Anti-fraud product & Anti-money laundering product of the year – BlackSwan Technologies’ ELEMENT™ of Compliance

Even before the pandemic, artificial intelligence (AI) was delivering noteworthy results in financial services. After a year of lockdowns, market shocks and recovery, AI is an even bigger trend.

BlackSwan Technologies has taken a forward-thinking approach to compliance that blends current regulatory and operational needs with leading-edge anomaly detection, predictive analytics and new insight generation at the heart of today’s innovation trends. Its ELEMENT™ of Compliance application represents cloud-based, ‘enterprise software 4.0’, with composite AI technologies at its core. The result is a solution tailored specifically for large financial institutions’ sophisticated risk and compliance functions, which delivers substantial gains in insight accuracy, staff productivity, speed and flexibility of implementation, and cost-savings.

ELEMENT of Compliance is an end-to-end, business solution for anti-money laundering (AML), anti-fraud, know your customer and automated client lifecycle management (CLM). However, the characteristics that first caught the attention of Risk.net’s award judges centered on its underlying AI-powered platform, known simply as ELEMENT™. BlackSwan considers this platform as a service to be the “first business-level, enterprise-wide AI operating system”.

Multiple AI technologies are embedded in ELEMENT, including knowledge graphs, machine learning, deep learning, a rules engine, natural language processing and contextual analytics. Analyst firm Gartner refers to this as “composite AI” and has placed BlackSwan in its emerging leaders’ category. Composite AI enables human-like decision-making and greater analytic transparency to add value to employees’ roles. For example, BlackSwan’s AI algorithms ingest millions of data points about an entity and categorise the significance of each piece of data it collects in terms of fraud or AML sensitivity. Composite AI goes beyond simple keyword tagging by employing semantic natural language processing to interpret each source of data and then extracting the relevant entities and context in a way that mimics analyst review and yet is completed in seconds.

BlackSwan’s AI-based approach is founded upon a semi-autonomous Knowledge Graph, which scans vast repositories of data within an enterprise, an array of global compliance databases, and thousands of public sources like social media and industry news, to build a holistic representation of relevant entities and relationships between these entities. (Departments can manually add to or modify the graph, or create their own view). The relationships’ representation means the system is sensitive to the activities of customers, their business associates and even secondary organisations’ associates.

Regulators expect financial institutions to examine all data available: unstructured documents, web-based resources, news outlets and open sources to inform their judgements on transaction monitoring for suspicious behaviour. Accessing this large and diverse set of data sources requires a new data management design. To this end, ELEMENT rests on a ‘data mesh’ framework, which catalogs both structured and unstructured data, and accesses the latest data points directly from the original source. The data mesh, plus the knowledge graph, create an always up-to-date, single source of truth with context.

BlackSwan’s Knowledge Graph captures a financial institution’s universe of concepts, parties, relationships and behaviours that impact risk and compliance

BlackSwan Technologies

ELEMENT of Compliance builds on this technology foundation to provide a comprehensive set of business features that support AML and anti-fraud compliance from end-to-end. Key feature areas include: know your customer (KYC), perpetual (continuous) KYC, transaction monitoring, transaction intelligence, name and watchlist screening and adverse media monitoring. These functional concentrations are coordinated through flexible data integration points, the composite AI engines, pattern diagnostics, scenario management, workflows, triage alerts, customer/case dashboards, data visualisation, and data/security governance policies.

The application has been adopted by numerous global banks, which have helped hone the feature set to maximise its business impact. Some of the more noteworthy capabilities include the following:

The KYC module uses adaptive elicitation procedures. The AI identifies missing data about a potential customer that would influence risk scores and prioritises obtaining that information from the applicant. In addition, automated screening for low-risk customers enables adopting banks to reduce analyst touch-time by up to 80%.

Gartner has recognised ELEMENT’s fresh counterpoint to traditional rules-based applications, which have been the industry standard for more than a decade. Machine learning and deep learning isolate anomalous patterns of customer (and employee) behaviour that could represent new patterns of fraud or money laundering, without explicitly being trained to identify these behaviours. The same AI monitors the outcomes of risk-flagging decisions. It incorporates that experience into a self-learning model of risk scoring and action recommendations to achieve continuous improvement.

The data visualisation tools are a departure from the output of a bank’s financial transaction systems plus watch lists. Traditional data screens display situational information in field-and-value format, which is unconducive to seeing the macro trends. Although Compliance and FIU have been organised into a combined unit, they often work with separate systems. BlackSwan has developed an ability to study relationships in visual formats that evolve to unique views based on datasets from across the enterprise.

While ELEMENT of Compliance caters to banks and asset management firms’ AML, fraud, KYC and CLM functions, related offerings from BlackSwan extend its risk management footprint into areas such as investigations, asset tracing, e-discovery, loan and insurance underwriting, and cyber threat intelligence.

For operational and technology decision-makers, there’s a concern that migrating from one’s existing technology to a new application platform could uncover unexpected complexities and take up a growing, possibly fatal (to the project) amount of time. BlackSwan incorporates several characteristics to address this. Indeed, in one client situation, it shortened the projected time to implementation by 50-fold, when compared to the prior, failed project that relied on another vendor.

The underlying ELEMENT platform is unusually agile. Partly, this is due to its low-code/no-code approach that allows business analysts to configure and customise everything from the data sources, AI models to the workflows, alerts, rules logic, case dashboard and data visualization layouts, without having to resort to programming. A no-code proof of concept (PoC) development environment, known as ELEMENTRY, lets potential adopters build a working PoC, apply different AI models, and view real-world insights – all in a single sitting.  

ELEMENT is cloud-agnostic, supporting private, public (any of the leading platforms), or hybrid architectures. Whichever the environment, the cloud-based approach provides fast deployment, and ease of maintenance and upgrading, as well as unlimited scalability (valuable when ingesting billions of external data points about entities and individuals). BlackSwan has applied its team’s prior experience in government intelligence to incorporate military-grade security, a key attraction for those evaluating cloud-based solutions. Organisations adopting ELEMENT of Compliance can operate the solution themselves, or rely on a managed service provider to apply best operational practices while further reducing costs and time-to-implementation. A flexible set of APIs enables the solution to share analytic results seamlessly with legacy systems.

The product targets the risk and compliance KPIs that matter most. One industry study found that 75–85% of the AML alerts raised at banks turn out to be false positives, for example, where two similarly-named entities might have been mistaken for each other. False positives were skyrocketing within the industry as stimulus checks went out, and a great shift to online transactions raised anti-fraud alarms across enterprises. 

In one client situation, BlackSwan Technologies worked with a global bank with $100 billion in assets that was concerned about ongoing exposure and frustrated with the false positives that increased its costs of complying with KYC, AML and related customer-activity regulations. After implementing ELEMENT of Compliance, the bank experienced a 50% reduction in false positives and an increase in accuracy identifying true positives from 89% to 99.7% of the time.

More broadly, clients have realised up to a 55% decrease in cost/alert, with a 65% alert volume reduction.

BlackSwan represents a real-world approach to helping banks build agile environments that iterate IT investments and leverage industry best practices to manage the risks of today, while advancing AI for the long term.

The judges said:

• “Very innovative use of AI.”
• “Unique offering that deploys AI to help customers develop their own solutions, or to tweak their processes, and how they ingest data sources. Compelling tech story with major big data chops.”  
• “Sophisticated, innovative product.”  

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