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 

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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.

EMPOWER REAL-TIME SCORING 

Evaluate all transactions, incoming and outgoing in real time.

ENHANCE YOUR PROTECTION OPTIONS 

Available as a standalone scoring solution. Enhance with the full Fraud Prevention solution (Scoring, Rules, Alerts, Reports, Dashboards).

Reduce Financial Losses

Stop illicit funds incoming and leaving the FI.

Manage Operational Costs

Reduce false positives and uncover money mules faster. ​

Increase Compliance

Increased money mule detection accuracy and speed to better meet regulatory requirements such as the contingency reimbursement model.

OPTIMIZE WITH DAILY DYNAMIC DAILY ADAPTIVE MODEL

Our solution utilizes the proprietary Daily Adaptive Model. These dynamic models continuously update based on the latest financial behaviors, ensuring precise identification of both genuine users and criminals. The ongoing updates maintain the highest level of accuracy while significantly reducing false positives and the associated costs.

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 Authorised push payments.

 

According to Europol, more than 90% of money mule transactions are linked to cybercrime.

 

Benefits

Identify money mules in real time

Immediately identify incoming illicit funds.

Significantly reduce losses

Stop Authorized Push Payment Fraud (APPF) incoming and exiting the financial institution.

Stay ahead with a proactive defense

Stay ahead with a proactive defense against evolving tactics.​ ​

Mitigate alert fatigue

Mitigate alert fatigue by providing more accurate alerts, allowing analysts to focus on genuine threats.​

Reduce recovery costs

Reduce recovery costs associated with incidents, improving overall operational efficiency.​

LYNX ENABLES ANALYSTS

Real time alerting on mule accounts reduces alert fatigue and provides a 360 view enabling faster decision making.

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)

01

Money Mule Account Detection

Our models are built for real-time money mule account detection, illicit fund detection and fraud prevention.

02

Bespoke models

The models are bespoke to the financial institution and use financial and non-financial data to learn genuine and criminal financial behavior.

03

Streamlined calculation process

They are architected to efficiently calculate tens of thousands of features and evaluate thousands of rules.

04

Optimized language for efficiency

We uphold strictcode discipline and develop in a language optimized for production.  

05

Flexibly adapt to new data

Extensible data models with procedures to automatically generate new features and adapt to new data. ​

06

Refined techniques

We have refined our techniques over two decades to train models that handle highly unbalanced datasets.

07

Tailored for Fraud

Our algorithms and libraries are specifically designed to address the problem of fraud.

01

Money Mule Account Detection

Our models are built for real-time money mule account detection, illicit fund detection and fraud prevention.

02

Bespoke models

The models are bespoke to the financial institution and use financial and non-financial data to learn genuine and criminal financial behavior.

03

Streamlined calculation process

They are architected to efficiently calculate tens of thousands of features and evaluate thousands of rules.

04

Optimized language for efficiency

We uphold strictcode discipline and develop in a language optimized for production.  

05

Flexibly adapt to new data

Extensible data models with procedures to automatically generate new features and adapt to new data. ​

06

Refined techniques

We have refined our techniques over two decades to train models that handle highly unbalanced datasets.

07

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. (*Depending on the quality of data your results may be better or worse).

Lynx in Numbers

01

<0Ms

Identify and stop transactions in real time.

Lynx in Numbers

02

0Mn

Money mule problem every year

Lynx in Numbers

03

0% VDR

Value of money mule transactions intercepted*

Lynx in Numbers

04

0% ADR

Money mule account detection rate

Lynx in Numbers

05

0

Genuine transactions flagged out of 10,000*

Next Steps

Take the first step towards safeguarding your institution from financial crimes.

Proof of Concept

Let the numbers speak


Work with Lynx to uncover fraud in your portfolio.

Understand the fraud and false positive reduction possible with a fast POC.

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Find out how much you could save


Schedule a proof of concept (POC) to discover potential cost savings and unearth undetected mule accounts within your company.

Let’s work together to disrupt the operations of criminal enterprises and safeguard the future of the financial industry.

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