The CHALLENGE: Verifying and Authenticating Customer Information to Prevent Financial Crime
Global regulators fined financial institutions $26 billion for anti-money laundering (AML) and know your customer (KYC) violations between 2008 and 2018. Institutions in the U.S. account for 44% of those fines, and 91% of the total value $23.52 billion.
Costs related to AML/KYC compliance are equally illuminating, with approximately $25 billion spent annually by financial services firms. While that number is staggering on its own, data indicate that the smallest institutions are the hardest hit. Firms with $10 billion in total assets paid a total of $12.3 billion in AML costs and those with more than $10 billion in assets spent $13 billion.
Despite the large sums of money spent to stay compliant and avoid penalties and fines, firms still face significant challenges when it comes to verifying and authenticating customer information. Those charged with regulatory compliance cite politically exposed person (PEP) checks, negative news checks, watch list scans and increased search of public records as standard measures for mitigating AML risk. At the same time, they note the need for those reviews to be content-deep and rich and grounded in accurate and well-structured data. However, an astounding 67% reported that their primary means of gathering AML data was dialogue between a potential customer and an employee and 42% said they only reassess customer profiles on an as-needed basis.
With between $800 billion and $2 trillion laundered every year, finding new technologies and data sources to make AML/KYC compliance more efficient, more accurate and more actionable is critical.
Open Source Intelligence (OS-INT)
is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk.
OS-INT scours publicly available data across the entire Internet, correlating names entered into the system with content related to 20 different risk factors, known as Behavioral Affinity Models (BAMs), and cross-referenced with more than 1 million queries into Lumina’s proprietary databases of risk.
Searches provide near-instant results, delivering meaningful, actionable intelligence to identify and prevent risk.
Internet Intelligence’s (NET-INT)
proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.
The system also searches known IP addresses, producing all URLs accessed by the address. Results are nearly instantaneous, and accessed with just three clicks on the computer’s mouse.
The platform collects and stores more than 1 million interactions every day and since its inception has recorded more than 623,000 IP addresses engaged with threat-related risk topics.
Human Intelligence’s (HUM-INT) is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time.
THE SOLUTION: Making Customer Due Diligence More Substantive and Streamlined with AI
The open web is a powerful source for information related to PEP, negative news, watch lists, and public records. But with 2.5 quintillion bytes of data added to the web every day, financial institutions need technology that can ingest, filter, and prioritize massive amounts of data. Radiance is designed for that purpose.
OS-INT’s financial services BAMs include more than 275 terms. The platform conducts more than 5,500 searches across all publicly available data on the web, correlating names with these terms and cross-referencing over 1 million queries into Lumina’s proprietary databases of risk. OS-INT pulls all applicable content into a comprehensive report. The results are prioritized, making it easy to further analyze the findings and determine potential risk. A manual web search of this magnitude would take one person more than 5 months to complete.
NET-INT monitors IP address behavior across 43 pre-categorized behaviors accessing content related to risk dimensions associated with money laundering and other financial crimes. NET-INT also screens IP address associated with an entity or person of interest against all IP addresses displaying anomalous behavior collected over the lifespan of the system. NET-INT identifies geographic areas where anomalous online behavior is originating. NET-INT also screens IP address associated with an entity or person can provide real-time insight on what the individual or institution is researching and what data streams are informing their actions.
HUM-INT, or S4 app can be configured as a workplace tool, allowing employees to submit information related to potential areas of concern. A centralized management portal allows clients to access real-time threats to geo-fenced facility locations.
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Lumina was founded on the idea that technology is a force for good. We optimized our artificial intelligence capabilities to help keep people and places safe and secure. Protecting what matters most is more than what we do. It’s who we are.
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