As insurers work to modernize claims experiences, reducing friction, accelerating payouts, and enabling self-service, they’re facing a new class of risk: claimants who may not be who they say they are. From synthetic identities to AI-generated documentation and manipulated images, today’s fraud schemes are designed to exploit speed, trust, and incomplete identity verification.
While insurance is on the front lines of this challenge, it’s far from alone. The same identity-based fraud patterns now appear across travel refunds, logistics claims, peer-to-peer payments, and marketplace disputes, anywhere a business must make fast payout decisions with limited information.
This article serves as a primer on how modern identity fraud works across claim-driven industries, and how access to people data can help organizations with verifying identities, detecting manipulation, and protecting revenue, without slowing down legitimate customers.
About Scams, Digital Identities, and Manipulated Information
Ordinary identity theft is well understood. Scammers steal crucial identifying information that relates to real people through avenues such as buying their private data after a major breach, individual phishing attacks, or accessing the victim’s papers or phone physically. Synthetic identity theft is less known, but a bigger threat to businesses. Synthetic identities use a combination of data from multiple sources — perhaps an infant’s SSN, combined with an adult’s driver’s license number and a random photo from a social media platform — to create a new identity that can be used to open accounts, establish credit, and deal with vendors.
Let’s look at some specific examples of how scammers use synthetic/stolen identities or manipulated data across multiple industries.
Fraudulent Insurance Claims
Insurance scams lean heavily on identity theft — and are on the rise. The National Insurance Crime Bureau estimated a 49% rise in identity-related scams in 2025. A representative handful of common scams includes:
- Using stolen or synthetic identities to drain the cash values from long-held life insurance policies, or to impersonate beneficiaries and claim the death benefit.
- Stealing the identities of consumers with good health coverage and maxing out their lifetime limits.
- Using manual image-editing software or AI tools to create convincing images of damage to vehicles or property, or to craft fraudulent documentation.
Travel Fraud Claims
Travel fraud, unlike some of the other schemes on this list, tends to have two victims: the person whose credit card information has been stolen and the travel operator on the receiving end of the booking. Catching these types of suspicious transactions before travel occurs is key to preventing lost revenue.
Here are two of the most common schemes:
- Scammers with a stolen or synthetic ID make a reservation, using the identity theft victim’s credit card number. Scammers travel at the card issuer’s cost, which becomes a loss when the legitimate cardholder notices and challenges the charge.
- In a refinement of the previous scheme, the scammer claims to have overpaid for flights or accommodations and requests a price adjustment or partial reimbursement, paid to another card or account. The issuer loses a secondary amount, above and beyond the primary loss, when the charge is reversed.
Logistics Fraud
In the most common form of logistics fraud, criminals use stolen identities to pose as legitimate logistics firms or contracted truckers and arrange false pickups of cargo. The scammers load a truck with high-value cargo at the dock, then disappear with their ill-gotten gains.
On the flipside, scammers will also take advantage of the fact that repairs to cargo trucks need to be taken care of as quickly as possible in order to ensure logistics companies can meet deadlines and deliver loads on time. In this scheme, they’ll pose as drivers or repair shops, claiming that they need money or payment to cover a necessary repair. The logistics company will send over payment via credit card or e-check without a second thought, only to later find out a repair was never needed in the first place.
Peer-to-peer Platform Fraud
While PayPal enjoys widespread commercial use as a payment processor, it’s relatively rare for companies to accept P2P payment apps like Venmo, Zelle, or CashApp, because they’re complicated to administer and not especially cost-effective for the vendor. But identity fraud that originates in P2P systems can, and does, spill into merchant disputes, chargebacks, and investigations.
In this scheme, the criminal gains access to a consumer’s account through identity theft or account takeover and uses it to make high-value purchases through the peer-to-peer account. When the fraud is discovered, the vendor is on the hook for the cost of the goods and services provided, pending the outcome of a reimbursement claim.
Marketplace and E-commerce Disputes
The main aim of these scams is to make off with both the product and a refund, resulting in frustrating losses for merchants. Two of the most common are:
- A scammer uses a stolen or synthetic identity to make purchases on a legitimate credit card, but has them delivered to an address not under the cardholder’s control. When the purchase is charged back, the vendor is out of pocket for its value.
- A genuine or synthetic customer orders a product, then fabricates pictures falsely showing it as damaged in transit in order to claim a refund or reimbursement.
Why Better Data is Key to Efficient Claim Fraud Detection
Claim fraud detection is a thorny problem, most notably when synthetic identities are in play. Ideally, it would be best to identify potential fraud before the claim is completed, but this isn’t always practical. Next best is at “first notice of loss” (FNOL), when the customer (real or purported) files the claim.
Once a reimbursement is issued or a claim is paid, your revenue protection team’s only option is to chase down the fraud after the fact, in an effort to recover your money and/or generate enough evidence to potentially lead to charges being laid. This is especially problematic when the criminals have used a synthetic identity, because those are difficult even for law enforcement agencies to pick apart using legacy data tools. Synthetic identities rarely fail because of one incorrect detail; they fail because their information doesn’t hold together over time. Names, phone numbers, email addresses, addresses, and online presence are often assembled from multiple sources, creating personas that look plausible in isolation but fall apart when examined holistically.
This is where modern people data platforms like Spokeo for Business provide unique value. By aggregating and cross-referencing signals across multiple data points and historical records, Spokeo helps claims and fraud teams assess whether a claimant’s information matches those signals — or shows signs of fabrication and manipulation.
Instead of slowing claims with manual reviews, people data enables faster, more confident decisions by revealing inconsistencies early in the process.
During a Transaction
There are many tools that companies can use to automatically flag and suspend suspicious-looking transactions as they’re occurring. This should be the first line of defense for any business offering self-serve purchasing, but it does not always go far enough—especially once a transaction has been flagged for review by automated tools.
For example, Spokeo searches can quickly help establish whether the transaction originates from phone numbers or email addresses that are consistent with the account-holder’s information. This can be especially helpful for investigating the types of travel and e-commerce merchant fraud discussed above, as the contact information signals can help determine if there is a sufficient-enough match to allow a transaction to proceed forward or move to a higher level of manual review.
At First Notice of Loss
First notice of loss is often the most critical and vulnerable moment in the claims process. At this stage, fraud teams are asked to evaluate documentation, images, and personal details that may be incomplete, manipulated, or entirely fabricated.
Here are a few ways to empower teams to act quickly once a red flag is raised:…
- Rather than relying solely on documents submitted by the claimant, organizations can introduce people data into the FNOL process. By validating whether a name, phone number, email address, address history, and digital footprint align in a consistent and credible way, teams can quickly identify claims that warrant deeper review, while allowing legitimate claims to proceed without unnecessary delays.
- This “trust but verify” approach helps insurers and claims teams move beyond surface-level validation and toward confidence through corroboration, especially in cases involving synthetic identities or AI-assisted fraud.
During the Investigative Process
Incorporating Spokeo for Business into your investigative process for claims or refunds places an additional powerful fraud detection tool at your disposal. Aside from verifying photos, you might also opt for additional checks, such as:
- Methodically cross-searching the names, telephone numbers, and other pieces of personal identification used in the claim to identify discrepancies and inconsistencies. Inconsistent results might indicate a synthetic ID cobbled together from multiple sources. Consistent results, meanwhile, might suggest a deliberately fraudulent claim by the client.
- Using Spokeo’s unsurpassed social media search to identify the claimant’s social media accounts and review their public posts, photos, and videos for evidence that supports or contradicts the claim or refund request. This is especially useful in determining the validity of disability insurance claims.
After the Claim or Reimbursement is Paid Out
After any money has been disbursed on a fraudulent claim or refund request, or merchandise has been trucked away from your warehouse, recovery and potential prosecution become priorities. Law enforcement agencies are chronically overworked, so any information you can uncover about the persons behind the fraud makes it more likely an arrest or settlement will result.
Helpful steps you could take include:
- Documenting discrepancies between data in the claim and contradictory information gleaned from a search of the client’s social platforms, which are easy to find using Spokeo. This can help pressure the client to offer restitution.
- Working through the list of phone numbers, email addresses, and social media usernames turned up by Spokeo when you searched the stolen or synthetic ID used to commit fraud. Even when criminals use “burner” accounts, it’s not uncommon for them to use those accounts to publicly interact and communicate with their family and friends—and those connections can help establish a direct link to the real person behind the fraudulent account.
Where Digital Identity Fraud Meets New Data Tools
As digital claims processes accelerate, fraud has evolved to exploit identity gaps rather than policy loopholes. Documents, images, and even video evidence can now be fabricated at scale, making it increasingly difficult to separate legitimate claims from fraudulent ones using traditional verification methods alone.
Organizations that succeed in this environment are those that augment existing fraud controls with identity intelligence, adding context, continuity, and confidence to every decision.
Spokeo for Business helps insurance and claims-driven organizations do exactly that by bringing people data into the fraud prevention workflow, supporting faster investigations, fewer fraudulent payouts, and better outcomes for legitimate customers.
Reach out to explore our solutions and learn how Spokeo for Business can support your claims and fraud teams.
Sources
Shopify User Blog: Frictionless Experience: How to Create Smooth User Flows
National Insurance Crime Board: NICB Projects 49% Rise in Insurance Fraud Linked to Identity Theft in 2025
The Federal Reserve: Synthetic Identity Fraud Defined
Mozilla Foundation “Distilled” Blog: What Is a SIM Swapping Scam and How Can You Protect Yourself?
Life Insurance Attorney: Life Insurance Denials in Digital Identity Theft Cases
Insurance Journal: Generative AI: A Double Agent Serving Good and Evil In the World of Claims
ABTA: The Five Most Common Types of Travel Fraud
Merchant Cost Consulting: Can Businesses Accept P2P App Payments? (Venmo, Zelle, CashApp)