Consumer-Lending Discrimination in the FinTech Era

Bartlett, Robert P.; Morse, Adair; Stanton, Richard; Wallace, Nancy

doi:10.3386/w25943

Cited by 177 publications

(72 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the goal is for organizations to abandon AI -which some critics advocate -the "fatalistic" perspective is more effective. We show that the abandonment effect persists even in settings like (Bartlett et al, 2019) and Cowgill (2019) where algorithms reduce racial-and gender-disparities. The abandonment effect is also robust to the possibility of dedicated engineering improvements.…”

Section: Resultsmentioning

confidence: 73%

The Managerial Effects of Algorithmic Fairness Activism

Cowgill¹,

Dell'Acqua²,

Matz³

2020

AEA Papers and Proceedings

View full text Add to dashboard Cite

How do ethical arguments affect AI adoption in business? We randomly expose business decision-makers to arguments used in AI fairness activism. Arguments emphasizing the inescapability of algorithmic bias lead managers to abandon AI for manual review by humans and report greater expectations about lawsuits and negative PR. These effects persist even when AI lowers gender and racial disparities and when engineering investments to address AI fairness are feasible. Emphasis on status quo comparisons yields opposite effects. We also measure the effects of “scientific veneer” in AI ethics arguments. Scientific veneer changes managerial behavior but does not asymmetrically benefit favorable (versus critical) AI activism.

show abstract

Section: Resultsmentioning

confidence: 73%

The Managerial Effects of Algorithmic Fairness Activism

Cowgill¹,

Dell'Acqua²,

Matz³

2020

AEA Papers and Proceedings

View full text Add to dashboard Cite

show abstract

“…As financial markets continue to complexify, regulators must be continually mindful of iatrogenic responses if poorly constructed laws are enacted that drive further system complexity and unintended effects. There are also uncertainties on the wider social impacts of fintech, including its impact on marginalized classes and income inequality problems (Bartlett et al 2017;World Bank Group 2018). Additionally, the future of cryptocurrency as a money substitute is uncertain, as well as its net environmental impact.…”

Section: Conclusion and Emerging Issuesmentioning

confidence: 99%

Regulating Fintech in Canada and the United States: Comparison, Challenges and Opportunities (2020)

Clements

2020

SSRN Journal

View full text Add to dashboard Cite

The rise of fintech has attracted increased attention from investors, entrepreneurs, existing financial-sector participants and regulators. Fintech has many potential benefits and it could transform banking, lending, payments, investing and other financial services through the internet, smartphones, artificial intelligence, blockchain and cryptocurrencies, and many other current and future digital technologies. Such benefits include lower costs, an enhanced scope of products and services, and the possibility of reaching and offering previously underserved customers greater credit and financial services. Policy makers in Canada and the U.S. should encourage these positive developments, foster innovation and competition, and reduce barriers to entry, while ensuring adequate safeguards are established for the stability of the financial system and necessary consumer protections are in place.The market environment and regulatory approaches in Canada and the U.S. are similar but not uniform. Each jurisdiction faces different challenges and opportunities. The speed and complexity that this new wave of fintech has expanded throughout North America and the world, in just a few years, has created regulatory challenges for authorities in the U.S. and Canada. Fintech has many potential risks. If this revolution is not managed well, the results could be serious, including the risk of destabilizing the financial system.In the U.S., fintech has the potential for displacing banks and established financial institutions. There is also significant regulatory fragmentation and a growing desire for "principles-based" regulation -away from the "rules" based frameworks which generally characterize U.S. financial oversight. Several federal 1 and state regulators have instituted "regulatory sandboxes," which are an innovation that allows fintech firms to experiment with financial products and services in a limited and supervised way with potential relief from otherwise strict rules.Canada's financial regulatory structure is principles-based, and there is a healthy regulatory sandbox in securities jurisdiction. In Canada, due to high barriers to entry, and regulatory fragmentation for some fintech market segments not under federal oversight, fintech has been heavily driven by existing big banks. These incumbents often partner with upstart fintech firms to develop products and services inside the bank's existing infrastructure to enhance customer service and operations. As a result, new consumer-facing fintech firms in Canada are less prominent than in the U.S., which enjoys far greater levels of funding for fintech start-ups.Fintech creates new types of risks. When banks internally adopt fintech innovations into their existing processes and services there is cyber-risk and customer data vulnerability through new interface technologies, and risk to the stability of the financial system if more riskier borrowers are quickly approved for credit using algorithmic processes. Banks partnering with technology companies must also monitor and mana...

show abstract

“…In addition, the COMPAS program used for making bail and sentencing decisions in U.S. courts was hugely biased against black defendants, falsely flagging blacks nearly twice as likely to re-offend as whites (Larson et al, 2016). Moreover, AI-based online lenders discriminate against minorities, charging much higher interest rates to minority borrowers compared to white borrowers (Bartlett et al, 2018).…”

Section: Uncertainty Of Ai In Disease Diagnosis and Treatmentmentioning

confidence: 99%

The perils of artificial intelligence in healthcare: Disease diagnosis and treatment

Lee¹

2019

J. Comput. Biol. Bioinform. Res

View full text Add to dashboard Cite

For the past decade, artificial intelligence (AI) and its related technologies have made remarkable advances in marketing and business solutions based on AI-driven big data analysis of customer queries, and it, when coupled with bioinformatics, seemingly holds out great promise for use in healthcare. In reality, however, AI is still largely a buzzword when it comes to disease diagnosis and treatment. This review addresses the uncertainty of AI applications to disease diagnosis and treatment, not only pinpointing AI's inherent algorithmic problems in dealing with non-patternable stochastic healthcare data, but also revealing the innate fallacy of identifying genetic mutations as a tool for genome-based personalized medicine. Finally, this review concludes by presenting some insights into future AI application in healthcare.

show abstract

Consumer-Lending Discrimination in the FinTech Era

Cited by 177 publications

References 0 publications

The Managerial Effects of Algorithmic Fairness Activism

The Managerial Effects of Algorithmic Fairness Activism

Regulating Fintech in Canada and the United States: Comparison, Challenges and Opportunities (2020)

The perils of artificial intelligence in healthcare: Disease diagnosis and treatment

Contact Info

Product

Resources

About