Fight AI with AI: Building a Resilient Merchant Risk Management Program Facilitates Growth
By Andy Vrabel, GM Payment Ecosystem Solutions at LegitScript
The rise of e-commerce and digital payments has revolutionized how businesses operate and consumers transact, enhancing convenience, accelerating transactions, and fueling business growth. However, as digital payments expand, so do the associated risks for the companies that facilitate these transactions.
What makes digital transactions so attractive to legitimate buyers and sellers is what also makes them perfect for fraudsters and merchants engaged in the sale of illicit products and services. These sellers want fast, easy, and anonymous ways to process payments for their criminal activity. While the payment processing industry has many safeguards to stop these bad actors, advancements in technology — specifically in artificial intelligence (AI) — is making this increasingly difficult.
Merchants engaged in fraud and illicit sales rely less on traditional tactics to circumvent underwriting and avoid detection; instead, they’re turning increasingly to advanced AI tools that can allow them to generate deepfake identities, automate fraudulent merchant applications, and make transaction laundering (a form of money laundering) harder to detect. This sophisticated AI technology presents significant challenges for payment processors and financial institutions facilitating online transactions. But it also presents the solution.
Modern risk management demands a proactive, AI-powered approach built on continuous merchant monitoring, real-time fraud detection, and a deep understanding of regulatory and compliance frameworks to protect transactions, maintain consumer trust, and enable sustainable growth. Innovative risk intelligence allows financial institutions and online platforms to strengthen merchant risk management programs and stay ahead of evolving threats.
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The Rise of AI-Driven Risk
The payments ecosystem is inherently complex, involving multiple stakeholders that play a role in managing risks, including payment processors, banks, e-commerce platforms, and regulatory bodies. Proper risk assessment requires payment companies to verify the legitimacy of a merchant’s business, evaluate their financial health, assess product and service offerings, and ensure compliance with applicable regulations. However, AI has fundamentally altered the threat landscape, making these assessments more difficult.
A recent Juniper Research study found that e-commerce fraud will increase by 141% by 2029, and AI is the key driver of this projected spike due to its widespread adoption, current regulatory gaps, and rapid advancements across the entire tech sector. This trend presents a growing challenge for financial institutions and payment service providers that must detect and prevent fraudulent activity before it results in significant financial and reputational losses.
Some of the most harmful methodologies AI facilitates are:
- Synthetic Identity Fraud – AI can enable fraudsters to generate convincing artificial identities by blending real and fabricated personal data. These identities are then used to establish fraudulent merchant accounts, often evading traditional verification methods.
- Transaction Laundering – To acquire a merchant account to process credit cards, problematic merchants will often pretend to sell innocuous products by creating a “front” website, but these websites are often sloppy and built off templates. AI-powered tools, however, can help bad actors quickly create highly custom front websites that are far more sophisticated and difficult for onboarding teams to detect.
- Deepfake Merchant Profiles – AI can generate deepfake images, videos, and audio recordings that impersonate real business owners or embody a fabricated identity. Fraudsters may be able use these tactics to bypass KYC (Know Your Customer) and KYB (Know Your Business) checks, spread misinformation, and manipulate regulatory compliance processes.
Strengthening Merchant Risk Management with AI
Failure to properly screen merchants or detect high-risk behaviors can have severe consequences. Payment processors that onboard merchants engaged in fraudulent activity risk regulatory penalties, card network fines, and reputational damage. Additionally, acquiring banks and payment facilitators that lack adequate oversight may find themselves liable for enabling illicit transactions.
Given the complexity of modern threats, 70% of financial institutions now report the need for third-party solutions, recognizing that internal fraud detection and compliance efforts alone are no longer sufficient. Legacy risk management models dependent on manual underwriting or outdated automation fail to address the scale and sophistication of AI-driven fraud. Effectively managing merchant risk involves selecting advanced AI-driven tools built for modern threat detection that provide comprehensive coverage, balancing speed, scale, and accuracy.
Financial institutions and payment companies must adopt AI-powered risk management strategies that provide real-time risk intelligence, automated merchant risk profiling, and continuous monitoring. Organizations that embrace these AI-driven capabilities will be best positioned to protect their businesses and thrive in an increasingly digital economy.
Merchant Onboarding: Establishing a Strong Foundation for Risk Management
Merchant onboarding is the most crucial step in mitigating risk within the payments ecosystem because it is the first checkpoint through which all prospective merchants must pass. While traditional underwriting and manual checks may have been sufficient in the past, these processes will prove too slow, outdated, and fragmented for today’s sophisticated bad actors. As fraudsters continue to evolve and incorporate AI, payment processors and other financial institutions must also embrace AI tools that ensure efficiency while accurately identifying and preventing high-risk merchants from entering the system.
Key components of an AI-powered onboarding process include:
- Enhanced Business Verification – Affirms merchants are selling what they claim by identifying discrepancies in product listings, pricing, and business credentials.
- Automated MCC (Merchant Category Code) Detection – Provides accurate MCC classification, identifies misclassified merchants, and flags any high-risk categories.
- Know Your Business (KYB) & Know Your Customer (KYC) Checks – Quickly verifies and analyzes business owners’ credentials and flag synthetic identities or high-risk applicants.
- Regulatory & Policy Compliance Assessments – Detects missing legal notices, non-compliant terms and conditions, and other policy violations that might expose payment processors to regulatory scrutiny.
AI-driven onboarding solutions should seamlessly integrate into existing workflows and scale effortlessly as businesses grow. By incorporating AI into the onboarding process, payment companies can reduce manual review times, improve accuracy, and build a secure payment space.
Continuous Merchant Monitoring: The Key to Long-Term Fraud Prevention
Merchant risk management doesn’t stop after onboarding. Even a thoroughly vetted merchant can later engage in illicit or brand-damaging activities, making continuous monitoring essential.
AI-powered risk intelligence solutions can enable ongoing scrutiny of merchant behavior, ensuring that sudden shifts in business models, changes in transactional patterns, or new regulatory violations don’t go unnoticed. Key elements of continuous monitoring include:
- Real-Time Content Monitoring – AI-powered crawling technology scans merchant websites for changes in product offerings, terms, and site ownership—identifying risks that manual reviews would miss.
- Behavioral Anomaly Detection – Machine learning models track transaction patterns, flagging unexpected spikes or irregularities that may signal fraud.
- Regulatory & Compliance Audits – AI-driven tools automatically check merchant websites against evolving regulatory requirements, reducing compliance gaps and minimizing enforcement risks.
Financial institutions and payment providers that establish ongoing risk detection will be able to better avoid costly fines and preserve consumer trust, ensuring that their merchant portfolios remain compliant and sustainable.
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A Safer Future in Digital Payments
As the payments landscape grows more complex and the e-commerce field continues to boom, having the right partner is essential for managing risk effectively. A trusted risk management partner should combine comprehensive data, advanced AI-driven technology, and industry expertise to detect fraud, reduce false positives, and ensure ongoing compliance. By combining AI-powered solutions with expert analysis, financial institutions and payment companies can better protect their platforms, assure compliance, and build a secure, transparent payments ecosystem designed for long-term success.
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