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Use Case Business

Good Governance and Compliance: Artificial Intelligence for analysis, forecasting and support of good corporate management

The application of Artificial Intelligence (AI) for corporate management is already established in research and practice. The question of how governance and compliance issues can also be thematized with the help of AI is highly relevant, but has hardly been addressed so far. To achieve this is the overriding objective of the present Use Case. Society and state demand Good Governance and Compliance from enterprises. This concerns internal procedures in the enterprise, where laws and social norms are to be kept, as well as the relationship of enterprises and state, for instance the taxation. The growing use of AI for increasingly diverse functions in the company is both an opportunity (e.g. recognition of violations of standards) and a task (e.g. prevention of discrimination through algorithms) with regard to these criteria.

The aim of the Use Case is to analyse the role of AIs in companies with regard to compliance and good governance and, in particular, to answer whether and under what conditions AIs support compliance with social standards (e.g. anti-discrimination), detect or predict violations of applicable rules (e.g. white-collar crime) and how the macroeconomic effects of the increasing use of AIs are to be treated (e.g. taxation). The special and novel challenge of this use case - in contrast to scientific or engineering questions - is how to deal with endogenous risks that arise from adaptive human behaviour when using AIs.

In terms of content, the objective is pursued through cooperation between economists, lawyers and computer scientists. In order to comprehensively understand the desired and undesired behavioral effects of the use of AI, the use case is subdivided into three sub-cases that intertwine in terms of content, method and technology. These relate to:

  1. (Non-)Financial Compliance: Detection of misconduct in the areas of financial fraud, but also violations of norms in the field of corporate social responsibility (How can data from accounting or CSR reporting in conjunction with other sources of information (big data) be used to derive early indications of violations of regulatory requirements?)
  2. Social compliance: especially discrimination (How can AI be used to make personnel decisions without violating social norms?)
  3. Tax compliance: Design of tax regulations (What is an appropriate and consistent framework of standards for the taxation of AI-supported business models and what repercussions does this have for corporate structures and processes?)
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