Innovation toward more proactive investigations
Data analysis is an established tool companies and organizations use to investigate potential corruption. Now, at Microsoft, we’re leveraging advancements in technology to broaden the ability of investigators and auditors to use data more proactively in their work.
Globally, it’s common for companies and organizations to investigate third parties like partners or service providers. These investigations delve into areas such as internal compliance, supply chain integrity, and potential violations of policy and procedures.
Typically, investigations are initiated by and reliant on whistleblower reports or audit findings after corrupt acts have already happened. Those investigations can be hampered by data that is complex, incomplete, or siloed and not fully accessible.
Microsoft is developing new approaches to data analysis—and tools that use cutting-edge technologies such as machine learning and AI—to speed up investigations and proactively address risk for the company in its own operations.
These internal innovations are reflected by Microsoft ACTS, our Advanced Cloud Transparency Services initiative, as we seek to accelerate transparency with data-driven solutions that can empower governments to uncover risks, identify red flags, and spot suspicious behavior patterns within the data.
New methods expand investigative capabilities
The new processes and tools Microsoft is developing focus on applying advanced data analysis to uncover suspicious patterns, identify potential risk signals sooner, resolve cases more rapidly, and gain insights to use that proactively reduce—or even prevent—corruption.
Auditors, attorneys, and investigators continue to employ traditional methods of data analysis, such as SQL database queries, which are used in procurement, sales, and other operations. Layered on top of these are new methods, for example, ways to use and combine data that is siloed in different internal systems while also maintaining privacy and security standards, enabling a fuller picture of investigation subjects to be obtained.
Figure 1 Above: Shifting data analysis to the start of an investigation creates more opportunities for early detection.
Shifting data analysis to the start of investigations provides the potential to find evidence that can help resolve cases faster and also frees up investigators to focus on other avenues of inquiry. Further, the development of better ways to condense vast amounts of data into reports, analyses, and visualizations that are easier to understand and use supports more informed decision-making for better case outcomes.
The future of investigation technology
The next wave of innovation centers on expanding sources of data and the introduction of cutting-edge technology to utilize it.
Internal data only tells part of the story of the history, behavior, and relationships of an entity. Leveraging third-party and external open-source information, such as public records and business registries, will add critical details for investigations.
Soon, investigative tools will become even more powerful. Data scientists and analysts are working on projects to implement versions of AI-powered generative AI, making vast quantities of records much easier for investigators to mine by simply typing in questions.
The ultimate aspiration is to develop ways to detect risk and reduce—or even prevent—corrupt acts before they happen. In pursuit of this, data models and ways to visualize risk patterns are being developed by using machine learning and AI to study past investigations. These models can be used to identify trends that need to be addressed, to become aware of vulnerabilities, or to flag potential issues in the data which need further investigation.
These and other new advances in processes and technology, and the ways they are applied internally at Microsoft, are all part of moving the needle on the risk lifecycle—and our mission to help governments achieve greater transparency and empowerment to be more proactive against corruption.