Leveraging Data Analytics and Artificial Intelligence to Streamline Compliance Investigations

Leveraging Data Analytics and Artificial Intelligence to Streamline Compliance Investigations

May 13, 2024

This article was originally published in GRC Outlook Magazine, Legal Case Management Edition, May 2024. You can find the original article here. *Note: We have obtained the necessary permissions to republish this content.

In the ever-evolving business operations landscape, the early identification and containment of compliance risks has become a paramount concern for organizations worldwide. As someone deeply involved in both government and internal investigations, I have had the privilege of witnessing firsthand the transformative power of data analytics in unraveling complex schemes, identifying compliance gaps, and mitigating compliance risks before they spiral out of control.

In my journey through the world of investigations, I have discovered a profound love for uncovering truths and navigating the complexities of data. During my decade-plus tenure at the FCPA Unit of the U.S. Securities and Exchange Commission, I investigated misconduct across industries and geographic regions. This was an incredible experience, albeit somewhat limited in terms of the investigative technology stack available as a civil servant. Since joining the service provider community as a member of the TransPerfect Legal family, I am now armed with an impressive array of investigative tools to materially streamline the investigative process and ensure clients spend less time searching for key documents and more time analyzing and acting on them.

In today’s fast-paced and interconnected, Big Data business environment, traditional methods of investigation need to be revised. Manual reviews of documents and transactions are time-consuming and prone to human error.

Data analytics and artificial intelligence (AI) is thus a game-changer, offering an unparalleled potent blend of speed, accuracy, and depth of insight. Data analytics and AI involve using statistical models, algorithms and unsupervised machine learning to analyze raw data, providing valuable insights, isolating key documents and aiding decision-making. This process transforms data into actionable intelligence, guiding investigators toward relevant leads and potential risks.

The integration of analytics and AI into compliance investigations has revolutionized the process. Investigators can now identify trends, correlations, and outliers in financial transactions, communications, and employee behavior. This proactive approach helps detect fraud, misconduct, and compliance breaches more swiftly and accurately, where we can now go over layers of transactions and communications to uncover illicit actions. In the past, unraveling schemes required exhaustive manual efforts, sifting through vast volumes of data with the hope of finding a clue. However, this process has been revolutionized with the advent of data analytics.

As one example, in my daily practice, I leverage and investigative platform called Digital Reef, an investigations, an Early Case Assessment and e-discovery tool that leverages not only search terms, date filters and file-type breakdowns, but also sophisticated algorithms and machine learning models to swiftly analyze vast datasets. Through data visualization and anomaly detection, Digital Reef illuminates patterns that may elude human observation.

The main features that I look for in any analytics and AI-driven investigations platform are:

  • Reports: does the platform produce easily-digestible and readily-downloadable reports of key insights, such as volumes of search term hits, breakdowns of languages within the data and data sources, folder paths, and domains, etc.
  • Communication Grids: does the platform the volume and frequency of email traffic sent between specific individuals and/or email domains?
  • Email Threading: does the platform collate email “threads” for a more streamlined review and analysis?
  • Concept Clustering: using unsupervised machine learning, will the platform categorize my documents based on their content and subject matter?
  • Similarity Analysis: if I find a “hot” document, will the AI engine of the platform automatically find similar documents based on their content and subject matter?
  • GenerativeAI: while we are in the “beginning of the beginning” of generativeAI, does the tool offer any features like document summarization, automated chronologies and “ask my documents a question”?

The transformative impact of AI and data analytics on internal investigations cannot be overstated. They have enabled us to uncover intricate fraud schemes, identify compliance gaps, and mitigate risks before they escalate into crisis. In today’s fast-paced business environment, where compliance risks abound and fraudsters are becoming increasingly sophisticated, data analytics and AI are a beacon of hope, offering a proactive and agile approach to safeguarding organizations.

As we look to the future, integrating data analytics and AI into compliance investigation practices will continue to evolve. Organizations that embrace these tools and harness the power of data will be better equipped to navigate the complexities of the modern business landscape, ensuring resilience, compliance, and long-term success.

Data analytics and AI are crucial components of proactive investigations and plays a significant role in obtaining useful insights and accelerating results across various fields. Analysts use advanced algorithms, machine learning models, and data visualization techniques to uncover misconduct, enabling targeted and prompt action. The ability to detect misfeasance quickly empowers investigators to respond to and contain potential threats. As technology continues to evolve, data analytics and AI will become even more vital in driving compliance investigations and shaping the future of decision-making and risk management across industries and geographic regions.

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By Maria Gallo, Director of Special Investigations & FCPA, TransPerfect Legal