An AI solution to expose potential corruption risks

Summary:

The solution leverages digital technologies, including RPA/IPA, ML, AI, and data visualization, to expose potential corruption risks at the transaction level by identifying trends, patterns, relationships, and anomalies.

Client:

Founded in 1975, Microsoft Corporation is an American multinational technology company headquartered in Redmond, Washington. Microsoft develops AI-powered platforms and tools to provide innovative solutions that address the changing needs of its customers.

Problem Statement:

In the technology market, Microsoft operates within complex sales channel structures involving partners, distributors, and resellers. This multi-level sales channel structure poses risks such as bribery, corruption, collusion, and fraud. Given the frequent prosecutions of technology companies under the Foreign Corrupt Practices Act (FCPA), including actions taken by their business partners, Microsoft decided to implement a technical system to detect and monitor corruption risks proactively.

The challenge was to create a solution that not only detects corruption but also prevents potential corruption risks from escalating into issues. To address this, Microsoft sought assistance from PwC to develop an innovative solution that can utilize data analytics to identify risky transactions, allowing for additional compliance oversight throughout the sales agreement lifecycle, from pre-sale to post-order.

Results: 

• Effectiveness in work of the compliance program of the company by bringing together disparate data sets and management of its compliance risks. 
• Reduction in  risk of costly fines and reputational damage through early risk identification and compliance oversight. 
• Increased ability to make better-informed decisions about the deal.

AI Solution Overview:

Utilizing Microsoft’s extensive sales and channel partner data, PwC collaborated to develop the Microsoft Compliance Analytics Program Solution for real-time compliance reviews throughout the sales deal lifecycle. The solution leverages cutting-edge digital technologies, including RPA/IPA, ML, AI, and data visualization, to uncover corruption risks at the transaction level. By identifying trends, patterns, relationships, and anomalies, these technologies help expose potential corruption risks.

The program involves “data ingestion” from over 40 IT systems and data sources, totaling more than 80 terabytes of data (both structured and unstructured). In addition to the analytics solution, PwC collaborated on designing a new operating model for Microsoft. This included establishing a “high-risk” deals desk responsible for reviewing sales transactions flagged by the analytics and managing the identified risks.

This customized solution integrated enhanced controls into Microsoft’s standard sales process. Microsoft proactively assigns risk scores to its sales contracts and channel partners on a scale from zero to 100. When a contract or partner exceeds a certain risk threshold or score, a report is generated for the compliance function embedded in the business to execute controls. By identifying corruption risks early in the sales lifecycle, Microsoft can mitigate risks effectively and assess the adequacy of existing controls.

References: 

1. Prioritizing ethics and integrity: How Microsoft uses data analytics to fight corruption. https://www.pwc.com/us/en/library/case-studies/ethics-and-integrity-as-the-priority-how-microsoft-uses-data-analytics-to-fight-corruption.html
2. Using Machine Learning For Anti-Corruption Risk And Compliance.https://www.coalitionforintegrity.org/wp-content/uploads/2021/04/Using-Machine-Learning-for-Anti-Corruption-Risk-and-Compliance.pdf

Industry: Anti-Corruption Compliance

Vendor: PwC

Client: Microsoft Corporation

Publication Date: 2020