Data Analytics and the FCPA
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Data analytics can reduce the risk of corporate liability for bribery and corruption by third parties.
In order to comply with the provisions of the Foreign Corrupt Practices Act (FCPA), many companies direct their efforts towards making sure their employees follow the appropriate regulations and avoid corrupt behavior; however, a recent report from KPMG International available at https://assets.kpmg.com/content/dam/kpmg/pdf/2015/09/anti-bribery-corruption-2015.pdf claims that the biggest threat of liability from violations of the FCPA is associated with third parties not under the direct control of the company yet for whose unlawful, illegal, and criminal actions the company and its executives may be liable.
The challenge facing companies from bribery and corruption associated with their international trade and commerce has increased as the trend towards globalization continues to accelerate. As more and more and smaller and smaller companies seek to enter overseas markets in unfamiliar locations; as supply chains continued to lengthen; and as outsourcing and off shoring seems to be an inevitable competitive necessity in many industries; new opportunities for corruption and bribery proliferate, much of it in new and novel guises.
Minimizing risk to the company from the actions by third parties should be, but according to the KMPG report, is not, a top priority for almost half the companies involved in the survey. KPMG also reports that there has been a continuing expansion of global enforcement against bribery and corruption regulators outside the United States particularly in Europe, but even in China and Brazil.
There is significant difficulty in auditing third parties for FCPA compliance.
It is also becoming increasingly difficult to conduct due diligence with respect to foreign agents and third parties engaged in facilitating international trade and commerce.
There is a need to develop and implement a formal business risk-based process for “onboarding” new third parties who may become involved in the international trade efforts of any business subject to the FCPA. For example, it is important to determine whether prices charged by a third-party are consistent with fair market values for similar services based on a genuine business need for those services. Prices above fair market value should immediately flag the third-party vendor for further investigation since the higher than market value priced quoted may include charges that might be construed as bribery or corruption.
Merely requesting no third-party vendors to “self report” or complete pro forma due diligence questionnaires is not a substitute for a meaningful investigation utilizing the modern tools of data analytics. According to the KPMG report, almost half of their respondents did not use data analytics in order to do assure compliance with FCPA concerns, citing their belief that the investment of money and management energy was too great.
Predictive and Behavioral Analytics are growing in use to combat money laundering and fraud
Global media firms, manufacturers, exporters, importers, and financial institutions who use their own customer and market data augmented with third party data sources, including those from digital and social media, such as twitter feeds and online purchase behavior routinely use data anlytius in their marketing and promotion efforts. Insurers use numerous sources of “unstructured” and qualitative data to underwrite policies of varying types, including liability and trade risk management as well as individual, traditional life insurance contracts.
The mathematics of data analytics is well-established and there are many computer programs commercially available for predictive and behavioral analytics. Failure to utilize these tools to conduct due diligence with respect to compliance by third party vendors with the Foreign Corrupt Practices Act in the United States and the equivalent legislation in many of our trading partners exposes any business engaged in international trade and commerce to civil and criminal liability and their executive management substantial risk of civil and criminal liability.