Last year, 45 new FCPA-related investigations were publicly disclosed for the first time, making 2017 the most active year in history for new disclosures of FCPA-related investigations. Rewind one year and take into consideration 27 companies were required to pay a paralyzing $2.48 billion in fines and penalties to resolve FCPA cases in 2016, making it the biggest enforcement year in FCPA
These are but only two parts of a much larger force driving urgency around FCPA risk, which begs the question: “Why are current FCPA compliance efforts failing?”
We have dedicated this edition of On the Front Line with AI to discussing how corporations are adopting AI as part of their anti-bribery and corruption programs to mitigate FCPA risks.
Key highlights from the discussion with anti-money laundering (AML) expert and Founder & CEO of QuantaVerse, David McLaughlin, include:
- In recent years, the United States government has dramatically intensified its efforts to enforce the provisions of the Foreign Corrupt Practices Act (FCPA)
- There’s a historic increase in the number of companies under investigation and greater investigative resources are being deployed, including more FBI agents
- This sense of urgency goes beyond the U.S., as European regulators are following the U.S. model to crack down on corruption and are actively cooperating with U.S. enforcement agencies
The Problem with Current FCPA Programs and How They Can Be Improved with AI
- Current FCPA programs are ineffective and laborious because of their reliance on:
- Reports from whistleblowers
- Outdated technology that runs tedious keyword searches
- These programs are failing to find critical indicators of corruption such as accounting misappropriations
- The next evolution of FCPA is to leverage modern technologies and advancements in data science such as artificial intelligence (AI) and machine learning
While this is debated, the problem persists as legacy AML technology such as transaction monitoring systems (TMS) have little to no ability to identify and assess risk created by shell companies. And while policies, procedures, and processes, if applied correctly, can protect financial institutions from becoming conduits for some fraction of money laundering, terrorist financing, and other financial crimes, identifying shell company risk continues to be elusive.
On the final day of the FIBA conference, QuantaVerse Founder and CEO, David McLaughlin, participated on the “Customer Profiling, Use of Innovative Technologies in Onboarding and Risk Assessment” panel. David Schwartz, President and CEO of FIBA, set up the panel discussion by emphasizing the importance and impact that innovative technologies have on risk assessment and the customer onboarding process.
CASE STUDY: AI-Powered Entity and Alert Adjudication Streamlines Financial Crime Investigation Processes
Based on these outcomes, the bank is moving QuantaVerse AI solutions into production. Moving forward, the bank will be better equipped to find hidden financial crime risk while automating 70 percent of its AML investigation processes, enabling investigators to focus their time and talents on the most complex cases.