How Synthetic Identities Are Impacting the Insurance Industry
Synthetic identity theft involves creating a new identity from pieces of real and false information. Fraudsters often use real Social Security members (SSNs) combined with fake names and addresses to create these “synthetic” identities. These fraudulent profiles can be used to open credit card accounts, apply for loans, or even take out insurance policies. The challenge for insurance companies is that these synthetic identities often go undetected until it’s too late – by which time the fraudster has already taken out the policy or service using the stolen identity.
The best way for insurance companies to combat synthetic identities is by implementing an enterprise-wide digital strategy that validates customer data at the point of collection in real time. This could include requiring customers to provide additional forms of identification and validation of signatures, personal identifiable information and documentation of records when applying for coverage. Additionally, insurers should monitor accounts regularly for suspicious activity and use entity resolutions and artificial intelligence and machine learning technology to identify patterns that may indicate fraud. In addition to utilizing advanced analytic and fraud detection solutions, companies should focus on training employees on how to spot signs of potential identity fraud and what steps they should take if they suspect fraud in occurring on a policy, claims, or account.
Synthetic identity fraud is becoming increasingly common in the insurance industry and can be difficult to detect without the right technology in place. Fortunately, there are steps insurers can take to protect their business, customers, and insureds from this type of fraud – such as using advanced entity resolution technology, network generation and perpetual customer monitoring for suspicious activity – to ensure that only legitimate customers area able to access their policies, accounts, and services. By taking proactive steps now, insurance companies can reduce their risk of falling victim to synthetic identity fraud.
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Interesting thoughts Alan!
We've just recently invested to create an analytical approach which models all enterprise customer profiles against a wide variety of real-time digital entity and biometric inputs to create a "controlling digital mind". This enables surfacing of digital connections to be surfaced which previously were hiddem from "unconnected" stolen or synthetic identities and has helped surface a variety of application fraud threats hitting carriers.
What are you seeing as the biggest opportunity for this type of next generation detection methodolgy?
@Shyam_Bhatt @Matt @Ross interested in your views too.
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@MattG really interested in your view here :)
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Fascinating subject with lots of angles to explore @Alex_Johnson @Shyam_Bhatt :
- synthetic IDs in insurance is not new and in my view just more of a topic for discussion as insurers have upped their game and made better use of data to detect fraud
- although ... potential rise in synthetic IDs can be correlated to insurer adoption and use of credit bureau data at point of quote (limiting the use of wholly false IDs to obtain policies - be this for policy fraud, as a precursor to claim fraud or to enable organised crime)
- there's certainly ways to reduce exposure, especially at point of quote - entity resolution has a role to play, as does additional data validation points (e.g. email / phone / device) and layers such as payment auth and verification
- for me the challenge is less around can it be identified and more around layering all the solutions in the most cost effective ROI strategy WITH optimal integration into a friction appropriate customer journey
- I think far more fun is the emerging claims space - with litigants in person and organisations under desperate pressure to control 3rd party claims costs through early intervention - how to spot, weedle out and manage synthectic IDs used in claims
- Probably worth calling out that synthectic IDs are, arguably, more of an enabler rather than a fraud loss per se (e.g. the fronted policy used by a ghostbroker to cover their clients as additional named drivers etc)
Would like to hear more feedback on the group on strategies for optimising the layers of data and solutions, especially in a real time high trading volume (point of quote) environment.
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Synthetic identification fraud has become a growing concern, particularly in the realm of health insurance. Criminals create fake identities using a combination of real and fabricated information or steal an identity then pose as the legitimate policyholders in order to obtain medical benefits. By operationalizing internal data assets and accessing external data sets fraud prevention protocols can be put in place at the application and point of sales through to FNOL. In my opinion application fraud is the most undetected insurance fraud. How can you protect against application fraud?
- Focus on strong identity proofing tools for customer intelligence
- Real-time entity resolution and verification protocols
- Enrich internal and external with analytics and scoring models
- Identify social media and online presence
- Validate with ID verification and documentation or biometrics
As soon as we think we've figured out how the criminals figure out new ways to commit fraud!
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