The use of artificial intelligence (AI) will truly revolutionize compliance, allowing it to more efficiently and robustly be operationalized into the fabric of an organization employing this new technology. Not only is this one exciting reason to be involved with the compliance profession today, tomorrow, and into the future, it also make companies run more efficiently and with higher profitability.
One area with the prospect of greater application is machine learning of bribery and corruption schemes. This is the type of AI that moves past the information that compliance professionals may be able to pull from corporate databases, such as gifts, travel, and entertainment (GTE). Consider when one employee spends a large amount of GTE not on one foreign government official but on one department. Now pair that example with an entire business unit that spends far over the limit for one company employee on one foreign government official. Key issues arise around too many false positives requiring too many resources to investigate such findings.
A straight transactional analysis might well raise one or more red flags under either scenario. If you couple machine learning into the mix, however, you might be able to decrease these instances of false positives. What your system should do is review timeline findings to provide trends over time, coupled with a robust statistical analysis that compares similar events. Under the above two GTE scenarios, you would consider the information on the employee GTE spend and then review the statistical information on the business generated after the contract is signed.
Behavioral analytics, coupled with machine learning will enhance anti-corruption compliance programs and the company run more efficiently, as it will allow an organization to more closely track its overall spend going forward.