early surrender, policy loans, unusual premium payments and third-party payments can be warning signs, though none is proof of criminal conduct on its own.

In the United States, insurers issuing covered products have had federal AML programme obligations since the mid-2000s. The scope includes products such as permanent life insurance and annuities, subject to regulatory definitions and exclusions. Requirements generally include a written programme, designated compliance responsibility, training, independent testing and suspicious activity reporting processes. US firms should apply the rules to their specific product mix and distribution model.

In the European Union, life insurers and providers of other investment-related insurance services are obliged entities under EU anti-money laundering law. They must apply customer due diligence, assess risk, identify beneficial owners where relevant, monitor business relationships and report suspicions through the applicable national framework. Member-state implementation can affect operational detail.

PEPs, beneficiaries and payout events

A politically exposed person, or PEP, is an individual entrusted with a prominent public function, along with certain family members and known close associates under applicable rules. PEP status is not an allegation of wrongdoing, but it can require enhanced due diligence because of corruption risk. Sanctions screening is a separate control and should not be treated as interchangeable with PEP screening.

Screening should extend beyond the policyholder where risk and law require it. Beneficiaries, owners, assignees, payers and controlling persons can all be relevant. A payout is a critical moment for renewed checks: the beneficiary may not have been verified at sale, personal circumstances may have changed, and fraudsters may try to redirect proceeds through a recently altered payment instruction.

• Verify the identity and payment details of the person or entity receiving proceeds before payment.
• Screen relevant parties against sanctions and PEP data at appropriate points, including material changes and payout.
• Review unusual beneficiary changes, third-party funding, rapid surrender requests and payment destinations that do not fit the policy relationship.
• Escalate potential matches and suspicious patterns for human review rather than relying solely on automated decisions.

Claims fraud has an identity dimension

Insurance claims fraud can involve fabricated losses, inflated losses or staged events, but identity misuse often enables those schemes. Criminals may submit claims using stolen personal information, impersonate a policyholder during a call-centre interaction, or take over an online account and change contact or bank details. Synthetic identity fraud, in which real and fabricated information is combined to create a plausible new identity, can also be used to obtain policies or establish a claims history.

Claims teams need controls proportionate to the value and risk of the claim. These may include re-authentication, document and image forensics, cross-checking claimant details against policy records, verification of representatives, and review of links among claims, devices, bank accounts and addresses. Automated fraud signals can prioritize cases, but adverse outcomes should have meaningful human oversight and a route to correct errors.

Digital distribution and the friction trade-off

Remote sales remove opportunities to inspect documents in person, making reliable digital identity checks more important. Yet excessive friction can cause applicants to abandon a quote or push lower-risk customers into manual review. Insurers can use risk-based journeys: a straightforward, low-risk application may need less evidence than a high-value life policy, a complex ownership structure or a transaction with unusual payment behavior.

Age verification may also be necessary for products or sales journeys where legal capacity, product eligibility or protections for minors are relevant. The required standard is jurisdiction and use-case specific. Firms should collect only the age evidence needed, rather than routinely retaining full identity documents when a date-of-birth or age attribute would suffice.

Privacy, sensitive data and data minimisation

Insurance processing can combine identity information with health, disability, genetic or financial data. In the EU, much of this may be personal data subject to the General Data Protection Regulation, with health data receiving additional protection. In the US, privacy obligations are split across federal, state and sector-specific laws, and insurance regulation is often state-led. Health information may fall outside the federal HIPAA framework when handled by an insurer outside a covered-provider relationship, but it can still be protected by other laws and duties.

Data minimisation means collecting, using and retaining only what is necessary for a defined purpose, such as fraud prevention, AML compliance or claims payment. Insurers should separate identity-verification data from underwriting and marketing uses where appropriate, define retention schedules, secure vendor access, explain processing clearly, and provide procedures for data subject and consumer rights. A well-designed identity programme reduces both fraud exposure and unnecessary surveillance.