An uptick in fraudulent activity is an unfortunate byproduct of the rapid growth in the eCommerce market.
From payment card fraud and identity theft to chargeback fraud and refund fraud, scammers are continuously devising new ways to siphon money away from cardholders and merchants illegally. Of particular concern to merchants is first-party misuse of the chargeback process by cardholders. 72% of merchants surveyed for the recently published 2024 Chargeback Field Report say they have experienced a year-over-year increase in chargebacks received. Data from Visa suggests that friendly fraud could account for as many as 75% of all disputes.
Whether legitimate or illegitimate, chargebacks are costly for merchants. Mastercard reports that the average seller bears three-quarters of the cost of a dispute. In 2023, merchants worldwide lost an estimated $117.46 billion to chargebacks, thanks in part to onerous dispute fees ranging from $20 to $100 per chargeback.
These costs and the difficulties of fighting fraudulent disputes have forced merchants to implement strategies to prevent chargebacks wherever possible. The good news is that innovations in the AI space are making chargeback prevention a much more manageable prospect.
AI isn’t just a buzzword in cybersecurity. The technology is gaining traction because these tools excel at fraud detection in several ways.
First, AI tools have much higher throughput than manual or non-software-based detection methods. In real-time, they can sift through thousands of transaction data points per minute and detect suspicious patterns, outlier activities, and other fraud indicators.
AI tools also serve as a valuable line of defence because they can be deployed network-wide. For merchants, this means that AI fraud detection tools can be on the lookout for new and existing threats across every checkout session, physical retail location, and buyer account. Once suspicious transactions are flagged, they can be referred to human teams for manual review. This frees up time and enables human fraud detection specialists to focus on the most urgent and probable instances of fraud.
Another benefit of AI is its capacity for self-improvement. Once deployed, live transaction data can be fed into an AI-based fraud detection system, which, over time, can reduce false positives and increase fraud detection accuracy.
For example, say you have an AI fraud solution configured to parse text. That tool can be fine-tuned against the language (or languages) in which a merchant does business. After analysing emails, live chat sessions, and other communications between merchants and sellers, the tool can then pick up on words or phrases commonly used in scams.
Finally, AI tools also have applications in identity verification. Merchants who invest in these tools may be able to reduce instances of account takeover fraud or identity theft. Beyond that, AI solutions can monitor and assign fraud risk scores to customer purchase behaviours and flag transactions that exceed historical average order volumes.
22.6% of surveyed merchants in the 2024 Chargeback Field Report say they are already deploying AI tools in the fight against fraud. Another 39.7% say they plan on using AI fraud-detection solutions in the future. But how exactly is the technology being used?
Scammers and AI tools are constantly evolving in an attempt to get ahead of each other. Let’s examine a few emerging threats and how AI tools can fight them.
How it works: Scammers who employ this tactic use a combination of data points pulled from different individuals to create new, synthetic identities. For example, they may use real data stolen from a customer’s social media profile to create a fake persona. They’ll use this fake person to acquire fraudulent lines of credit.
How AI tools can help: AI-enabled biometric identification systems, which use biological characteristics (like fingerprints, voice, or iris recognition) to verify and authenticate a buyer’s identity, can help reduce identity theft and root out synthetic data.
How it works: Fraudsters can use phishing emails, false promises, and other social engineering attacks to steal a cardholder’s personal information and gain unauthorised access to their account. Scammers may also obtain cardholder information from data breaches or use stolen login credentials to access other payment platforms.
How AI tools can help: Strengthening the login and checkout process using technologies like 3-D Secure 2.0, which blends multi-factor authentication measures with AI risk analysis, can help merchants mitigate the effects of account takeover fraud. 32.4% of merchants surveyed in the 2024 Chargeback Field Report say they currently use the 3-D Secure protocol to prevent chargebacks and reduce fraud.
How it works: Although mobile wallet and tap-to-pay methods are considered more secure than swiping or dipping a physical payment card, they’re not entirely immune from fraud. Scammers can launch malware attacks, engage in Wi-Fi snooping (packet sniffing), or create fraudulent lookalike sites to con victims out of their information.
How AI tools can help: After collecting information about a user’s plugins, operating system, and hardware, a merchant can create a “digital fingerprint” to track them. AI detection systems can then analyse data against this fingerprint to flag fraudsters who create and use multiple accounts on the same device.
How it works: Friendly fraud occurs when cardholders dispute valid transactions for invalid reasons, such as buyer’s remorse or false non-delivery claims. Additional 2024 Chargeback Field Report data reveals that the average merchant saw an 18% increase in friendly fraud incidents over the last three years.
How AI tools can help: Machine learning algorithms can use supervised, semi-supervised, ensemble, and unsupervised learning to identify trends in customer behaviour based on real-time transaction data and past purchase histories. Geolocation technologies can add another dimension to buyer behaviour and generate more data that AI tools can analyse to forecast chargeback risks.
AI tools can help merchants combat fraud at all stages of the purchase lifecycle. Monitoring customers across the account creation, checkout, and post-purchase stages can help sophisticated sellers ward off bad actors, whether those are third parties or cardholders themselves.
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