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How Fraudsters Are Advancing Money Laundering Tactics? How FIs or individuals can safeguard themselves?

Madhu Srinivas

Money laundering is now faster, more sophisticated, and deeply embedded in the digital ecosystem. As financial systems modernise, criminals are exploiting new vulnerabilities with tactics far beyond traditional shell companies and offshore accounts. According to media reports, over 1.9 million mule accounts have been identified in India, helping prevent fraudulent transactions worth ₹2,038 crore. Despite this progress, both financial institutions and individuals must remain vigilant to effectively combat such frauds.

Today, illicit funds are being laundered through a range of tactics, including rent-a-bank-account scams, synthetic identity accounts, sleeper mule accounts, often involving everyday people who may unknowingly become part of the crime. To stay ahead of these threats, it’s essential for both financial institutions and consumers to understand how such schemes work, where traditional safeguards fall short, and how emerging technologies like Artificial Intelligence (AI) can play a transformative role in detection and prevention.

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The Evolving Tactics of Money Laundering

Emerging trends include:

  • Rent-a-Bank-Account Scams:

One such emerging trend is the ‘rent-a-bank-account’ scam, where criminals convince individuals to allow third-party access to their bank accounts often under the promise of quick financial gain.

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These accounts are then used to receive stolen funds or facilitate fake transactions, with the money quickly withdrawn or transferred, making it difficult to trace. This method significantly contributes to the increase in money mule fraud, enabling broader illegal financial activities such as money laundering.

  • Synthetic Identity Accounts

Synthetic identity accounts are created using a mix of real and fake identity elements such as a genuine PAN or Aadhaar number paired with a fabricated name, photo, or address. This blend allows fraudsters to bypass basic KYC checks and open accounts that appear legitimate but are untraceable. These accounts are commonly used in organized financial crimes and identity theft-driven money laundering, enabling bad actors to operate under the radar while exploiting gaps in the verification process.

  • Sleeper Mule Accounts

Sleeper mule accounts are bank accounts that are deliberately kept inactive for extended periods after being opened often using fake or manipulated documents. Fraudsters activate these accounts suddenly to conduct high-value or rapid transactions, making detection harder due to their previously dormant status. This tactic helps them avoid raising red flags in banking systems. Such accounts are commonly used in investment scams and telecom frauds, where timing and anonymity are critical to moving illicit funds swiftly.

The Systemic Gap in AML Defenses

One of the biggest weaknesses in today’s anti-money laundering (AML) framework is the disconnect between customer onboarding and transaction monitoring.

Many banks treat these as separate systems: onboarding uses KYC, credit bureau, and sometimes social media checks to profile customers, while transaction monitoring operates independently, flagging suspicious activities. Without linking these systems, banks miss obvious red flags.

For example, if a customer with a low-income profile suddenly begins high-volume third-party transactions, the lack of integration means the transaction system may not flag this as suspicious.

Creating dynamic risk profiles helps continuously compare real-time behaviour against the original customer profile, and banks can detect anomalies, flag mule accounts, and prevent financial crimes before they escalate.

How Financial Institutions Can Stay Ahead

AI-driven solutions are revolutionizing fraud detection by enabling real-time risk monitoring through analysis of device fingerprints, login locations, and transaction patterns dramatically reducing false positives. Dynamic customer risk profiling combines onboarding data with behavioural trends to identify deviations and trigger timely alerts. Graph analytics helps uncover hidden mule account networks linked via common IPs or devices. Real-time decisioning allows banks to pause or block suspicious transactions instantly. Cross-channel fraud intelligence tracks activity across UPI, wallets, credit cards, and accounts. Additionally, partnering with RegTech firms and sharing anonymized insights boosts collective detection and response capabilities.

Also Read: India’s Trillion-Dollar opportunity in Insurance & InsurTech sector

How Individuals Can Protect Themselves

Fraudsters often exploit everyday individuals knowingly or unknowingly to move illicit funds, making it crucial for citizens to stay vigilant. Mule accounts can entangle unsuspecting people in cyber scams and expose them to serious legal consequences. To protect yourself, never share your bank account details or credentials, even if offered passive income or freelance work. Avoid job offers or schemes involving payment processing on behalf of others. Be wary of investment opportunities that require receiving or routing money, especially in crypto or forex. Always use verified financial platforms and report any suspicious activity to your bank or local cybercrime authority immediately.

As financial fraud becomes more sophisticated, tackling mule-driven laundering demands a united front. Financial institutions must break down silos between onboarding and monitoring, adopt AI-driven tools for real-time detection, and collaborate to share fraud intelligence.

At the same time, individuals must stay alert to manipulation tactics that turn them into unknowing accomplices. By combining smart technology, regulatory vigilance, and public awareness, we can build a financial system resilient against tomorrow’s threats.

Views Expresses by: Mr. Madhu Srinivas, Chief Risk & Compliance Officer, Signzy

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