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The author of this paper is not a lawyer. This paper does not constitute legal advice. The positions herein are presented for the purpose of academic research discussions, and do not necessarily reflect the views of Capital One.
References
- (1)
- Aleo and Svirsky (2008) Michael Aleo and Pablo Svirsky. 2008. Foreclosure Fallout: the banking industry’s attack on disparate impact race discrimination claims under the Fair Housing Act and the Equal Credit Opportunity Act. Public Law Interest Journal 18, 1 (2008), 1–66. https://www.bu.edu/pilj/files/2015/09/18-1AleoandSvirskyArticle.pdf
- Ards and Myers (2001) Sheila D Ards and Samuel L Myers. 2001. The Color of Money: Bad Credit, Wealth, and Race. American Behavioral Scientist 45 (2001), 223–239. https://doi.org/10.1177/00027640121957141
- Avery et al. (2012) Robert B. Avery, Kenneth P. Brevoort, and Glenn Canner. 2012. Does Credit Scoring Produce a Disparate Impact? Real Estate Economics 40, s1 (2012), S65–S114. https://doi.org/10.1111/j.1540-6229.2012.00348.x
- Baines and Courchane (4 11) Arthur P Baines and Marsha J Courchane. 2014-11. Fair Lending: Implications for the Indirect Auto Finance Market. https://www.crai.com/sites/default/files/publications/Fair-Lending-Implications-for-the-Indirect-Auto-Finance-Market.pdf
-
Bardenet et al. (2013)
Rémi Bardenet, Mátyás
Brendel, Balázs Kégl, and Michèle
Sebag. 2013.
Collaborative Hyperparameter Tuning. In
Proceedings of the 30th International Conference on International Conference on Machine Learning - Volume 28 (ICML’13). JMLR.org, II–199–207. http://dl.acm.org/citation.cfm?id=3042817.3042916 - Barocas and Selbst (2016) Solon Barocas and Andrew Selbst. 2016. Big Data’s Disparate Impact. California Law Review 104, 1 (2016), 671–729. https://doi.org/10.15779/Z38BG31
- Bayer et al. (8 01) Patrick Bayer, Fernando Ferreira, and Stephen L. Ross. 2018-01. What Drives Racial and Ethnic Differences in High-Cost Mortgages? The Role of High-Risk Lenders. The Review of Financial Studies 31, 1 (2018-01), 175–205. https://doi.org/10.1093/rfs/hhx035
- Bubeck and Cesa-Bianchi (2012) Sébastien Bubeck and Nicolò Cesa-Bianchi. 2012. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems. Foundations and Trends in Machine Learning 5, 1 (2012), 1–122. https://doi.org/10.1561/2200000024
- Burrell (2016) Jenna Burrell. 2016. How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society 3, 1 (2016), 1–12. https://doi.org/10.1177/2053951715622512
- Butler (6 08) Tammy Butler. 2016-08. Is your ”target marketing” breaking fair lending laws? https://fairlendingdiversity.com/target-marketing-breaking-fair-lending-laws/
- Chang et al. (2009) Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, Chong Wang, and David M. Blei. 2009. Reading Tea Leaves: How Humans Interpret Topic Models. In Proceedings of the 22nd International Conference on Neural Information Processing Systems (NIPS’09). Curran Associates Inc., 288–296. https://papers.nips.cc/paper/3700-reading-tea-leaves-how-humans-interpret-topic-models
- Clarke (2016) Roger Clarke. 2016. Big data, big risks. Information Systems Journal 26, 1 (2016), 77–90. https://doi.org/10.1111/isj.12088
- Cohen-Cole (1 05) Ethan Cohen-Cole. 2011-05. Credit card redlining. Review of Economics and Statistics 93, 2 (2011-05), 700–713. https://doi.org/10.1162/REST_a_00052
- Committee on Financial Services (5 11) Committee on Financial Services. 2015-11. Unsafe at Any Bureaucracy: CFPB Junk Science and Indirect Auto Lending. https://financialservices.house.gov/uploadedfiles/11-24-15_cfpb_indirect_auto_staff_report.pdf
- Committee on Financial Services (6 01) Committee on Financial Services. 2016-01. Unsafe at Any Bureaucracy, Part II: How the Bureau of Consumer Financial Protection Removed Anti-fraud Safeguards to Achieve Political Goals. https://financialservices.house.gov/uploadedfiles/cfpb_indirect_auto_part_ii.pdf
- Committee on Financial Services (7 01) Committee on Financial Services. 2017-01. Unsafe at Any Bureaucracy, Part III: The CFPB’s Vitiated Legal Case Against Auto-Lenders. https://financialservices.house.gov/uploadedfiles/1-18-17_cfpb_indirect_auto_staff_report_iii.pdf
- Consumer Financial Protection Bureau (2014) Consumer Financial Protection Bureau. 2014. Using publicly available information to proxy for unidentified race and ethnicity: a methodology and assessment. https://www.consumerfinance.gov/data-research/research-reports/using-publicly-available-information-to-proxy-for-unidentified-race-and-ethnicity/
- Consumer Financial Protection Bureau (8 03) Consumer Financial Protection Bureau. 2018-03. CFPB Supervision and Examination Process. https://www.consumerfinance.gov/policy-compliance/guidance/supervision-examinations/
- Consumer Financial Protection Bureau (8 05) Consumer Financial Protection Bureau. 2018-05. Statement of the Bureau of Consumer Financial Protection on enactment of S.J. Res. 57. https://www.consumerfinance.gov/about-us/newsroom/statement-bureau-consumer-financial-protection-enactment-sj-res-57/
- Cubita and Hartmann (2006) Peter N. Cubita and Michelle Hartmann. 2006. The ECOA Discrimination Proscription and Disparate Impact—Interpreting the Meaning of the Words That Actually Are There. The Business Lawyer 61, 2 (2006), 829–842. http://www.jstor.org/stable/40688368
- Datta et al. (6 05) A. Datta, S. Sen, and Y. Zick. 2016-05. Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems. In 2016 IEEE Symposium on Security and Privacy (SP). 598–617. https://doi.org/10.1109/SP.2016.42
- Division of Consumer and Community Affairs (1 07) Division of Consumer and Community Affairs. 2011-07. 12 CFR Supplement I to Part 202 - Official Staff Interpretations. https://www.law.cornell.edu/cfr/text/12/appendix-Supplement_I_to_part_202
-
Elliott et al. (9 04)
Marc N. Elliott, Peter A.
Morrison, Allen Fremont, Daniel F.
McCaffrey, Philip Pantoja, and Nicole
Lurie. 2009-04.
Using the Census Bureau’s surname list to improve estimates of race/ethnicity and associated disparities.
Health Services and Outcomes Research Methodology 9, 2 (2009-04), 69–83. https://doi.org/10.1007/s10742-009-0047-1 - Federal Trade Commission (3 02) Federal Trade Commission. 2013-02. In FTC Study, Five Percent of Consumers Had Errors on Their Credit Reports That Could Result in Less Favorable Terms for Loans. https://www.ftc.gov/news-events/press-releases/2013/02/ftc-study-five-percent-consumers-had-errors-their-credit-reports
-
Fernández-Delgado et al. (2014)
Manuel Fernández-Delgado,
Eva Cernadas, Senén Barro, and
Dinani Amorim. 2014.
Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?
Journal of Machine Learning Research 15 (2014), 3133–3181. http://jmlr.org/papers/v15/delgado14a.html - Feurer et al. (2015) Matthias Feurer, Jost Tobias Springenberg, and Frank Hutter. 2015. Initializing Bayesian Hyperparameter Optimization via Meta-learning. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI’15). AAAI, 1128–1135.
- Freeman (2013) Andrea Freeman. 2013. Payback: A structural analysis of the credit card problem. Arizona Law Review 55 (2013), 151–199.
- Freeman (7 05) Andrea Freeman. 2017-05. Racism in the Credit Card Industry. North Carolina Law Review 95, 4 (2017-05), 1071–1160. http://scholarship.law.unc.edu/nclr/vol95/iss4/4
- Hurley and Adebayo (2016) Mikella Hurley and Julius Adebayo. 2016. Credit Scoring in the Era of Big Data. Yale Journal of Law & Technology 18 (2016), 148–216. http://yjolt.org/credit-scoring-era-big-data
- Ibarra and Rodriguez (2007) Beatriz Ibarra and Eric Rodriguez. 2007. Latino Credit Card Use: Debt Trap or Ticket to Prosperity? National Council of La Raza Issue Brief 17 (2007).
- Kaebling et al. (6 05) Leslie P Kaebling, Michael L Littman, and Andrew W Moore. 1996-05. Reinforcement Learning: A Survey. Journal of Artificial Intelligence Research 4 (1996-05), 237–285. https://jair.org/index.php/jair/article/view/10166
- Kevin and M. (2006) Fiscella Kevin and Fremont Allen M. 2006. Use of Geocoding and Surname Analysis to Estimate Race and Ethnicity. Health Services Research 41, 4p1 (2006), 1482–1500. https://doi.org/10.1111/j.1475-6773.2006.00551.x
- Koren (6 08) James Rufus Koren. 2016-08. Feds use Rand formula to spot discrimination. The GOP calls it junk science. Los Angeles Times (2016-08). http://www.latimes.com/business/la-fi-rand-elliott-20160824-snap-story.html
- Lieber (9 01) Ron Lieber. 2009-01. American Express Kept a (Very) Watchful Eye on Charges. The New York Times (2009-01), B1. http://www.nytimes.com/2009/01/31/your-money/credit-and-debit-cards/31money.html?pagewanted=all
- Mayser (1 07) Sabine Mayser. 2011-07. Perceived Fairness of Differential Customer Treatment. https://doi.org/10.1177/1094670512464274
- Mayser and von Wangenheim (2013) Sabine Mayser and Florian von Wangenheim. 2013. Perceived Fairness of Differential Customer Treatment: Consumers’ Understanding of Distributive Justice Really Matters. Journal of Service Research 16, 1 (2013), 99–113. https://doi.org/10.1177/1094670512464274
- McDonald (2016) Kevin M McDonald. 2015-2016. Who’s policing the financial cop on the beat? A call for judicial review of the Consumer FInancial Protection Bureau’s non-legislative rules. Review of Banking & Financial Law 35, 1 (2015-2016), 224–271. http://ssrn.com/abstract=2786093
- Mnih et al. (5 02) Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis. 2015-02. Human-level control through deep reinforcement learning. Nature 518 (2015-02), 529–533. https://doi.org/10.1038/nature14236
- Nguyen and Klaus (2013) Bang Nguyen and Philipp Phil Klaus. 2013. Retail fairness: Exploring consumer perceptions of fairness towards retailers’ marketing tactics. Journal of Retailing and Consumer Services 20, 3 (2013), 311–324. https://doi.org/10.1016/j.jretconser.2013.02.001
- Office of the Comptroller of the Currency (7 01) Office of the Comptroller of the Currency. 2017-01. Credit Card Lending: OCC Comptroller’s Handbook.
- O’Neill (2016) Cathy O’Neill. 2016. Weapons of Math Destruction: how big data increases inequality and threatens democracy. Crown. https://weaponsofmathdestructionbook.com
- Pfahringer et al. (2000) Bernhard Pfahringer, Hilan Bensusan, and Christophe G. Giraud-Carrier. 2000. Meta-Learning by Landmarking Various Learning Algorithms. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML ’00). Morgan Kaufmann, 743–750. http://dl.acm.org/citation.cfm?id=645529.658105
- Ribeiro et al. (6 08) Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016-08. ”Why Should I Trust You?”: Explaining the Predictions of Any Classifier. In KDD ’16 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 1135–1144. https://doi.org/10.1145/2939672.2939778
- Ritter (2012) Dubravka Ritter. 2012. Do we still need the Equal Credit Opportunity Act? https://ideas.repec.org/p/fip/fedpdp/12-03.html
- Ropiequet et al. (2014) John L. Ropiequet, Christopher S. Naveja, and L. Jean Noonan. 2014. Fair Lending Developments: Is Disparate Impact Here to Stay? The Business Lawyer 69, 2 (2014), 609–621. http://www.jstor.org/stable/43665748
- Rothstein (2018) Richard Rothstein. 2018. The Color of Law: A Forgotten History of How Our Government Segregated America. Liveright.
- Rutherglen (1987) George Rutherglen. 1987. Disparate Impact under Title VII: An Objective Theory of Discrimination. Virginia Law Review 73, 7 (1987), 1297–1345. http://www.jstor.org/stable/1072940
- Steel and Angwin (0 08) Emily Steel and Julia Angwin. 2010-08. On the Web’s Cutting Edge, Anonymity in Name Only. Wall Street Journal (2010-08). www.wsj.com/news/articles/SB10001424052748703294904575385532109190198
- Strader (5 06) Yolanda P Strader. 2015-06. CFPB Continues Crackdown on Fair Lending: Marketing Materials Targeted. https://www.carltonfields.com/cfpb-continues-crackdown-on-fair-lending-marketing-materials-targeted/
- Turner (6 09) Ryan Turner. 2016-09. A model explanation system. In 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP). 1–6. https://doi.org/10.1109/MLSP.2016.7738872
- US Congress (1968a) US Congress. 1968a. 42 U.S.C. §3601 ff.: Fair Housing Act. https://www.justice.gov/crt/fair-housing-act-2
- US Congress (1968b) US Congress. 1968b. Consumer Credit Protection Act. http://uscode.house.gov/view.xhtml?path=/prelim@title15/chapter41&edition=prelim
- US Congress (0 10) US Congress. 1970-10. 15 U.S.C. §1681 ff.: Fair Credit Reporting Act. https://www.gpo.gov/fdsys/pkg/STATUTE-84/pdf/STATUTE-84-Pg1114-2.pdf
- US Congress (4 10) US Congress. 1974-10. 15 U.S.C. §1691 ff.: Equal Credit Opportunity Act. https://www.ecfr.gov/cgi-bin/text-idx?tpl=/ecfrbrowse/Title12/12cfr202_main_02.tpl
- US Congress (3 12) US Congress. 2003-12. P. L. 108-159: Fair and Accurate Credit Transactions Act of 2003. https://www.gpo.gov/fdsys/pkg/PLAW-108publ159/pdf/PLAW-108publ159.pdf
- US Congress (7 03) US Congress. 2017-03. Fair and Equal Housing Act of 2017. https://www.congress.gov/bill/115th-congress/house-bill/1447
- US Court of Appeals for the Eighth Circuit (3 03) US Court of Appeals for the Eighth Circuit. 2013-03. No. 11-3466: Catherine L. Taylor v. Tenant Tracker, Inc. https://www.gpo.gov/fdsys/pkg/USCOURTS-ca8-11-03648/pdf/USCOURTS-ca8-11-03648-0.pdf
- Vermorel and Mohri (2005) Joannès Vermorel and Mehryar Mohri. 2005. Multi-armed Bandit Algorithms and Empirical Evaluation. In Machine Learning: ECML 2005, João Gama, Rui Camacho, Pavel B. Brazdil, Alípio Mário Jorge, and Luís Torgo (Eds.). Springer Berlin Heidelberg, 437–448.
- Wei et al. (2016) Yanhao Wei, Pinar Yildirim, Christophe Van den Bulte, and Chrysanthos Dellarocas. 2016. Credit Scoring with Social Network Data. Marketing Science 35, 2 (2016), 234–258. https://doi.org/10.1287/mksc.2015.0949
- Zhang (6 01) Yan Zhang. 2016-01. Assessing Fair Lending Risks Using Race/Ethnicity Proxies. Management Science 64, 1 (2016-01), 178–197. https://doi.org/10.1287/mnsc.2016.2579
- Zimmer (1996) Michael J Zimmer. 1996. The Emerging Uniform Structure of Disparate Treatment Discrimination Litigation. Georgia Law Review 30 (1996), 563–626. https://ssrn.com/abstract=1354323
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