From many, comes one (algorithm)

Recent anticorruption research shows that when companies collaborate to share information about third-party payments and high-risk transactions, they have a 25% greater chance of predicting improper payments than when each company’s model is performed in isolation. A new data-sharing consortium led by a nonprofit at MIT is working to make such collaboration possible.

According to the World Economic Forum, international corruption can take many forms, including bribery, embezzlement, cronyism, and fraud. And it’s an expensive problem that costs the global economy trillions of dollars annually. (See “Corruption is costing the global economy $3.6 trillion dollars every year,” by Stephen Johnson, World Economic Forum, Dec. 13, 2018.) Detecting it is challenging but possible using advanced analytics and machine learning technologies on top of legal and subject-matter expertise. And, when organizations work together in collaboration, it’s now proven the results are even better. Here we look at how a consortium led by a nonprofit at MIT is helping organizations share data without comprising privacy in their fight against fraud.

Companies work hard to detect and prevent fraud and corruption. Still, it can be challenging for businesses to identify behaviors that cross the line — particularly where employees are determined to commit a crime and then take steps to conceal their behavior. As anti-fraud professionals, we’re increasingly using data analytics to identify and monitor these risks for our organizations or clients. A critical factor when evaluating compliance programs involves determining if compliance and control personnel have sufficient access to relevant data sources. Can they access information to implement timely monitoring, policy testing and controls evaluation? As the U.S. Department of Justice (DOJ) indicates, this is even more critical in a regulatory environment that increasingly requires monitoring amid the ever-expanding availability of new data sources. This is true not just during due diligence but “throughout the lifespan of the third-party relationship,” says the DOJ. [See “Evaluation of Corporate Compliance Programs (Updated June 2020),” U.S. Department of Justice, Criminal Division.]

Corruption often tends to flourish where multiple actors compete in opaque markets in a race to the bottom, often leaving victims unaware of wrongdoing occurring across multiple organizations. Against that backdrop, we shouldn’t attack corruption alone in organizational silos, but rather encourage transparency across organizations and industry sectors, sharing insights, risk profiles and third-party attributes that describe a potentially improper or corrupt payment.