How AI can help your AML get unstuck in 2023

December 28, 2022
The uphill battle against money laundering and financial crime in 2022 was marked by progress in some areas but offset by a mountain of new challenges.  In fact, progress in AML programs appears to be “stuck,” according to the Basel AML Index which ranks money laundering and terrorist financing risks around the world.  The 2022 report concluded that any real progress is being impeded by increased risks. No doubt these trends will continue to impact anti-money laundering efforts in 2023, as most countries continue to be too many steps behind criminals seeking to launder illicit funds.   The following are some of the negative headwinds that are weighing on compliance programs. Sanctions screening pressure Sanctions lists saw a 95% jump in updates in the first half of 2022 due to the Russia-Ukraine war.  This has caused a massive impact on compliance programs now faced with a higher stack of alerts, pressure on list updating processes, and burdensome alert remediation.  Real-time sanctions screening is a regulatory requirement and a major point of friction in the world of instant payments. Sanctions screening quickly turns into a bottleneck for financial institutions as surgical precision is required while matching a variety of imperfect and unstructured payment data against sanctions lists. Crypto is still a heyday for financial crime  Financial criminals continued to flow to cryptocurrency and other virtual assets in 2022 to innovative methods of money laundering. The Basel report called the AML risks from virtual assets “worrisome” with compliance oversight dropping dramatically. In one case that was uncovered last month, two Estonian citizens were arrested in a $575 million cryptocurrency fraud and money laundering scheme. Data breaches   Digital authentication hazards continue to challenge the financial system, as face-to-face identification is no longer a requirement to open a digital or mobile bank account. Criminal sophistication continues to cause data breaches and identity theft, where information can end up in money-laundering schemes.  The ease of opening bank accounts and the surge in the number of financial ecosystem players complicate the ability of the financial ecosystem to detect the true identities of the people and the activity behind them. Major data-compromising incidents and new patterns were recorded globally in 2022. In South Africa, credit bureau TransUnion SA suffered a cyberattack that saw data stolen from around three million customers by a criminal third party. In South Korea, researchers identified a new “fake calls” banking trojan. The bot has the ability to “talk” to victims and pretend to be an employee of the bank in order to gather personal information.  In the United States, 2.5 million social security numbers were stolen in a student loan data breach at Nelnet Servicing. In positive developments, measures are being taken to improve AML/CFT capabilities. Banks and fintech are continuing to adopt new AML solutions powered by advanced AI technology to get out of the rut. Indeed, according to the Basel report, the highest level of progress was achieved with the involvement of the private sector. Here are areas where AML is

Riding through the sanctions storm with AI

December 21, 2022
Compliance professionals have surely had a very stressful year in 2022 with the extra burden of transaction screening work, amid a 95% jump in sanctions list updates due to the Russia-Ukraine war. This regulatory pressure is not expected to fade away in 2023 with new sanctions packages being approved and sanctions evasion set to become a crime in the EU as the bloc continues to seek ways to punish Russia over its war in Ukraine. Real-time sanctions screening is a regulatory requirement and a major point of friction in the world of instant payments. Fintechs, whose mission is to deliver a better customer experience, speed, and reduce friction, are discovering that sanctions screening quickly turns into a bottleneck for their fast-growing business. The increasing complexity of screening The complexity of sanctions screening is not only caused by the volume or frequency of the updates of different uncoordinated regulatory bodies. It is also the story of the surgical precision required while matching a variety of imperfect and unstructured payment data against sanctions lists. Regulators expect more than perfect/exact matches, increasing expectations each year for sanctions screening frameworks. As a result, screening software is relied on to analyze misspellings, different alphabets, transliterations, and, more recently, geographical challenges to effectively match real-time transactions. Recent fines leveraged against fintechs highlight an urgent need to ramp up their sanctions screening game. Choose your perfect match Choosing a sanctions screening solution in this stormy journey is key. Surprisingly, there are not so many screening solutions providers with good technology tailored to fintech needs that provide good value for money as well as company culture fit. Legacy systems trigger large volumes of false positive alerts, often more than 95%. While balancing risk and cost, the goal is to cover all possible risks. However, fintech will incur high costs with the need to review false hits that could be like 297/300, all while slowing down business. In addition, incumbent legacy providers often do not have customer-centricity in their DNA while having prohibitive prices adapted to the compliance budgets in the banking sector. Those drivers make fintech consider a more sophisticated, cloud-native AI-based technology that is better equipped to overcome challenges for both sanctions screening and transaction monitoring. Rule-based solutions are no longer a good option for sanctions risk protection or for fintech pockets. Here are the key factors to take into consideration while choosing a screening solution: 1. Speed and infinite scalability The hectic rhythm of real-time transaction screening requires a smart architectural fit and unrivaled performance. Your tool should adapt to your scaling business in the same way it adapts to the changing sanctions risks and regulatory requirements. An AI-based solution with machine learning algorithms in the screening engine delivers extreme precision and speed in the process. It also filters out the noise that triggers false alerts. In this way, AI can replace the time-consuming work of investigators to spot true alerts and focus on real risks. 2. Magic three “E”: efficient, effective, explainable AI enables FIs

Harness the Gulf economic boom with AI technology

December 7, 2022
The Middle East, at a crossroads between Europe, Africa, and Asia, is playing an increasingly global role on the financial scene. Today, the United Arab Emirates (UAE) serves as a financial hub in the region, with commerce, banks, and fintech operating out of Abu Dhabi and Dubai. UAE fintech is also leading in the region, with a market value of $ 2.5 billion in 2022, according to figures from the UAE Ministry of Economy. The UAE is also a major player in the remittance market with about 90 percent of the country’s total population foreign workers or expats. Amid this boom, the UAE financial community was hit with a blow in February 2022, when the country was placed on the “grey list” of the Financial Action Task Force (FATF), the global anti-money laundering watchdog, for countries in need of “increased monitoring” of their AML/CFT regime. The deterioration to the grey list highlights the vulnerability of the UAE as a corridor for illicit transactions and sanctions evasions, notably with several other neighbors on the grey list (Jordan, Turkey, Syria, Yemen) and even blacklisted (like Iran). These issues are undoubtedly a concern for other neighbors as well such as Saudi Arabia and Bahrain. On the bright side, countries on the list actively work with the FATF to address strategic deficiencies in their system to fight money laundering, terrorist financing, and other financial crimes. Indeed, the UAE has made a high-level commitment to work with the FATF to strengthen the effectiveness of its AML/CFT system and resolve the identified strategic deficiencies within agreed timeframes under tighter supervision. The FAFT is expecting an improvement in areas such as the number and quality of STRs; greater use of financial intelligence to pursue high-risk ML threats; and proactively identifying and combating sanctions evasion, including by demonstrating a better understanding of sanctions evasion. As part of this effort, the UAE is also proposing to establish a national committee to allow sharing of strategic information and intelligence between the public and private sectors on suspected money laundering and terrorist financing activities, as well as develop best practices to fight financial crime. On a recent visit to the region, I met with new customers and prospects to discuss how to use AI technology as a tool to help solve their AML challenges and better position them to transform into significant players in the regional and global financial market and growing fintech ecosystem. Here are my impressions on how Middle East and North Africa FIs can benefit from adopting AI: Enable trust. Middle East banks and fintech are looking to grow business and boost connectivity to the global financial system. As noted, they are faced with unique challenges due to their relative proximity to risky areas, exposing them to manipulation by sanctioned entities and terrorist groups using front non-listed entities. By adopting AI-based solutions they are going to be better positioned to deliver effective and efficient AML programs. Using AI, true criminal financial activity can be detected in a timely

See the big picture in the AML details

October 25, 2022
Embrace network visualization tools for more effective AML compliance in an increasingly complex financial world By Dagan Osovlansky, ThetaRay Chief Product Officer Fintechs and banks are struggling today to operate effective and efficient anti-money laundering (AML) and combating the financing of terrorism (CFT) programs, especially with the complexity of cross-border payments driven by new online platforms.  As digital payment velocity increases, AML compliance managers are exposed to enormous volumes of data.   To unravel complexity, big data analytics are becoming more essential for tracking money-laundering activities. Bad actors continuously develop new modus operandi, changing criminal schemes faster than investigators can get on the trail of crime. Indeed, today, the FATF is promoting the use of technology to implement a risk-based approach that can improve AML/CFT efforts. Specifically, according to the FATF, artificial intelligence-based tools can analyze data accurately and help better identify emerging risks. [add source]. Moreover, according to the FATF, technology has the potential to make efforts to combat money laundering and terrorist financing (AML/CFT) faster, cheaper, and more efficient. Big data tools are also evolving alongside sophisticated machine learning.  Technology can increase the capacity to collect and process data, and share it with stakeholders, including supervisors, notes the FATF. Data visualization provides a powerful tool for AML professionals to gain insights to be able to effectively analyze and communicate data. Here are some benefits of visualization tools for AI-powered AML transaction monitoring: Maximize the power of AI-generated data. AI-powered technology for AML, especially “unsupervised” machine learning, learns the financial behavior of each customer, builds “normal” profiles, and detects unusual cases. In this way, hidden risks and “unknown unknown” typologies can be uncovered within the data. When the AI-processed data is analyzed and then visualized, the dots are connected, and discoveries are enriched, shedding new light onto abnormalities and enabling uncovering of new typologies in an increasingly complex financial world. See the big picture. Visualizations are more intuitive than text alone, and can therefore help provide context for red flags. Additionally, visualization can expose “hidden” suspicious patterns that cannot be revealed by alerts and/or transaction tabular representation. Using a visually mapping out financial network, AML compliance teams can thereby more easily explore relationships among different players, opening up the layers and revealing the source of activity from one to the next. Enriching customer data with visualization helps deliver more accurate risk assessments, better decision-making, and fewer instances of false alerts. Speed investigations. The big picture enables faster and smarter decisions. Having network visualization as part of a machine learning ecosystem improves the investigation process, enabling faster investigations through clear and intuitive visualization of activity on financial networks. Layers of the data behind alerts can be presented and analyzed graphically, including recipient names, the volume of transactions, payment timeline, aggregation of currencies, transaction direction, and country of origin. When transactions can be easily and clearly viewed transactions across the networks, analysts and supervisors can see hundreds and thousands of transactions at one glance including interconnectivity with other entities.  As a result, significant time and operating

What is Trade-Based Money Laundering?

September 19, 2022
    The mounting challenge of trade for AML compliance  Trade financing is a big business for banks, with letters of credit and an important revenue stream. For the developing world, global trade is key to economic growth. The global trade finance market, with an estimated value of $5.2 trillion, facilitates the cross-border movement of goods and services around the world. It includes buyers and suppliers of all sizes, with financial institutions providing the liquidity and the risk assessment necessary to execute trade transactions.  At the same time, the Financial Action Task Force (FATF), a global financial crime watchdog, has identified trade as one of most worrisome methods by which criminal organizations and terrorist financiers move large amounts of money while disguising origins and integrating the funds into financial systems.  A growing global problem in the past several years, international trade attracts bad actors and terrorists aiming to exploit legitimate types of activities while manipulating and misrepresenting the quality, value, and or quantity of imports and exports. Indeed, trade-based money laundering (TBML) is one of the most sophisticated methods of “cleaning” dirty money, notably for narcotics traffickers and terror organizations. Due to the complexity of trade finance and global shipping logistics, money-laundering red flags are usually manyfold and also among the hardest to detect. While the scope of money laundered through the international trade system is also unknown, as estimates range vastly from hundreds of billions to trillions of dollars per year.    As a result, many banks often choose to de-risk or limit activity, meaning businesses and economies lose access to global trade.  To help address the challenges of detecting trade-based money laundering, the FATF has asked financial institutions to redouble efforts and reassess controls to ensure they are using the right tools in combatting TBML. In March 2021, a new guidance issued specific guidelines for trade-based money-laundering risk factors. Adopting a risk-based approach  Classic money-laundering flags used in a rules-based approach, such as threshold values and high-risk jurisdictions, are simply too general for the complexity of global trade where so many factors are involved in the transaction.    The FATF highlighted a host of risk indicators that can point to TBML in the guidance. The multitude of risks is grouped as follows: Structural risk indicators such as high-risk jurisdictions, suspected use of shell companies, a lack of public information or corporate offices, little or no business activity, and criminal records.  Trade activity risk indicators include a discrepancy between the line of business and the trade activity, use of many intermediaries, abnormal shipping routes, unconventional use of letters of credit, importing wholesale commodities at or above retail value unreasonably low-profit margins, a newly formed or recently re-activated trade entity engage in high-volume and high-value trade activity.  Trade document and commodity risk indicators for example inconsistencies across contracts, invoices, or other trade documents or prices that do not seem to be in line with commercial considerations. For example, when the value of registered imports of an entity displays significant mismatches to the entity’s

ThetaRay AI Tech to Monitor African Payments for ARCA  

September 8, 2022
Nigerian fintech selects SONAR SaaS solution for AML and sanctions screening to create new revenue opportunities and boost customer service. ThetaRay, a leading provider of AI-powered transaction monitoring technology, today announced that ARCA, a premier African payment services provider, will implement ThetaRay’s advanced SONAR SaaS anti-money laundering (AML) and sanctions list screening solution for transactions on its open AI-based platform. ARCA is the first Nigerian fintech to adopt ThetaRay’s advanced SONAR solution, industry renowned for its ability to detect the very first signs of sophisticated financial crime. ARCA provides advanced digital payments for an open banking ecosystem, helping expand innovative and inclusive financial services throughout Africa. “Our mission is to provide feature-rich financial solutions delivered through an open and flexible digital platform, through the use of cutting-edge technologies,” said Alex Umeh, Chief Information Security Officer at ARCA. “ThetaRay’s SONAR is a perfect fit. Its advanced machine learning and algorithms can instantly spot any attempts to launder money or circumvent sanctions, no matter how sophisticated. This will help us to create new lines of revenue, better serve our customers, and continue to remain compliant with regulatory requirements.” “Instant payments have become the new norm in the digital ecosystem, and ARCA is a leader in driving this revolution in the African financial system,” said Mark Gazit, CEO of ThetaRay. “ARCA prioritizes trust, confidence, and quality. We are thrilled to build this partnership and help facilitate both the growth of their business and expansion of the world economy by enabling financial inclusion.” SONAR is based on an advanced form of AI that makes better decisions with no bias or thresholds. It enables fintechs and banks to implement a risk-based approach to effectively identify truly suspicious activity and create a full picture of customer identities, including across complex, cross-border transaction paths. This enables the rapid discovery of both known and unknown money laundering threats, with a 99% reduction in false positives compared to rules-based solutions. About ARCA ARCA was founded in 2016 with a clear vision to become Africa’s premier payment services platform, fostering financial inclusion and innovation, and actively shaping the future of financial services throughout the region. The ARCA system empowers banks, financial institutions, developers & SMEs to seamlessly connect and create solutions for their customers. Learn more at About ThetaRay ThetaRay’s AI-powered SONAR transaction monitoring solution, based on “artificial intelligence intuition,” allows banks and fintechs to expand their business opportunities and grow revenues through trusted and reliable cross-border payments. The groundbreaking solution also improves customer satisfaction, reduces compliance costs, and increases risk coverage.  ThetaRay’s technology is the only SaaS offering that analyzes SWIFT traffic, risk indicators and client/payer/payee data to detect anomalies indicating money laundering activity across complex, cross-border transaction paths in a single unified platform. Financial organizations that rely on highly heterogeneous and complex ecosystems benefit greatly from ThetaRay’s unmatchable low false positive and high detection rates. Learn more at Itweb: Africa business communities:   Linkedin