Stop advanced attacks and financial market manipulation with AI
Brighterion’s artificial intelligence creates unique one-to-one behavioral analysis that detects and predicts behavioral patterns over time at both the individual and market levels. The result is a technology platform providing unique insights into the behavior of markets, traders and algorithms. Ultimately Brighterion AI protects the stability of financial markets by rooting out cyber crime, insider trading, brute force attacks and more.
HOW BRIGHTERION AI BENEFITS FINANCIAL MARKETS:
- Increased efficiency: Augments employees’ efforts and efficiency via automation
- Immediate ROI: Reduces back office costs and increases ROI
- Gained autonomy: Customers dynamically incorporate changes and test each change
- Know what’s happening in the moment: Real-time insights provide unprecedented, omnichannel visibility into the behavior of each entity
- Never run out of space: Infinite scalability, more than 2x the rate of our nearest competitor (Aite Group analysts)
- Be ready in 6–8 weeks with AI Express
- Peace of mind: Backed by Mastercard experience and infrastructure
Use case: AML & compliance
Anti-money laundering (AML) compliance can be extremely complex for global organizations; countries have their own regulations and unique sanctions laws. The estimated amount of global money laundering is US$2 trillion a year, according to the UN Office on Drugs and Crime. Financial markets face regulatory scrutiny and potentially heavy fines, sometimes measured in the billions of dollars for non-compliance. As companies broaden channels and increase transaction volumes, transaction monitoring is becoming increasingly difficult. Failure to put a comprehensive compliance program in place also means risking depreciated share value, costly legal battles and reputational damage, as will failure to accurately monitor and report detected activity in a timely manner.
Four critical actions require specific controls for AML and sanctions laws while transacting and operating:
- Onboarding: verify the identity of new customers while ensuring they are not on a relevant sanctions list
- While transacting: ensure parties in a transaction are not sanctioned, and screen for fraudulent transactions, e.g., mirror trading and “smurfing” wherein numerous purchasers buy the same stock with black money using smaller transactions to comprise the entire amount
- Post-transaction: monitor all transactions for indications of money laundering or terrorist finance activity
- During a customer’s lifecycle: use customer risk rating (CRR) to properly monitor based upon customer’s risk profile with proper adjustments made based upon observed behavior/change
The most commonly used tool, rules-based technology, is inefficient. Criminals often change behaviors, requiring multiple resources to modify rules-based systems and manually dispose of AML alerts with false positive ratios as high as 96%.
Brighterion creates artificial intelligence models that identify behavior indicative of money laundering. Brighterion AI modeled the compliance rules and used supervised and unsupervised learning to keep the model flexible, providing adaptive learning and continuous updates to better reflect the evolving nature of techniques used by money launderers.
For one major payments company, Brighterion completed the AML compliance model in 6 weeks. Brighterion reduced 50,000 rules from the rules-based system to 12 and used Smart Agents technology to develop one-to-one relationships that provided individual account views for each user. Alerts were reduced from 8,300 per month to 300, significantly reducing the cost of investigating false positives. The payments company reported increased detection of money laundering schemes and built a case for law enforcement.