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Lynx Money Mule Account Detection
Identify illicit sources of funds and mule accounts in real-time to stop trillions of illicit funds flowing through the global financial system each year.
Lynx Product
Lynx Money Mule Account Detection
Dan Dica, CEO of Lynx Tech
“Stopping money mules doesn’t just matter for financial institutions; it matters for everyone. Money mules are a critical link in the chain of financial crime, as they facilitate the movement of illicit funds across the globe. By disrupting this flow, we not only protect countless victims but also cripple the operational capacity of criminal enterprises.”
Did you know?
- $3.1 trillion in illicit funds flowed through the global financial system.
- In the UK, fraud more than doubled to £2.3 billion in 2023.
- Most financial institutions struggle to identify inbound APP fraud.
Solution
Our Money Mule Detection solution is powered by advanced supervised machine learning algorithms, enabling a proactive approach to identify illicit funds and mule accounts in real-time.
Challenges Addressed
Financial institutions worldwide encounter a complex challenge in detecting and preventing money mule activities in real-time. Failure to promptly identify these illicit activities not only enables the unauthorized flow of funds but also leads to significant financial losses, alert fatigue, heightened operational costs, and potential regulatory repercussions.
The consequences of undetected money mule operations can reverberate with billions of dollars moving through FIs via illicit funds, posing a threat to financial stability and regulatory compliance.
How are fraudsters able to move illicit funds undetected through the banking system?
- Compromised Accounts (3rd Party fraud)
- Recruited Accounts (1st Party Fraud)
- Fake Accounts (New Account Fraud)
Stop more money mules – Prepare for October 2024 split reimbursement for authorized push payments.
According to Europol, more than 90% of money mule transactions are linked to cybercrime.
Benefits
Differentiators
Daily Adaptive Models
Daily adaptive models are the latest breakthrough in fraud prevention. Lynx’ Daily Adaptive Models (DAM) continually update by leveraging the latest genuine user behavior and fraud patterns. Self-learning profiles leverage genuine users’ connected devices, card and account transactions, beneficiary and incoming payments and geographic location of users. Real-time data enrichment, facilitated by Lynx’s in-memory database, enables swift and precise identification of fraudulent behavior and activities.
Differentiators
Lynx’ Daily Adaptive Models (DAM)
Money Mule Account Detection
Our models are built for real-time money mule account detection, illicit fund detection and fraud prevention.
Bespoke Models
The models are bespoke to the financial institution and use financial and non-financial data to learn genuine and criminal financial behavior.
Streamlined Calculation Process
They are architected to efficiently calculate tens of thousands of features and evaluate thousands of rules.
Optimized Language for Efficiency
We uphold strictcode discipline and develop in a language optimized for production.
Flexibly Adapt to New Data
Extensible data models with procedures to automatically generate new features and adapt to new data.
Refined Techniques
We have refined our techniques over two decades to train models that handle highly unbalanced datasets.
Tailored for Fraud
Our algorithms and libraries are specifically designed to address the problem of fraud.
Identify and stop transactions in real-time
Case study of a Financial Institution.
100 Ms
Identify and stop transactions in real-time
€ 7 Mn
Money mule problem every year
70 % VDR
Value of money mule transactions intercepted* (*Depending on the quality of data your results may be better or worse).
65 % ADR
Money mule account detection rate
10
Genuine transactions flagged out of 10,000* (*Depending on the quality of data your results may be better or worse).
Learn more about our Fraud solution
Market leading Artificial Intelligence to predict, detect, and prevent fraud across all channels.
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