Credit Data and Scoring Book

Credit Data and Scoring

  • Author : Eric Rosenblatt
  • Publisher : Academic Press
  • Release Date : 2020-01-07
  • Genre: Business & Economics
  • Pages : 274
  • ISBN 10 : 9780128188163

Credit Data and Scoring Excerpt :

Credit Data and Scoring: The First Triumph of Big Data and Big Algorithms illuminates the often-hidden practice of predicting an individual’s economic responsibility. Written by a leading practitioner, it examines the international implications of US leadership in credit scoring and what other countries have learned from it in building their own systems. Through its comprehensive contemporary perspective, the book also explores how algorithms and big data are driving the future of credit scoring. By revealing a new big picture and data comparisons, it delivers useful insights into legal, regulatory and data manipulation. Provides insights into credit scoring goals and methods Examines U.S leadership in developing credit data and algorithms and how other countries depart from it Analyzes the growing influence of algorithms in data scoring

Handbook of Credit Scoring Book
Score: 4
From 3 Ratings

Handbook of Credit Scoring

  • Author : Elizabeth Mays
  • Publisher : Global Professional Publishi
  • Release Date : 2001-06
  • Genre: Business & Economics
  • Pages : 382
  • ISBN 10 : 1888988010

Handbook of Credit Scoring Excerpt :

· Credit scoring is a vital and sometimes misunderstood tool in financial services · Evaluates the different systems available Bankers and lenders depend on credit scoring to determine the best credit risks--and ensure maximum profit and security from their loan portfolios. Handbook of Credit Scoring offers the insights of a select group of experts on credit scoring systems. Topics include: Scoring Applications, Generic and Customized Scoring Models, Using consumer credit information, Scorecard modelling with continuous vs. Classed variables, Basic scorecard Development and Validation, Going beyond Credit Score, Data mining, Scorecard collection strategies, project management for Credit Scoring

Intelligent Credit Scoring Book

Intelligent Credit Scoring

  • Author : Naeem Siddiqi
  • Publisher : John Wiley & Sons
  • Release Date : 2017-01-10
  • Genre: Business & Economics
  • Pages : 464
  • ISBN 10 : 9781119279150

Intelligent Credit Scoring Excerpt :

A better development and implementation framework for credit risk scorecards Intelligent Credit Scoring presents a business-oriented process for the development and implementation of risk prediction scorecards. The credit scorecard is a powerful tool for measuring the risk of individual borrowers, gauging overall risk exposure and developing analytically driven, risk-adjusted strategies for existing customers. In the past 10 years, hundreds of banks worldwide have brought the process of developing credit scoring models in-house, while ‘credit scores' have become a frequent topic of conversation in many countries where bureau scores are used broadly. In the United States, the ‘FICO' and ‘Vantage' scores continue to be discussed by borrowers hoping to get a better deal from the banks. While knowledge of the statistical processes around building credit scorecards is common, the business context and intelligence that allows you to build better, more robust, and ultimately more intelligent, scorecards is not. As the follow-up to Credit Risk Scorecards, this updated second edition includes new detailed examples, new real-world stories, new diagrams, deeper discussion on topics including WOE curves, the latest trends that expand scorecard functionality and new in-depth analyses in every chapter. Expanded coverage includes new chapters on defining infrastructure for in-house credit scoring, validation, governance, and Big Data. Black box scorecard development by isolated teams has resulted in statistically valid, but operationally unacceptable models at times. This book shows you how various personas in a financial institution can work together to create more intelligent scorecards, to avoid disasters, and facilitate better decision making. Key items discussed include: Following a clear step by step framework for development, implementation, and beyond Lots of real life tips and hints on how to detect and fix data issues How to realise bigger ROI from credit scoring u

Credit Scoring and Its Applications  Second Edition Book

Credit Scoring and Its Applications Second Edition

  • Author : Lyn Thomas
  • Publisher : SIAM
  • Release Date : 2017-08-16
  • Genre: Business & Economics
  • Pages : 373
  • ISBN 10 : 9781611974553

Credit Scoring and Its Applications Second Edition Excerpt :

Credit Scoring and Its Applications is recognized as the bible of credit scoring. It contains a comprehensive review of the objectives, methods, and practical implementation of credit and behavioral scoring. The authors review principles of the statistical and operations research methods used in building scorecards, as well as the advantages and disadvantages of each approach. The book contains a description of practical problems encountered in building, using, and monitoring scorecards and examines some of the country-specific issues in bankruptcy, equal opportunities, and privacy legislation. It contains a discussion of economic theories of consumers' use of credit, and readers will gain an understanding of what lending institutions seek to achieve by using credit scoring and the changes in their objectives. New to the second edition are lessons that can be learned for operations research model building from the global financial crisis, current applications of scoring, discussions on the Basel Accords and their requirements for scoring, new methods for scorecard building and new expanded sections on ways of measuring scorecard performance. And survival analysis for credit scoring. Other unique features include methods of monitoring scorecards and deciding when to update them, as well as different applications of scoring, including direct marketing, profit scoring, tax inspection, prisoner release, and payment of fines.

Credit Risk Scorecards Book

Credit Risk Scorecards

  • Author : Naeem Siddiqi
  • Publisher : John Wiley & Sons
  • Release Date : 2012-06-29
  • Genre: Business & Economics
  • Pages : 208
  • ISBN 10 : 9781118429167

Credit Risk Scorecards Excerpt :

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 R

Readings in Credit Scoring Book

Readings in Credit Scoring

  • Author : Lyn Carey Thomas
  • Publisher : Oxford University Press on Demand
  • Release Date : 2004
  • Genre: Business & Economics
  • Pages : 321
  • ISBN 10 : 0198527977

Readings in Credit Scoring Excerpt :

Credit scoring is one of the most successful applications of statistical and management science techniques in finance in the last forty years. This unique collection of recent papers, with comments by experts in the field, provides excellent coverage of recent developments, advances and sims in credit scoring. Aimed at statisticians, economists, operational researchers and mathematicians working in both industry and academia, and to all working on credit scoring and data mining, it is an invaluable source of reference.

Credit Scoring  Response Modeling  and Insurance Rating Book
Score: 5
From 1 Ratings

Credit Scoring Response Modeling and Insurance Rating

  • Author : S. Finlay
  • Publisher : Springer
  • Release Date : 2012-06-26
  • Genre: Business & Economics
  • Pages : 297
  • ISBN 10 : 9781137031693

Credit Scoring Response Modeling and Insurance Rating Excerpt :

A guide on how Predictive Analytics is applied and widely used by organizations such as banks, insurance providers, supermarkets and governments to drive the decisions they make about their customers, demonstrating who to target with a promotional offer, who to give a credit card to and the premium someone should pay for home insurance.

Data Analysis and Applications 4 Book

Data Analysis and Applications 4

  • Author : Andreas Makrides
  • Publisher : John Wiley & Sons
  • Release Date : 2020-04-09
  • Genre: Mathematics
  • Pages : 310
  • ISBN 10 : 9781119721581

Data Analysis and Applications 4 Excerpt :

Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications are appearing, covering the need for information from all fields of science and engineering, thanks to the universal relevance of data analysis and statistics packages. This book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working at the forefront of data analysis. The chapters included in this volume represent a cross-section of current concerns and research interests in these scientific areas. The material is divided into three parts: Financial Data Analysis and Methods, Statistics and Stochastic Data Analysis and Methods, and Demographic Methods and Data Analysis- providing the reader with both theoretical and applied information on data analysis methods, models and techniques and appropriate applications.

The Credit Scoring Toolkit Book

The Credit Scoring Toolkit

  • Author : Raymond Anderson
  • Publisher : Oxford University Press
  • Release Date : 2007-08-30
  • Genre: Business & Economics
  • Pages : 731
  • ISBN 10 : 0199226407

The Credit Scoring Toolkit Excerpt :

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.

Credit Scoring  Response Modelling and Insurance Rating Book

Credit Scoring Response Modelling and Insurance Rating

  • Author : S. Finlay
  • Publisher : Springer
  • Release Date : 2010-10-27
  • Genre: Business & Economics
  • Pages : 280
  • ISBN 10 : 9780230298989

Credit Scoring Response Modelling and Insurance Rating Excerpt :

Every year, financial services organizations make billions of dollars worth of decisions using automated systems. For example, who to give a credit card to and the premium someone should pay for their home insurance. This book explains how the forecasting models, that lie at the heart of these systems, are developed and deployed.

Big Data in Context Book

Big Data in Context

  • Author : Thomas Hoeren
  • Publisher : Springer
  • Release Date : 2017-10-17
  • Genre: Law
  • Pages : 120
  • ISBN 10 : 9783319624617

Big Data in Context Excerpt :

This book is open access under a CC BY 4.0 license. This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.This volume was produced as a part of the ABIDA project (Assessing Big Data, 01IS15016A-F). ABIDA is a four-year collaborative project funded by the Federal Ministry of Education and Research. However the views and opinions expressed in this book reflect only the authors’ point of view and not necessarily those of all members of the ABIDA project or the Federal Ministry of Education and Research.

Credit Scoring Book

Credit Scoring

  • Author : Murray Bailey
  • Publisher : Unknown
  • Release Date : 2020-03-16
  • Genre: Uncategoriezed
  • Pages : 240
  • ISBN 10 : 1657480399

Credit Scoring Excerpt :

Required reading for anyone in the field of credit scoring. It presents the foundations but also provides users' interpretations of the basic principles. It offers guidance on setting cut-offs, strategies, validation, use of bureau data and monitoring. The book concludes with more advanced chapters on alternative technologies as well as ideal on profit scoring, customer scoring, and recession scoring.

Retail Credit Risk Management Book

Retail Credit Risk Management

  • Author : M. Anolli
  • Publisher : Springer
  • Release Date : 2013-01-29
  • Genre: Business & Economics
  • Pages : 236
  • ISBN 10 : 9781137006769

Retail Credit Risk Management Excerpt :

Introducing the fundamentals of retail credit risk management, this book provides a broad and applied investigation of the related modeling theory and methods, and explores the interconnections of risk management, by focusing on retail and the constant reference to the implications of the financial crisis for credit risk management.

Data Science for Economics and Finance Book

Data Science for Economics and Finance

  • Author : Sergio Consoli
  • Publisher : Springer Nature
  • Release Date : 2021
  • Genre: Application software
  • Pages : 355
  • ISBN 10 : 9783030668914

Data Science for Economics and Finance Excerpt :

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Creditworthy Book
Score: 4.5
From 2 Ratings


  • Author : Josh Lauer
  • Publisher : Columbia University Press
  • Release Date : 2017-07-25
  • Genre: History
  • Pages : 352
  • ISBN 10 : 9780231544627

Creditworthy Excerpt :

The first consumer credit bureaus appeared in the 1870s and quickly amassed huge archives of deeply personal information. Today, the three leading credit bureaus are among the most powerful institutions in modern life—yet we know almost nothing about them. Experian, Equifax, and TransUnion are multi-billion-dollar corporations that track our movements, spending behavior, and financial status. This data is used to predict our riskiness as borrowers and to judge our trustworthiness and value in a broad array of contexts, from insurance and marketing to employment and housing. In Creditworthy, the first comprehensive history of this crucial American institution, Josh Lauer explores the evolution of credit reporting from its nineteenth-century origins to the rise of the modern consumer data industry. By revealing the sophistication of early credit reporting networks, Creditworthy highlights the leading role that commercial surveillance has played—ahead of state surveillance systems—in monitoring the economic lives of Americans. Lauer charts how credit reporting grew from an industry that relied on personal knowledge of consumers to one that employs sophisticated algorithms to determine a person's trustworthiness. Ultimately, Lauer argues that by converting individual reputations into brief written reports—and, later, credit ratings and credit scores—credit bureaus did something more profound: they invented the modern concept of financial identity. Creditworthy reminds us that creditworthiness is never just about economic "facts." It is fundamentally concerned with—and determines—our social standing as an honest, reliable, profit-generating person.