Machine-Learning Credit Scores and Disparate Impact Theory PDF Download
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Author: Lauri Kai
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
This Note analyzes the effects of machine learning in the lending context and argues that the existing legal framework can address unintentional discrimination that may result from credit-scoring models developed through machine learning. Potential liability stems from increased complexity of machine-learning processes; as machine-learning algorithms become more sophisticated, it becomes more difficult to explain the results they produce. Under current law, the inability to reasonably explain or even discover the correlations between data inputs and the resulting disparate impact leaves the lender vulnerable to suit for unintentional discrimination.
Author: Lauri Kai
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
This Note analyzes the effects of machine learning in the lending context and argues that the existing legal framework can address unintentional discrimination that may result from credit-scoring models developed through machine learning. Potential liability stems from increased complexity of machine-learning processes; as machine-learning algorithms become more sophisticated, it becomes more difficult to explain the results they produce. Under current law, the inability to reasonably explain or even discover the correlations between data inputs and the resulting disparate impact leaves the lender vulnerable to suit for unintentional discrimination.
Author: Robert B. Avery
Publisher: DIANE Publishing
ISBN: 1437980201
Category :
Languages : en
Pages : 52
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Book Description
Author: Anne Kraus
Publisher:
ISBN: 9783954047369
Category : Algorithm
Languages : en
Pages : 166
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Book Description
Author: Bogumił Kamiński
Publisher:
ISBN: 9788380304246
Category :
Languages : en
Pages :
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Book Description
Author: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35
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Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Author: Raymond Anderson
Publisher: Oxford University Press
ISBN: 9780199226405
Category : Business & Economics
Languages : en
Pages : 791
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Book Description
The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions.In eight modules, the book provides frameworks for both theory and practice. It first explores the economic justification and history of Credit Scoring, risk linkages and decision science, statistical and mathematical tools, the assessment of business enterprises, and regulatory issues ranging from data privacy to Basel II. It then provides a practical how-to-guide for scorecard development, including data collection, scorecard implementation, and use within the credit risk management cycle.Including numerous real-life examples and an extensive glossary and bibliography, the text assumes little prior knowledge making it an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners.
Author: Naeem Siddiqi
Publisher: John Wiley & Sons
ISBN: 1118429168
Category : Business & Economics
Languages : en
Pages : 124
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Book Description
Praise for Credit Risk Scorecards "Scorecard development is important to retail financial services in terms of credit risk management, Basel II compliance, and marketing of credit products. Credit Risk Scorecards provides insight into professional practices in different stages of credit scorecard development, such as model building, validation, and implementation. The book should be compulsory reading for modern credit risk managers." —Michael C. S. Wong Associate Professor of Finance, City University of Hong Kong Hong Kong Regional Director, Global Association of Risk Professionals "Siddiqi offers a practical, step-by-step guide for developing and implementing successful credit scorecards. He relays the key steps in an ordered and simple-to-follow fashion. A 'must read' for anyone managing the development of a scorecard." —Jonathan G. Baum Chief Risk Officer, GE Consumer Finance, Europe "A comprehensive guide, not only for scorecard specialists but for all consumer credit professionals. The book provides the A-to-Z of scorecard development, implementation, and monitoring processes. This is an important read for all consumer-lending practitioners." —Satinder Ahluwalia Vice President and Head-Retail Credit, Mashreqbank, UAE "This practical text provides a strong foundation in the technical issues involved in building credit scoring models. This book will become required reading for all those working in this area." —J. Michael Hardin, PhD Professor of StatisticsDepartment of Information Systems, Statistics, and Management ScienceDirector, Institute of Business Intelligence "Mr. Siddiqi has captured the true essence of the credit risk practitioner's primary tool, the predictive scorecard. He has combined both art and science in demonstrating the critical advantages that scorecards achieve when employed in marketing, acquisition, account management, and recoveries. This text should be part of every risk manager's library." —Stephen D. Morris Director, Credit Risk, ING Bank of Canada
Author: Woodrow Barfield
Publisher: Edward Elgar Publishing
ISBN: 1786439050
Category : Computers
Languages : en
Pages : 736
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Book Description
The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.
Author: Solon Barocas
Publisher: MIT Press
ISBN: 0262048612
Category : Computers
Languages : en
Pages : 341
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Book Description
An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility. • Introduces the technical and normative foundations of fairness in automated decision-making • Covers the formal and computational methods for characterizing and addressing problems • Provides a critical assessment of their intellectual foundations and practical utility • Features rich pedagogy and extensive instructor resources
Author: Osonde A. Osoba
Publisher: Rand Corporation
ISBN: 0833097636
Category : Computers
Languages : en
Pages : 45
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Book Description
Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.
