What if the greatest risk to your business identity was lurking in a combination of real and fabricated information? In our latest BEV Break webinar, Jules Mei, Middesk’s expert in Product Operations, outlined the tactics fraudsters use to exploit vulnerabilities and shared smarter approaches to preventing synthetic identity fraud.
Here’s a breakdown of the top insights from the session:
Synthetic identity fraud is a growing threat
Synthetic identity fraud is on the rise, costing industries nearly $5 billion annually. Unlike traditional identity theft, synthetic fraud creates fake “Frankenstein” profiles by blending real data—like EINs or TINs—with fabricated business details.
These profiles can bypass basic compliance checks to:
- Open fraudulent accounts
- Obtain credit lines that default after months or years
- Disappear after high-value eCommerce purchases, leaving businesses with significant losses
📽️ Watch Jules explain the unique characteristics of synthetic fraud and why it’s so difficult to detect
The high cost of fraud for businesses
The impact of synthetic fraud is felt most heavily in financial services and eCommerce. Fraudsters exploit these sectors’ focus on seamless onboarding and high-growth strategies, which often leave compliance gaps.
Key risks include:
- Operational strain: Fraud investigations demand time and resources from analysts, legal, and technical teams
- Revenue loss: Defaulted loans, credit lines, and chargebacks often have no recourse
- Reputational damage: Loss of trust among customers, partners, and investors, as well as jeopardized banking licenses and partnerships
📽️ Jules breaks down how synthetic fraud affects businesses operationally, financially, and reputationally
Strategies to detect synthetic identity fraud
Effective fraud prevention requires a layered approach that combines robust verification processes with advanced tools and analytics:
Jules shared insights on how businesses can build comprehensive fraud detection frameworks:
- Develop a strong foundation: Ensure foundational data, such as incorporation details and ownership information, is accurate and reliable
- Leverage alternative data sources: Use transaction history, geolocation, and device behavior to build more nuanced risk profiles
- Invest in real-time monitoring: Identify anomalies quickly by tracking changes in business data, such as addresses, IP activity, or transaction patterns
- Harness advanced technologies: AI and machine learning can help detect fraud faster, freeing teams to focus on strategic cases and evolving fraud tactics
📽️ Explore how digital footprints reveal fraud signals like unusual address activity or shared IPs
Common characteristics of synthetic identities
Fraudsters employ predictable patterns when creating synthetic identities. Jules highlighted key characteristics businesses should monitor:
- Shared or high-risk addresses: Locations linked to multiple businesses, such as registered agent addresses, may signal fraud.
- Mismatched digital footprints: Fraudulent entities often exhibit inconsistent or suspicious online behavior, like placeholder text, broken links, or domains registered recently.
- Unusual transaction patterns: Rapidly opening multiple bank accounts or making excessive withdrawals are red flags.
- Fabricated documentation: Altered incorporation papers, utility bills, or bank statements mix real and fake details to appear legitimate.
- Networked fraud indicators: Shared IP addresses, TINs, or device IDs across accounts often reveal connections between fraudulent entities.
📽️ Watch Jules break down fraud characteristics with real-world examples
Final thoughts
Synthetic identity fraud is one of the most pressing challenges in business verification today. By adopting a layered approach—combining identity verification, alternative data, and continuous monitoring—businesses can reduce risk, protect their reputations, and build trust with customers and partners.
Next BEV Break
Join us next month to learn how to balance fraud prevention with frictionless customer onboarding. Register here!
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