TILEC Seminar: Konrad Borowicz | Open Finance, Artificial Intelligence and Data Quality

Abstract

As the financial industry seeks to leverage the strengths of artificial intelligence (AI), it must confront the data quality problem. AI applications demand substantial volumes of both training and testing data, posing significant challenges not only in terms of data availability but also with respect to its quality. Open finance initiatives focus on the former but not the latter. AI regulations are likely to impose strict but general data quality requirements prompting the question how the financial industry will meet them. While some private initiatives aimed at addressing the problem are ongoing, major issues in areas such as data structuring, compensation, liability, and dispute resolution are likely to remain unaddressed. This paper proposes a menu of public policy options designed to address the data quality problem inspired by data quality regulations in various sectors. These options range from providing guidance regarding financial data quality, mandating the setting of data quality standards by private data sharing schemes to public management of data pools certified to meet such standards.

Speaker: Konrad Borowicz

Time: 10:45-11:45 hrs