Bias in Mission-Driven Finance: Discrimination or Mission Drift?*
There is a growing focus on the issue of inequitable lending practices. It has been demonstrated that institutions with a social mission are not exempt from the potential for negative bias. This paper contributes to the existing literature in two ways. First, we present a theoretical framework for e...
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| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
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| Veröffentlicht: |
2026
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| In: |
Journal of business ethics
Jahr: 2026, Band: 203, Heft: 1, Seiten: 91-106 |
| weitere Schlagwörter: | B
D63
B Ethical finance B C44 B Migrants B C12 B Discrimination in lending B Mission drift B G21 B Gender B Unemployed B J16 B J15 |
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Volltext (lizenzpflichtig) |
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| 520 | |a There is a growing focus on the issue of inequitable lending practices. It has been demonstrated that institutions with a social mission are not exempt from the potential for negative bias. This paper contributes to the existing literature in two ways. First, we present a theoretical framework for elucidating the nature of bias for mission-driven lenders, who prioritize lending to specific disadvantaged groups. This framework clarifies the distinction between discrimination, which is defined with respect to ethical principles, and mission drift, which is associated with a specific social mission. This classification helps to rigorously assess the nature of identified biases. Second, we test for bias in lending outcomes using data from a European microfinance organization (MFO), with a social mission to prioritize unemployed loan applicants. The findings suggest that the mission-driven lender is subject to both discrimination and mission drift. The results indicate the presence of two discriminatory biases: (i) against women holding European Union (EU) citizenship in comparison with EU men and (ii) against unemployed women in comparison with unemployed men. The evidence of mission drift stems from the negative bias against unemployed women in comparison with employed women. These three biases are consistent with unconscious gender stereotypes. The theoretical and managerial implications of these findings are discussed in the conclusion, along with avenues for further research, particularly in the detection of bias in fintech lending. | ||
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