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
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—
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.
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 —
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.
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 —
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.
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 —
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.