seven key trends in global fraud
what organisations are doing today to meet the moment
Trust fuels confident decision making. But it’s harder to come by in a complicated world.
Businesses today face an increasingly complex and dangerous risk environment. Real-time identity verification is necessary for any competitive business, but it’s becoming harder and harder for thinly-stretched human teams to assess. At the same time, new payment systems are dramatically increasing the speed of global transactions, shortening the timeframe for risk teams to address issues.
Meanwhile, organized crime is thriving in the chaos. Global crime syndicates are sourcing security-breach details, talent, tools and other resources from the dark web. In their hands, powerful AI software enables incredibly realistic synthetic IDs, deepfake photos and videos. At the same time, individuals are increasingly engaging in first-party fraud, blurring the line between customers and fraudsters.
But there’s good reason for hope.
Companies around the world are beginning to collaborate and share risk data and insights. A better understanding of mule networks’ vital role in money laundering is rising, and joint efforts are disrupting and disbanding them. While AI is helping criminals improve the quality of their fraudulent activities, it’s also powering tools that help legitimate businesses quickly analyze a dizzying array of contextual evidence at scale.
"Businesses run on trust. In a world of complex identity, trust requires gathering robust contextual data around every transaction, analyzing it with the best tools available and collaborating together with other organizations to thwart common threats. Only then can companies confidently accelerate action in something close to real-time and keep their businesses moving."
First-party fraud has climbed rapidly, especially in EMEA and for ecommerce and financial services. It accounts for 36% of all fraud types now (after accounting for just 15% in the previous year) and is an emerging source of risk for businesses, where it can be mistaken for third-party fraud or synthetic identity fraud.
Whatever form first-party fraud takes, including bonus abuse, chargeback abuse and unwitting mule activity, perpetrators can be driven by financial pressure and a perception of low risk. Steps taken to prevent these crimes can add friction for customers as well.
For more information: The Rise of First-Party Fraud: When Customers Become the Weak Link
The dark web has long provided criminals with an under-the-radar way to engage in all kinds of illicit activity. But as research commissioned by LexisNexis Risk Solutions discovered, this collection of individual exchanges has effectively become a self-service collective marketplace for individual fraudsters and criminal networks alike.
Using cryptocurrency and other blockchain-based value stores, criminals can buy and sell ready-made synthetic IDs, mule accounts and a wealth of personally identifiable information (PII) data, often stolen in data breaches. They can also level up their game with advice, fraud tutorials, recruitment and even one-on-one mentorship. Conversations spotted on dark web forums can reveal criminals’ pain points, like their reliance on new devices and their frustration with strong Know Your Customer (KYC) techniques like biometrics and modern document authentication.
For more information: Read this story, 'Spotlight on the Dark Web'
Understanding is growing around the vital role mule networks play in laundering fraudulently obtained money and exiting funds quickly from the financial system. These networks are growing more complex, averaging around 15 mules per network, but risk management professionals have new tools to help them ramp up efforts to shut mule networks down and deprive criminals of their services.
Complicit, recruited and exploited mules shift money quickly and invisibly across geographies and channels including banks, cryptocurrency exchanges and gaming platforms. But cutting-edge fraud prevention solutions help financial institutions spot the telltale signs of mule activity, so they can stop illicit money from moving and disrupt these criminal organizations.
For more information: Insidious Mule Networks and the Global Fight Back
Reliably verifying customers today means sorting ever larger and more intricate arrays of data representing aspects of each person’s physical and digital selves including locations, devices, behavioral patterns and history. As a result, the concept of identity has itself become quite complex to assess, challenging companies who need to be able to verify customers quickly and reliably at scale.
Organized criminal networks are working overtime to exploit any security loopholes caused by this, for example by developing synthetic identities to try to bypass “thin file” emerging identity verification steps. Successfully thwarting them requires carefully assessing contextual data and applying cross-linking technology to create dynamic risk intelligence. Armed with the appropriate modular solution that fits their business model, each organization can then use this identity intelligence to make confident verification decisions with accuracy.
For more information: Embracing the New Complexity of Identity
New payment methods are on the rise around the world, with digital wallets expected to account for 61% of ecommerce transactions by 2027 and neobanking poised to rise to $2tr by 2030. Buy-now-pay-later (BNPL) options and innovations like Canada’s new Real-Time Rails system, India’s Unified Payments Interface (UPI), Brazil’s PIX and China’s complete financial ecosystem ‘super-apps’ are bringing us ever closer to a world where everyone will enjoy instant access to money.
However, every new payment scheme adopted requires a learning curve for businesses, and this gap can sometimes be exploited by fast-thinking criminal organizations. It’s critical for financial institutions to find risk management solutions that deliver a centralized view of customer activity to make informed decisions on which payments to approve or to challenge.
For more information: Keeping Pace with the Digital Payments Boom
It’s estimated that 85% of identity fraud cases involve generative AI tools, as fraudsters furiously improve fabricated IDs, deepfake selfie videos and other schemes to try to bypass verification and KYC steps. Legitimate businesses have no choice but to use their own AI-powered tools to stay ahead.
The fight isn’t quite fair, because criminals don’t have to use AI responsibly: Fairness, removal of bias and adherence to regulation are not on their agenda. Nevertheless, today’s powerful risk management solutions are embedding AI to help improve performance and spot complex fraud patterns, cross-referencing and analyzing identity data at scale.
For more information: How AI Is Changing the Fraud and Identity Game
The value of multiple companies sharing fraud data and insights (within the boundaries of regulation and privacy protection) in a well-organized way can’t be overstated. Integrating crowd-sourced risk intelligence can improve fraud capture by over 40% relative to isolated approaches. Each member’s risk insights contribute to a regional and global interconnected dataset that delivers value in real-time.
It’s not just theoretical: Industry groups are joining forces to share real-time intelligence and fight their common enemies. The results are paying dividends.
For more information: Data Collaboration Goes Global
Methodology
The seven trends identified in this story are based on unpublished and published findings from LexisNexis Risk Solutions’ proprietary research and analysis, including:
▶ LexisNexis True Cost of Fraud study, a global survey of 1,193 decision makers at financial institutions and retail and ecommerce merchants with responsibility in fraud management.
▶ LexisNexis Risk Solutions Cybercrime Report, an exploration of over 104bn transactions and 1.5bn human-initiated attacks around the world, analyzed across the customer journey including new account creations, logins, payments and other non-core transactions such as password resets and transfers. Transactions are analyzed for legitimacy based on hundreds of attributes including digital identity, device identification, geolocation, previous history and behavioral analytics.
*For the purposes of this study, Mexico is included in the LATAM region.
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