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Combating Fraud with Experian’s New Precise ID® Model Suite

Published: May 6, 2020 by Guest Contributor

One of the most difficult parts of combating fraud is the ability to distinguish between the variety of fraud types. To properly manage your fraud efforts, you need to be able to differentiate between first party fraud and third party fraud so you can determine the best treatment.

After all, if you’re treating first party fraud as though it’s third party fraud, the customer you’re contacting for verification will give whatever information they need to in order to continue their criminal actions. So how do you verify each type of fraud without adding additional overhead or increasing the friction experienced by your customers?

Combating Fraud During an Economic Downturn

Particularly in times of economic uncertainty, the ability to detect and identify individual fraud types allows you to work to prevent them in the future. Through proper identification, you can also apply the correct treatments to maximize the effectiveness of your fraud response teams, since the treatment for first and third party fraud is different.

During the economic upswing, first party fraud was a secondary concern. Businesses were easing friction to help continue growth. Now, the same customers that businesses thought would drive growth are hurting and unable to help offset the losses caused by bad actors.

Now is the time to revisit existing fraud prevention and mitigation strategies to ensure that fraud is properly identified, and the correct treatments are applied.

Introducing Precise ID® Model Suite

Experian’s Precise ID Model Suite combines identity analytics with advanced fraud risk models to:

  • Protect the entire customer journey again fraud – across account opening, login, maintenance and transactions
  • Distinguish first-party, third-party, and synthetic identity fraud to determine the best next action
  • Enable agility during changing market conditions
  • Maintain regulatory compliance (including: KYC, CIP, GLBA, FCRA, FFIEC, PATRIOT Act, FACTA, and more)
  • Improve overall fraud management strategies and reduce losses

Precise ID Model Suite allows you to detect and distinguish types of fraud with a single call – enabling your business to maximize efficiency and eliminate redundancy across your fraud prevention teams. By accurately recognizing risk, and in particular, recognizing that first party fraud is in fact a type of fraud distinct from credit risk, you’re able to protect your portfolio and your customers.

Learn more

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Fake IDs have been around for decades, but today’s fraudsters aren’t just printing counterfeit driver’s licenses — they’re using artificial intelligence (AI) to create synthetic identities. These AI fake IDs bypass traditional security checks, making it harder for businesses to distinguish real customers from fraudsters. To stay ahead, organizations need to rethink their fraud prevention solutions and invest in advanced tools to stop bad actors before they gain access. The growing threat of AI Fake IDs   AI-generated IDs aren’t just a problem for bars and nightclubs; they’re a serious risk across industries. Fraudsters use AI to generate high-quality fake government-issued IDs, complete with real-looking holograms and barcodes. These fake IDs can be used to commit financial fraud, apply for loans or even launder money. Emerging services like OnlyFake are making AI-generated fake IDs accessible. For $15, users can generate realistic government-issued IDs that can bypass identity verification checks, including Know Your Customer (KYC) processes on major cryptocurrency exchanges.1 Who’s at risk? AI-driven identity fraud is a growing problem for: Financial services – Fraudsters use AI-generated IDs to open bank accounts, apply for loans and commit credit card fraud. Without strong identity verification and fraud detection, banks may unknowingly approve fraudulent applications. E-commerce and retail – Fake accounts enable fraudsters to make unauthorized purchases, exploit return policies and commit chargeback fraud. Businesses relying on outdated identity verification methods are especially vulnerable. Healthcare and insurance – Fraudsters use fake identities to access medical services, prescription drugs or insurance benefits, creating both financial and compliance risks. The rise of synthetic ID fraud Fraudsters don’t just stop at creating fake IDs — they take it a step further by combining real and fake information to create entirely new identities. This is known as synthetic ID fraud, a rapidly growing threat in the digital economy. Unlike traditional identity theft, where a criminal steals an existing person’s information, synthetic identity fraud involves fabricating an identity that has no real-world counterpart. This makes detection more difficult, as there’s no individual to report fraudulent activity. Without strong synthetic fraud detection measures in place, businesses may unknowingly approve loans, credit cards or accounts for these fake identities. The deepfake threat AI-powered fraud isn’t limited to generating fake physical IDs. Fraudsters are also using deepfake technology to impersonate real people. With advanced AI, they can create hyper-realistic photos, videos and voice recordings to bypass facial recognition and biometric verification. For businesses relying on ID document scans and video verification, this can be a serious problem. Fraudsters can: Use AI-generated faces to create entirely fake identities that appear legitimate Manipulate real customer videos to pass live identity checks Clone voices to trick call centers and voice authentication systems As deepfake technology improves, businesses need fraud prevention solutions that go beyond traditional ID verification. AI-powered synthetic fraud detection can analyze biometric inconsistencies, detect signs of image manipulation and flag suspicious behavior. How businesses can combat AI fake ID fraud Stopping AI-powered fraud requires more than just traditional ID checks. Businesses need to upgrade their fraud defenses with identity solutions that use multidimensional data, advanced analytics and machine learning to verify identities in real time. Here’s how: Leverage AI-powered fraud detection – The same AI capabilities that fraudsters use can also be used against them. Identity verification systems powered by machine learning can detect anomalies in ID documents, biometrics and user behavior. Implement robust KYC solutions – KYC protocols help businesses verify customer identities more accurately. Enhanced KYC solutions use multi-layered authentication methods to detect fraudulent applications before they’re approved. Adopt real-time fraud prevention solutions – Businesses should invest in fraud prevention solutions that analyze transaction patterns and device intelligence to flag suspicious activity. Strengthen synthetic identity fraud detection – Detecting synthetic identities requires a combination of behavioral analytics, document verification and cross-industry data matching. Advanced synthetic fraud detection tools can help businesses identify and block synthetic identities. Stay ahead of AI fraudsters AI-generated fake IDs and synthetic identities are evolving, but businesses don’t have to be caught off guard. By investing in identity solutions that leverage AI-driven fraud detection, businesses can protect themselves from costly fraud schemes while ensuring a seamless experience for legitimate customers. At Experian, we combine cutting-edge fraud prevention, KYC and authentication solutions to help businesses detect and prevent AI-generated fake ID and synthetic ID fraud before they cause damage. Our advanced analytics, machine learning models and real-time data insights provide the intelligence businesses need to outsmart fraudsters. Learn more *This article includes content created by an AI language model and is intended to provide general information. 1 https://www.404media.co/inside-the-underground-site-where-ai-neural-networks-churns-out-fake-ids-onlyfake/

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