Integrity Distributed

From many comes one...

Integrity Distributed is a non-profit organization dedicated to developing anti-corruption technology through academic partnership

helping companies cost-effectively fight the multi-trillion-dollar problem of global corruption, Integrity Distributed is unlike any organization of its kind. With minimal start up, maintenance and operating costs, we believe that the use of anti-corruption algorithms will become table stakes for all compliance programs.

Integrity Distributed (InDi) is that solution.

Our Mission Statement

Integrity Distributed is a non-profit organization dedicated to leveraging technology to democratize analytics to fight corruption, improve transparency, and set new standards for compliance.

As organizations increasingly digitize, it is inevitable that technological advances find their way into compliance programs. This transition can be challenging as it can require knowledge, technology and expense that is beyond the reach of many compliance programs.

Integrity Distributed seeks to fill that gap by funding and promoting research into technologies that enable organizations to collect and gain insights into data, develop algorithms based on those insights, and trade those algorithms on a platform that allows for real time bench-marking and the development of “super algorithms” that incorporate the feedback of the group

The project was initially spearheaded by Matthew Galvin, currently Compliance Counsel to the U.S. Department of Justice, Criminal Division, Fraud Seciton and formerly Chief Compliance Officer of AB InBev and the architect of the award-winning BrewRIGHT compliance analytics platform, who developed this technology in conjunction with MIT in order to find a sustainable approach to scale data analytics to optimize compliance programs. In his experience in developing advanced compliance platforms, Matt understood that there were too barriers to more widespread adoption - effeciency and cost. By leveraging differential privacy strategies developed at MIT, Matt saw the opportunity to scale analytics processes across companies in a way that could preserve privacy while allowing collaboration - thereby unlocking algorithms that could improve at low cost and require minimal upkeep to operationalize. The solution has lead to the most exciting and innovative technology in compliance and an answer to the question - how do we know if our compliance program is effective?

Our Research

Our Current Research:

In November of 2022, InDi released its first research paper which was generously funded by the AB InBev Foundation

InDi team brought together forensic accounting technology and data science professionals from Kona AI, MIT and Harvard Business School, working in cooperation with Fortune 500 companies and leading AmLaw 100 Law firms who focus on white-collar crime.

Several companies extracted relevant third-party payments data from their enterprise resource planning systems (e.g., SAP or Oracle procure-to-pay systems) and loaded it into a consistent unified data model (or UDM) developed by Kona AI. On a company-by-company basis, payment risks were risk-scored across a library of tests and behavioral algorithms, and the highest risk transactions were reviewed by each company’s representatives and/or their retained outside counsel. Using an approach that originated in eDiscovery known as Technology Assisted Review (TAR), a predictive model was created for each company designed to proactively identify a potentially improper payment based on the attributes of each transaction. Finally, each company’s model was combined into one “super-model,” using a neural network statistical model to retain and share insights while protecting data privacy and anonymity.

With this initial cohort of companies, the results of the super-model clearly indicate that the predictive value of identifying a potentially improper payment is 25% greater when companies collaborate compared to results when each company’s model is performed in isolation. As more companies are added to the cohort, it is our expectation that the super-model results will continue to improve, thus fueling InDi’s mission to help organizations fight global corruption.

Future Research Coming in 2023:

Funded by participating members, InDi intends to publish more anti-corruption research and insights related to model performance, key risk variables that trigger high risk third parties across the cohort of participating organizations, among other key innovations and observations.

The Power of Your Peers

As of December 2022, six leading companies have collaborated in the Integrity Distributed framework. Each member has pulled and organized parts of their accounts payable (spend) data and leveraged that data to analyze risks. The result produced six individual algorithms that were sent to

Integrity Distributed which returned a singular “super algorithm” that was superior to each of the six.ntegrity Distributed has demonstrated that by working together, companies can leap frog years of development in a matter of months, and avail themselves of the most sophisticated compliance algorithm on the market.

Join US!

Register to participate in our second cohort

Integrity Distributed is seeking applications for its second cohort of companies to join its account payable initiative. By joining in this cohort, companies can ensure access to an anti-corruption algorithm that has already outperformed anything on the market.

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