In this three-part blog post series, we are ruminating on how to create an effective compliance program through  the use of data analytics. I am joined in this exploration by Vince Walden, CEO of Kona AI and we are considering the requirements laid out by the Department of Justice (DOJ) in their recent pronouncements on best practices, as well as the key trends and lessons learned from enforcement actions. Finally, we will consider the speech by Kenneth Polite on the changes to the Corporate Enforcement Policy and how to meet those requirements using data analytics. Walden articulated 10 steps you need to follow:

1. Assess a company’s conduct;
2. Self-disclose;
3. Know quickly if there is a problem or not;
4. Have access to relevant sources of data;
5. Conduct monitoring at the beginning and throughout the lifespan of the relationship
6. Have an on-premise application;
7. Look up vendors and transactions quickly;
8. Run data through a library of corruption and fraud tests;
9. Look at a predictive model and see if it meets the profile of an improper payment; and
10. Have visibility into data almost at their fingertips.

Under Step 4, companies must quickly analyze their data quickly and efficiently to determine if they need to self-disclose any potential issues. By sharing the attributes across corporate siloes, companies can make their individual models perform better and improve their compliance programs. This allows companies to access the data quickly and easily, allowing them to identify potential risks and areas of improvement. It also provides insights into the effectiveness of compliance programs, allowing companies to make better informed decisions concerning their compliance.

Overall, having access to relevant sources of data is essential for an effective compliance program. Companies can gain access to data through on-premise platforms. By leveraging these sources of data, companies can ensure their compliance programs are up to date and compliant with applicable laws and regulations.

Step 5 is to conduct monitoring at the beginning and throughout the lifespan of any business  relationship or transaction cycle. This is an important step as it allows a company to identify potential issues with their compliance program and take corrective action. Monitoring should be conducted at the beginning of a relationship or transaction to ensure that all parties understand the expectations and that there is no potential for criminal activity. Monitoring should continue throughout the relationship as well, as this will allow a company to identify any changes in behavior or activity that could indicate a potential problem. This can be used to gain insights into a vendor’s financial and transactional data, which is often a key indicator of future or even potential compliance violations.

Having access to relevant sources of data and conducting monitoring throughout the lifespan of a third-party relationship will help an organization meet the expectations set by the DOJ for an effective compliance program. With the DOJ’s recent announcement of amendments to the Corporate Enforcement Policy, companies have even greater incentive to self-disclose if they uncover potential violations, all of which demonstrates an effective compliance program. A data analytics platform can help companies quickly identify understanding of the risks and monitoring these relationships regularly, companies can ensure that they are compliant with all applicable regulations and review potential issues.

With a comprehensive view of their activities, organizations can quickly identify any changes in activities, such as unusual patterns of payments or activities, which could indicate a potential problem. Through visibility into third party activities and transactions, companies are able to gain a better understanding of the compliance risk associated with their third-party relationships. Moreover, businesses have a mechanism to identify any financial or transactional red flags.

Interestingly Walden advocates having an “on-premise application” for data analytics, which is he step 6.  He believes “This is an important step, as it allows companies to keep their data secure, while still being able to use predictive analytics and other compliance monitoring tools.” It can be hosted and managed as a service, “meaning that companies can utilize the platform without having to move large amounts of data around each month.” This helps companies to gain insights from the model without compromising their data privacy. Furthermore, this platform can be used to identify anomalous payments that may be indicative of corruption or fraudulent activities.

Join us tomorrow where continue conclude our exploration of using data analytics to create an effective compliance program.

Listen to Vince Walden on Data Driven Compliance

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