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Recent Advances in Algorithmic Biases and Fairness in Financial Services: A Survey

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Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1 (FTC 2022 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 559))

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Abstract

Artificial intelligence capabilities and machine learning algorithms have been widely used in different applications including financial services. Many financial services such as loan or credit limit approval and credit score estimation rely on automated algorithms to offer efficient and best possible services to customers. However, algorithms suffer from intentional and unintentional biases and produce unfair outcomes. This paper presents a survey of algorithmic biases and fairness in financial services. We study the sources of bias and the different instances of bias existing in the prominent areas of the financial industry. We also discuss on the detection and mitigation techniques that have been proposed, developed and used to enhance transparency and accountability.

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Acknowledgments

This work was supported in part by Mastercard Inc research funds and Intel Corporation research funds at Howard University. However, any opinion, finding, and conclusions or recommendations expressed in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the funding agencies.

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Authors and Affiliations

  1. Howard University, Washington, DC, 20059, USA

    Aakriti Bajracharya, Utsab Khakurel, Barron Harvey & Danda B. Rawat

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  1. Aakriti Bajracharya
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  2. Utsab Khakurel
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  3. Barron Harvey
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  4. Danda B. Rawat
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Correspondence to Aakriti Bajracharya .

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  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Bajracharya, A., Khakurel, U., Harvey, B., Rawat, D.B. (2023). Recent Advances in Algorithmic Biases and Fairness in Financial Services: A Survey. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-031-18461-1_53

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