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Equalizing Credit Opportunity in Algorithms
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Equalizing Credit Opportunity in Algorithms (2022)Equalizing Credit Opportunity in Algorith…The (Im)possibility of fairness (2021)The (Im)possibility of fairne…Fairness in credit scoring: Assessment, implementation and profit implications (2021)Fairness in credit scoring: A…Bias Preservation in Machine Learning: The Legality of Fairness Metrics Under EU Non-Discrimination Law (2021)Bias Preservation in Machine …On the apparent conflict between individual and group fairness (2020)On the apparent conflict betw…The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform (2019)The roles of alternative data…Consumer-Lending Discrimination in the FinTech Era (2019)Consumer-Lending Discriminati…A comparative study of fairness-enhancing interventions in machine learning (2019)A comparative study of fairne…50 Years of Test (Un)fairness (2019)50 Years of Test (Un)fairnessCREDIT SCORING IN THE ERA OF BIG DATA (2017)CREDIT SCORING IN THE ERA OF …Variable importance analysis: A comprehensive review (2015)Variable importance analysis:…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…The Scored Society: Due Process for Automated Predictions (2014)The Scored Society: Due Proce…Consumer Financial Protection Bureau (2014)Consumer Financial Protection…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactEqual Employment Opportunity Commission (2012)Equal Employment Opportunity …Board of Governors of the Federal Reserve System (2001)Board of Governors of the Fed…Fairness Without Demographic Data: A Survey of Approaches (2023)Fairness Without Demographic …Uniform Guidelines on Employee Selection Procedures (2007)Fairness through awareness (2012)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Semantics derived automatically from language corpora contain human-like biases (2017)A Survey on Bias and Fairness in Machine Learning (2021)Equality of Opportunity in Supervised Learning (2016)A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle (2021)A Review on Fairness in Machine Learning (2022)Trustworthy AI: From Principles to Practices (2022)Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending (2012)Trust and Credit: The Role of Appearance in Peer-to-peer Lending (2012)Fintech, regulatory arbitrage, and the rise of shadow banks (2018)Machine learning techniques for credit risk evaluation: a systematic literature review (2020)Fintech and big tech credit: Drivers of the growth of digital lending (2022)Fintech, Cryptocurrencies, and CBDC: Financial Structural Transformation in China (2022)Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color (1991)What Is the Point of Equality? (1999)An empirical characterization of fair machine learning for clinical risk prediction (2020)A clarification of the nuances in the fairness metrics landscape (2022)Fairness in recommender systems: research landscape and future directions (2023)Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)AI in education: learner choice and fundamental rights (2020)Algorithmic bias: Senses, sources, solutions (2021)Can HR adapt to the paradoxes of artificial intelligence? (2022)Statistical principles in experimental design. (1962)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global Sensitivity Analysis. The Primer (2007)Regression and Kriging metamodels with their experimental designs in simulation: A review (2016)Random forests for global sensitivity analysis: A selective review (2020)Surrogate-assisted global sensitivity analysis: an overview (2020)Expanding Enrollments and Contracting State Budgets (2013)Limited and Varying Consumer Attention: Evidence from Shocks to the Salience of Bank Overdraft Fees (2014)Foundations of Financial Well‐Being: Insights into the Role of Executive Function, Financial Socialization, and Experience‐Based Learning in Childhood and Youth (2015)The Threat of Algocracy: Reality, Resistance and Accommodation (2016)Artificial Intelligence and the Public Sector—Applications and Challenges (2018)Artificial Intelligence in Society (2019)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)The ethics of algorithms: Mapping the debate (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Demand System Approach to Asset Pricing (2018)Does Climate Change Affect Real Estate Prices? Only If You Believe In It (2018)The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data (2020)
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References

  • 2014Big Data's Disparate Impact3,046 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2001Board of Governors of the Federal Reserve System1,130 cited
  • 2019A comparative study of fairness-enhancing interventions in machine learning601 cited
  • 2015Variable importance analysis: A comprehensive review526 cited
  • 2014The Scored Society: Due Process for Automated Predictions523 cited
  • 2019The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform431 cited
  • 2014Consumer Financial Protection Bureau333 cited
  • 2020On the apparent conflict between individual and group fairness312 cited
  • 201950 Years of Test (Un)fairness297 cited
  • 2012Equal Employment Opportunity Commission275 cited
  • 2021The (Im)possibility of fairness262 cited
  • 2019Consumer-Lending Discrimination in the FinTech Era212 cited
  • 2017CREDIT SCORING IN THE ERA OF BIG DATA199 cited
  • 2021Fairness in credit scoring: Assessment, implementation and profit implications196 cited
  • 2021Bias Preservation in Machine Learning: The Legality of Fairness Metrics Under EU Non-Discrimination Law

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  • 2023Fairness Without Demographic Data: A Survey of Approaches21 cited