AI for Compliance and Integrity Monitoring in Private Companies: Benefits and Use Cases

Table of contents:

  • Why is AI so effective in compliance and integrity monitoring?
  • How AI combats money laundering for HSBC and JPMorgan Chase
  • AI is a foreseer based on data, not feelings
  • AI for 90% faster in internal investigations
  • AI is just better at it…

Regulatory requirements and ethical standards are becoming increasingly complex and stringent. Failure to meet these requirements for private companies can result in significant financial penalties, legal sanctions, and the loss of trust from customers and partners. In fact, compliance is not just a bureaucratic hurdle but is important for protecting businesses against vulnerabilities. 

Yet, in many companies compliance and integrity monitoring still rely on outdated methods, like spreadsheets and labor-intensive processes, thus provoking costly mistakes due to human factors. According to Corporate Compliance Insights, in 2020, regulators imposed fines of $15B on banks, of which US banks shouldered 73%.

Artificial Intelligence offers efficiency, accuracy, and adaptability to compliance. Due to its outstanding capabilities in real-time data monitoring and analyzing, as well as making data-based forecasts, AI enables companies to effectively follow regulatory requirements, detect potential risks, and ensure high integrity within organizations while making the processes much less time- and cost-consuming.

I assume that in the near future AI will completely substitute human workforces in the compliance and integrity realm. Here’re some of my thoughts on it with some vibrant cases from Stopcorruption.ai.

Why is AI so effective in compliance and integrity monitoring?

In order to meet compliance requirements, organizations must deal with vast amounts of data from various sources. The bigger the company, the more information it has to process, and that is challenging for human teams. 

AI can process large volumes of data in the blink of an eye, easily detecting anomalies or inconsistencies that may indicate violations of norms or standards. It will hardly miss something because it’s tired or it has only two hours left before the long-awaited annual leave. AI is always equally concentrated, attentive, and accurate despite the current state of the economy and weather conditions. And that is quite useful for banks.

How AI combats money laundering for HSBC and JPMorgan Chase

HSBC collaborated with Ayasdi, a company that develops machine learning (ML) software, to create an AI-based solution for combating money laundering. 

This is how it works:

  • The software detects suspicious patterns in historical data.  
  • Then, the current payment data will be analyzed, and various factors, including the source and destination of payments, will be examined to identify any unusual behavior.
  • If it identifies fraudulent transaction patterns, it alerts personnel to block such payments.

By implementing this AI-based anti-money laundering (AML) solution, the bank was able to reduce investigation time by more than 20% and minimize regulatory risks by identifying previously overlooked risk segments.

JPMorgan Chase adopted a similar solution. This AI-based system analyzes customer data and identifies potential risks. Integrating AI-based solutions into its compliance processes allowed the company to improve its ability to identify fraudulent activities, achieve better accuracy, and reduce false positives by 95%.

AI is a foreseer based on data, not feelings

Algorithms can help companies not only to detect all types of possible violations, but predict potential risks. Their forecasts are based on historical data and behavioral patterns, which are extremely useful for predictive analysis. 

Such an approach allows companies to prevent violations before they occur instead of dealing with cases that have already happened, thus avoiding millions of dollars in expenses.

For example, the world’s largest brewer, AB-InBev, developed an ML technology to identify risky business partners and potential illegal payments. 

  • The BrewRIGHT analytical platform consolidates data from finance, compliance, HR, and other systems in over 50 countries to detect transactions and third parties that pose risks. 
  • Transactions or relationships are classified as high-risk based on various risk attributes such as urgency of payment, payment to a political or government entity, supplier type, and a weighted scoring of these attributes.
  • BrewRIGHT enables proactive monitoring and prevents violations effectively. 

The solution reduced the AB-InBev’s costs related to compliance with anti-corruption norms by millions of dollars.

AI for 90% faster in internal investigations

It is also an indispensable tool for investigations. AI can scan emails, messages, and other communications to detect signs of corruption or policy violations.

A European distributor of agricultural machinery initiated an internal investigation into cartel activity. Management needed to respond quickly to mitigate the risk of fines and negative publicity. The primary objectives were to determine whether the bid-rigging was an isolated incident involving a single fraudulent employee or a more widespread issue. 

The company employed the Aiscension tool, developed in collaboration with eDiscovery and AI experts at Reveal Brainspace

  • The tool rapidly scans millions of messages using AI to detect potential risks.
  • Working in over 100 languages, it can be implemented across the entire supply chain to ensure compliance. 
  • It is trained to detect various forms of cartel behavior, including price-fixing, bid-rigging, market division, collective boycotts, and exchanging confidential information. 

Due to its capabilities, with Aiscension investigations or compliance checks can be conducted 91% faster than traditional audits and more cost-effectively than any other options.

AI is just better at it…

Regulatory frameworks are constantly changing, making it challenging for organizations to keep up with the latest requirements. People often fail to stay on top of the news, while algorithms are extremely good at navigating changes. AI automates regulatory compliance checks or document updates, reducing human error and enabling rapid monitoring.

The implementation of AI in compliance and integrity monitoring benefits private companies in numerous ways. It provides:

  • higher levels of security, transparency, and accountability, 
  • reducing risks and preventing violations,
  • strengthening brand trust and enhancing reputation, 
  • improving competitiveness in the market,
  • reducing costs. 

I firmly believe that AI’s role in these processes will only grow in the future, gradually displacing the human factor from these processes. Eventually, there will be very little space for the business of legal companies, outsourcing compliance and integrity monitoring for private companies in exchange for significant fees. However, I do not exclude the fact that human participation in these processes will remain mandatory in some final verification stages, but only for chosen experts. 

Algorithms evolve each day, becoming more advanced. Therefore, some specific AI-based tools, like BrewRIGHT or Aiscension mentioned above, may one day become completely self-sufficient in providing such services without any involvement of human supervisors.

Best regards,

Author: Vitaliy Goncharuk

12New.AI / BestAgreement.ai

CEO & Founder