On the back of our recent thought leadership article ‘Why are regulated institutions still not getting their Fraud and AML (FRAML) due diligence right?’, MoData, as market leaders and experts at collaborating in the fight against financial crimes are excited to introduce an industry-first pilot to enable secure FRAML data exchange using Blockchain, Confidential computing, and AI technology
Overview
Existing technology currently supports companies to detect fraudulent transactions that originate or are received by a single company. These technologies use decision management systems that combine predictive machine learning models and business rules that allow companies to monitor transactions to detect potentially suspicious activity and either alert or, in some cases, block transactions. In addition, companies are sensitive to the costs of investigations and the need to effectively identify and mitigate fraud risks that may result in potential losses. MoData and R3 believe these new technologies will help companies to reassess previously unknown risky transactions, quickly and more accurately, which will have dramatic improvements in return on investment for fraud teams.
How?
Confidential computing will allow multiple datasets from several companies to be brought together for analysis and identify fraudsters attempting to avoid detection by structuring their transactions and behaviour across many institutions.
Fraudsters modify their techniques for moving money, for example, reducing amounts or volumes of transactions to avoid detection across multiple institutions and accounts. Fraudsters are employing methods such as adversarial AI to reverse engineer the scenarios that are less likely to be detected by the decision management systems employed by the companies. When this occurs, fraudulent activities may not be investigated because they are not detected based on the few transactions that pass-through monitoring systems in a single institution. When companies can identify patterns of financial activity occurring across multiple companies it improves detection and risk management, while at the same time providing a better return on investment across the industry by reducing fraud losses and improving fraud investigation efficiency. In addition, as the volume of data increases and insights are identified, there will be greater improvements to fraud analytics and models.
Given the sensitivity of transaction and account data, any data exchange must be able to meet exacting security and privacy requirements which has to date been difficult to achieve. The proposed solution uses next-generation hardware Trust Technology (Intel SGX) in conjunction with the R3 Conclave development platform to ensure data is only processed and exchanged for agreed appropriate purposes.
Conclusion
Real-time data sharing through a trust model is absolutely key in the success of industry collaboration in the fight against financial crimes and aiding regulators to increase the risk posture and safety in the global financial ecosystem. MoData is the first to market this Blockchain, Confidential computing and AI capability to enable such a trust model without compromising customer or business privacy. MoData is also first to market the only affordable, real-time software-as-a-service (SaaS) marketplace for all financial crime and risk management operations. This customer value proposition removes the upfront investment barriers and where organisations can select bespoke FRAML services they need to stitch into their customer journeys while availing a monthly pay-as-you use license model. MoData brings a collective 86 years of financial crime and risk management experience as passionate crime fighters and industry collaborators during this tenure.
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