How Big Data Is Changing Anti Money Laundering

Today, the average person generates 1.7 megabytes of data in just one second.¹ Between 2010 and 2020, the total amount of data created and consumed globally grew by over 3000%.² This proliferation has driven significant shifts in the ways data is interpreted and used across industries. For financial institutions, the growth in big data has the potential to change the face of anti-money laundering (AML) investigations and best practices. 

A great example of this is the use of publicly available data, otherwise known as open source intelligence (OSINT), to identify insights and connections that would otherwise be easily missed. This intelligence-led approach can increase the effectiveness, consistency and transparency of AML compliance processes; especially important as regulators worldwide are putting pressure on FIs to get tougher on financial crime. 

In this article, we’re going to look at the ramifications that using big data can have for financial institutions, and what that means for AML processes moving forward. 

Suggested reading: For more information on how intelligence is transforming AFC, check out our report — Open Source Intelligence: Transforming Financial Crime Investigations

What does an intelligence-led shift actually mean?

The value of expansive, readily available data sources is self-evident, but with huge volumes of data siloed across any number of sources, big data in its raw form is more likely to derail investigations than drive actionable outcomes. 

The volume and spread of open source data has been a catalyst for the development of intelligence techniques now shaping modern investigation best practices.  And, as the importance of data increases, it is playing a key role in effective AML processes.³

Open source intelligence is the end result of open source data (OSD) – news articles and company records for example – being collected, analysed and turned into practical insights for decision makers. Originally developed to source intelligence from news outlets worldwide during the second world war, OSINT has long been used in government and military disciplines.⁴

In the context of anti-financial crime investigations, OSINT can be used to identify connections within complex datasets, generate additional insights and make better risk decisions. An intelligence-led shift is not just about the data, but the ability to turn data into actionable intelligence.

And the shift to an intelligence-led approach can bring particular value to AML investigations because it enables banks to— 

• Target data collection and analysis
• Identify hard-to-spot connections
• Increase investigation efficiency whilst improving outcomes 

This is made possible by AML software that not only collects data across sources, but helps the investigator to identify and analyse the information that is relevant to achieving their objectives. While technologies like machine learning and artificial intelligence can play a part, for example by simplifying advanced analytics, humans are left to make decisions that require expert, nuanced judgements. The Intelligence-led approach is therefore largely reliant on the ability of professional investigators to access and make sense of all of the information they need during an investigation.

Why open source data is a critical part of evolving best practices

Its ability to enhance sensitive, network-centric investigations is the prime reason why OSD usage is popular amongst government and military agencies. Ths benefit can translate directly to the financial sector where investigators can leverage sources such as corporate records data, search engine results and social media to inform AML investigations. 

Open Source Intelligence can provide greater accuracy and context to help analysts get into the minds of increasingly intelligent risk actors. OSINT solutions help investigators put that information to good use with benefits such as — 

• Ability to quickly filter and categorise large volumes of information
• Enterprise-wide secure, anonymous, and ethical investigations
• Enhanced capacity to meet regulatory and compliance regulations
• The opportunity to transform investigatory best practices and disrupt financial crime

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Pro tip: While AML compliance can be enhanced by publicly available information, the poorly thought-through or indiscriminate hoarding of OSD compromises long-standing compliance regulations like GDPR. The future of financial best practices relies on the ability to access only data aimed at targeted investigation outcomes, which is where technology can help.

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Using data to drive outcomes in AML

Marrying big data technologies with AML compliance processes helps financial institutions to stay abreast of new requirements. OSINT tools can transform AML processes in a number of ways — 

• Customer due diligence (CDD): OSINT tools allow the investigator to cross-check customer information across external sources and increase understanding of customer risk by both verifying identity, and checking for associated risk. This is fundamental for ensuring compliance with anti-money laundering regulations.
• In-depth money laundering investigations: OSINT investigations allow AML officers to investigate complex cases more thoroughly, rather than rely on search engine results alone. Using OSINT in combination with internal data allows the investigator to collect and analyse the maximum possible relevant information, discover key insights more easily and make better judgements about potentially suspicious activity.  

By automating the manual processes that shouldn’t require human judgment, the investigator has more time to think about the processes that do require their input. What’s more, sophisticated OSINT tools leave less room for risk or non-compliance, allowing financial institutions to spend less time on manual investigation and more time on implementing AML best practices. 

The importance of using the right solution

OSD and big data can create as many issues as they solve, leaving companies not only drowning in unusable insights, but also at risk of failure to comply. OSINT tools can be a life raft, but indiscriminate automation and overly complex technologies can present a barrier to investigative insight . This means that choosing the right AFC tech can be daunting. 

Financial institutions need sophisticated solutions that drive rather than derail investigations with secure, and outcome-driven focuses. We at Blackdot have created a solution to do just that: Videris, an intelligent automation platform that offers these benefits — 

A focus on outcomes

• Intelligent automation: IA simplifies the investigative process by automating key activities such as risk-flagging, categorisation, and corporate network mapping that inform human-led, outcome focused, results.
• Targeted data collection: The ability to target data collection using Videris search and cross-matching capabilities minimises the data handled overall, thus making the process highly efficient, effective and ethical.

Security, transparency and visibility

• Single platform: Videris provides data collection, analysis and reporting at the click of a button ensuring complete oversight of the entire investigation.
• Customisable, secure access: The ability to set permissions makes sure that the right people always have access to the information that they need to drive decisions. At the same time, data collection is kept entirely secure and anonymous to ensure that the subject of the investigation is not ‘tipped off’.

Guaranteed ROI

• Relevant data: The ability to access relevant information across sources with a single click using Videris search and network mapping ensures that time and resources are spent on producing actionable intelligence that gives results.
• Broader use cases: As well as driving AML outcomes, Videris can help to inform further investigatory practices where OSINT is valuable, whether that be insider trading, terrorist financing, or beyond.
• Reduce risk of financial and personal penalties: With OSINT you’re less likely to miss key information that was in the public eye, making you less susceptible to regulatory penalties and reputational damage.

These features offer OSINT insights that transform, rather than complicate, AML best practices even as risks evolve. To see them in action, contact us to discuss how Videris is already shaping the future of AML, and to see precisely what part it can play in your investigation moving forward.

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1. 27+ Big Data Statistics – How Big It Actually Is in 2021?
2. Total Data Volume Worldwide from 2010 – 2025
3. A Brief History of Open Source Intelligence – bellingcat
4. A Brief History of Open Source Intelligence – bellingcat