There are more than one trillion U.S. dollars are estimated to be involved in worldwide acts of bribery and political corruption each year. These crimes impede developing nations from achieving stability, recovering from disasters and realizing measurable growth by siphoning off foreign aid and stealing national revenue.
Undiscovered instances of corporate corruption and bribery also unleash destructive effects on otherwise law-abiding Western organizations. In recent years, the United States government has dramatically intensified its efforts to enforce the provisions of the Foreign Corrupt Practices Act (FCPA). Nearly $2.5 billion in penalties were assessed in 2016, making it the biggest enforcement year in FCPA history. This cost is too high for global corporations to ignore.
Modern technologies and advancements in data science such as artificial intelligence (AI) and machine learning are well suited to solve this problem. AI-based systems have progressed to the point where large volumes of transactional data from enterprise accounting and email systems can be culled, consolidated, analyzed, and scored for risk so suspicious activities can be identified and compliance teams can make faster, more accurate determinations.
AI-based solutions, such as those offered by QuantaVerse, can easily analyze massive amounts of corporate financial data, discern patterns, and quickly identify where exceptions or anomalies exist that can unveil FCPA risks.
As U.S. corporations engage in imports/exports, foreign transactions, and related business deals, there is potential downstream FCPA and UK Bribery Act risk at every juncture. AI and other data analysis can efficiently assess FCPA potential risk to ensure no hidden risks exist, speed up identification of anomalous behavior and make an ABC compliance program more proactive than reactive.
Click here to read our full paper that discusses the integration of AI into anti-bribery and corruption programs to mitigate FCPA risk.
Prior to the COVID-19 outbreak, the 2020 outlook was an encouraging one as the year was shaping up to be positive for many industries. At the mid-year point of 2020, the world has changed, and we continue to observe the pandemic’s impact on our communities, economy,...
Jurisdiction Derivation, Powered by AI, Helps Financial Institutions Reduce Risk and Their Number of AML Investigations
Financial institutions are held accountable by regulators to ensure they are taking a risk-based approach in their AML/BSA compliance operations. As such, institutions must consider AML risk based on certain types of customers and transactions, including risky jurisdictions impacted by political or economic unrest.
The AI-powered QuantaVerse Automated Volume and Value (V&V) Transaction Analysis solution provides risk managers with better insights into variances in account activity that might indicate risks of financial crimes, or that suggest an account is being used for something other than its stated purpose. Analysis of this nature is a growing regulatory burden driven by the expectation that FIs understand the risk profile of clients as well as their clients’ clients.