Using Big Data for Detecting Economic and Corruption Crimes by Vitaliy Trenkenshu

By Vitaliy Trenkenshu

Join Vitaliy Trenkenshu, Chief Executive Officer of redflags.ai and Enterprise Big Data Framework Alliance Ambassador, as he delves into the challenges and innovations in detecting economic and corruption crimes using big data.

In Kazakhstan, the sheer volume of public procurement contracts makes them impossible to monitor for compliance and efficiency by relevant authorities, leading to annual losses estimated at US$ 470 million. The redflags.ai team developed an analytical system using Qlik Sense to identify risky tenders and contracts, focusing auditors’ attention on high-risk areas. This award-winning tool has significantly enhanced governmental auditors’ efficiency, helping prevent losses in procurement and saving taxpayers’ money. Over US$ 86 million of taxpayers’ money has already been saved as a result.

Participants will gain insights into integrating diverse data sources, including tax records, public procurement data, and familial connections, for effective risk assessment. The session will also demonstrate how alerting systems can proactively assist prosecutors, featuring interactive demonstrations, real-case scenarios, and a detailed walkthrough of the system, emphasizing its role in streamlining investigations and enhancing prosecutorial decisions.

About the Speaker

Vitaliy Trenkenshu, CEO and Founder of redflags.ai, is an expert in anti-fraud data analytics. His award-winning platform combats fraud in procurement through advanced data analytics. With over a decade of experience, he has assisted Kazakhstan’s government agencies in detecting and preventing economic crimes. His team develops analytical applications that automate red flag identification, uncover price anomalies, signs of collusion, and compliance violations, enhancing audit effectiveness. Notably, his largest anti-fraud project has generated over $600 million in economic impact.