Unmasking Illicit Financial Flows: The Role of Open-Source Intelligence
Illicit financial proceeds from criminal activities or evasive sanctions have the potential to stain every financial institution they touch. The failure of these organisations to identify and mitigate the risks posed by financial crimes can lead to severe penalties. In the UK, for example, the Financial Conduct Authority (FCA) fined Barclays £42m last year for poorly handling financial risks associated with two companies linked to money laundering and fraud. These criminal activities led to substantial prison sentences for four individuals involved in a £266m money-laundering operation.
Tackling money-laundering has become a global priority. In the United States, regulators imposed $1.1bn in anti-money-laundering (AML) and counter-terrorism finance penalties in 2021. In the same year, the US Financial Crimes Enforcement Network (FinCEN) imposed a staggering $1.3bn AML penalty on a single bank.
The Growing Threat of Money Laundering
Similarly, the UK faces a significant threat from money laundering. The National Crime Agency (NCA) suggests that over £100bn is laundered in the UK each year, including £12bn in cash. Last year, the number of prosecutions for money laundering offences in England and Wales increased by 36%, leading to 6,845 prosecutions and 3,756 convictions. Consequently, money laundering, along with international fraud, was among the nine primary concerns agreed upon by the UK’s NCA and FCA last year.
The task of investigating financial crimes is daunting. International criminal networks use encrypted channels, crypto-currency exchanges, social media platforms, and the deep and dark web to perpetrate their activities. The NCA estimates that about 70% of fraud committed against UK citizens or businesses originates abroad.
Spotting Suspicious Activity Amid Information Overload
Given the sheer volume of data that needs to be analysed and verified, most investigative and law enforcement agencies worldwide are in dire need of advanced tools. To successfully investigate platforms where criminals collaborate or target victims, these agencies require technology that can sift through the noise and provide focused insights from massive amounts of information.
These insights need to be quickly correlated with information from public databases, criminal and court records, commercial data sources, and other investigations. Given the volume of data, it’s unlikely that investigators will achieve significant results without adopting new approaches and leveraging advanced technology, such as AI-powered open-source intelligence (OSINT).
Crypto-Currency Investigations
Even in the opaque world of crypto-currencies, AI-powered OSINT can help investigators spot suspicious overlaps between crypto-currency activity and individuals’ digital footprints on social media. This offers crucial clues to illicit online activity. Crypto-currency exchanges, which are significant platforms for money-laundering, were slapped with $927m in fines for money-laundering infringements by the US government last year.
Financial Institutions and Advanced Intelligence
It’s not just law enforcement agencies that need OSINT technology. Banks face much stricter compliance and risk-management requirements from multiple regulations. These include the UK’s 2017 Money Laundering Regulations and the Economic Crime and Corporate Transparency Act of 2023. In the US, regulators like the US Treasury and FinCEN have clamped down on due diligence and have imposed unprecedented consent orders.
Helping Banks Identify AML Risks Better
For financial institutions conducting due diligence, uncovering connections between entities can be challenging. This is due to the tactics criminals use to disguise their identities in corporate registries and public records. However, if due diligence functions can access data from the surface, deep, and dark web and quickly correlate data across multiple sources to build a digital footprint, they can uncover a customer’s true risk profile.
With criminals keen on laundering their illicit money through financial institutions, there is an urgent need for these organisations to adopt more advanced techniques, including AI-powered OSINT, to ensure compliance and mitigate risk exposure.
In conclusion, with the power of generative AI and machine learning, an OSINT platform can sift through billions of data points and provide the necessary insights. AI-driven OSINT analysis has become indispensable for tracking down those involved in generating, hiding and laundering dirty money, thus protecting financial institutions and society at large.
Chad Longo, Financial Crime Compliance Director, Fivecast
Source: Here
