"Artificial intelligence in the prevention of legal and corruption risks of companies: opportunities and best practices"
October 20, the 10th-anniversary meeting of the HSE Compliance Club has taken place. The event was constructed in a mixed format, most of the Club members took part online. The moderator was Krylova Dina Vladimirovna, Head of the HSE PULAP, Public Ombudsman in the sphere of Protection of Entrepreneurs' Rights in the Field of Anti-Corruption, expert of the Council of Europe.
Leida Lukyanova, Vice President of Mobile TeleSystems PJSC for Business Ethics and Compliance, told the Club members about the artificial intelligence center at MTS PJSC and its compliance management systems in the field of labor compliance, which are aimed at optimizing the work of compliance services. The systems allow compliance managers to assess both the risks of reducing motivation and employee outflow, to receive and process data in connection with the pandemic: to track the peaks of morbidity, to take additional measures to protect employees, and, in general, to determine the company's development strategy in the short term in force majeure, as well as to solve issues in the field of anti-corruption compliance in order to optimize compliance control.
Alexander Rusetsky, Deputy Director General for Compliance of the Autonomous Non-profit Organization "Moscow Directorate of Transport Services", Director of the RANEPA Anti-Corruption Research and Training Center for Business Ethics and Compliance, spoke about the results that the "Moscow Directorate of Transport Services" was able to achieve in a year and a half of the work of the Compliance Department. As part of his speech, he spoke about the main functions of the compliance unit – providing methodological assistance to Moscow transport enterprises, improving anti-corruption mechanisms that already exist in organizations, and forming a unified system of anti-corruption activities. To solve the existing problem, the company is working on a single digital platform, which is designed to automate the processes that already exist as much as possible.
Alexander Hegai, Compliance Director in the Central European, member of the Academic Council of the Amazon Master's program "Compliance and Prevention of Legal Risks in the Corporate, Public and Non-profit Sector" of the HSE Faculty of Law, spoke in his speech about the pros and cons of using artificial intelligence in the compliance environment. He noted that Amazon is one of the leading developers of artificial intelligence in the world, but most of the developments remain inside the company. However, in his speech, the speaker drew attention no longer to Amazon, of which he is a representative, but in general to the use of artificial intelligence. "Artificial intelligence is a human attempt to identify all the connections that occur in the human brain and introduce them into machine production," was the definition given by Alexander Hegai. According to the speaker, artificial intelligence is developing very rapidly, for example, in the USA artificial intelligence is 9% more effective than doctors in making diagnoses to patients.
Asya Andreichenko, Director of Compliance Control at the First Infrastructure Company, noted in her speech that although the company she represents is not as large as Amazon and cannot afford high costs for artificial intelligence, she still tries to optimize her work by implementing certain mechanisms. So, she spoke about several areas where artificial intelligence can help: the analysis of significant amounts of documentation, the analysis of the database of court decisions, the consolidation of the database into a single format. AI is used in counterparty risk scoring: absence of signature in documents, assessment of general information (counterparty's age, authorized capital, founders), reliability assessment, etc. The speaker gave an example of the use of artificial intelligence in lockdown when the work was carried out online. Artificial intelligence was tested to identify the degree of employee engagement and satisfaction. Thus, informal leaders were identified, who were later attracted as compliance ambassadors.
Nikolay Solodovnikov, Partner, Head of Corporate Law Practice, Head of the Legal support of the digital economy of Pepelyaev Group, in his speech shared the experience of Pepelyaev Group in terms of using developments related to Legal Tech, which simplify the lives of lawyers and the entire accounting office. Since the development of its own mechanisms is quite expensive, the company has taken the path of interaction with other major market players, in particular with the company Nlogic, which develops a platform for working with formal texts and unstructured data. This platform allows you to search and match entities in documents and thus run some scripts. Thus, the time for processing typical operations is reduced, and employees have the opportunity to engage in more creative activities.
Yulia Glubokaya, Head of the Legal Department and Compliance of ABB Electric Networks, Russia. She shared the Coalition for integrity study "Using machine Learning in anti-corruption compliance". Yulia noted several advantages of the study: good definitions, a decision-making algorithm and ethical aspects. "Machine learning cannot cover all elements of compliance programs. If the company is not very big, then it can consider artificial intelligence based on human-developed rules. If the company is large, then it can consider machine learning," the speaker said. An important aspect of this process is the specialists themselves, compliance officers. They should use the data that the algorithm outputs efficiently. The speaker also stated that the company's code of ethics should include exactly how the company will use artificial intelligence methods.
"Any compliance processes can be automated by artificial intelligence," Sergey Svetushkin, director of the Transparent Deal project, Kaspersky Lab, shared his company's experience at the conference. The speaker spoke about three areas where his corporation uses artificial intelligence: identifying conflict relationships, where the main problem is a large amount of data; enriching objects with data; identifying types of relationships from unstructured data. Sergey Svetushkin also considered sanctions compliance and tasks related to internal and external fraud.