Trustworthy AI for Finance and Economics

Applications

Credit and risk scoring

The literature on algorithmic recourse commonly relates the methodology to the example of loan approval (e.g. Karimi, Schölkopf, and Valera 2021; Upadhyay, Joshi, and Lakkaraju 2021)
Kuiper et al. (2021) present a number of example use cases of AI in the context of consumer credit.

Financial Stability

AI robustness and the Covid crisis - negative impact of ML on model performance (Bholat, Gharbawi, and Thew 2020).
Potential for herding behaviour if large share of market participants uses off-the-shelf ML tools (OECD 2021).

Market Microstructure

ML model collusion hard to detect (OECD 2021).
Lack of explainability inhibits timely model adjustments (OECD 2021).
Intentional lack of transparency for proprietary trading (OECD 2021).

SupTech and RegTech

Market participants may start using AI to self-regulate in a transparent, trustworthy way (OECD 2021).
Simalarly, financial regulators are already employing AI for the purpose of supervision.

Monetary policy and forecasting

In Altmeyer, Agusti, and Vidal-Quadras Costa (2021) we show how to incorporate deep learning in the context of Vector Autoregression for macroeconomic data.

References

Altmeyer, Patrick, Marc Agusti, and Ignacio Vidal-Quadras Costa. 2021. “Deep Vector Autoregression for Macroeconomic Data.” https://thevoice.bse.eu/wp-content/uploads/2021/07/ds21-project-agusti-et-al.pdf.

Bholat, D, M Gharbawi, and O Thew. 2020. “The Impact of Covid on Machine Learning and Data Science in UK Banking.” Bank of England Quarterly Bulletin, Q4.

Karimi, Amir-Hossein, Bernhard Schölkopf, and Isabel Valera. 2021. “Algorithmic Recourse: From Counterfactual Explanations to Interventions.” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 353–62.

Kuiper, Ouren, Martin van den Berg, Joost van den Burgt, and Stefan Leijnen. 2021. “Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities.” arXiv Preprint arXiv:2111.02244.

OECD. 2021. “Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges and Implications for Policy Makers.” OECD. 2021. https://www.oecd.org/finance/financial-markets/Artificial-intelligence-machine-learning-big-data-in-finance.pdf.

Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. 2021. “Towards Robust and Reliable Algorithmic Recourse.” arXiv Preprint arXiv:2102.13620.