Last edited by Mausho
Thursday, July 30, 2020 | History

4 edition of Under-specified models and detection of discrimination in mortgage lending found in the catalog.

Under-specified models and detection of discrimination in mortgage lending

Jason Lynn Dietrich

Under-specified models and detection of discrimination in mortgage lending

by Jason Lynn Dietrich

  • 351 Want to read
  • 1 Currently reading

Published by Office of the Comptroller of the Currency in Washington, DC .
Written in English

    Subjects:
  • Discrimination in mortgage loans.,
  • Mortgage loans.

  • Edition Notes

    Statementby Jason Dietrich.
    SeriesEconomic and policy analysis working paper ;, 2003-2, Economic and policy analysis working paper (2000 : Online) ;, 2003-2.
    ContributionsUnited States. Office of the Comptroller of the Currency.
    Classifications
    LC ClassificationsHG2401
    The Physical Object
    FormatElectronic resource
    ID Numbers
    Open LibraryOL3390580M
    LC Control Number2004620327

      The results regarding to limit of detection (LOD) and limit of quantitation (LOQ) for LEVO, PRFX, GATI, SPAR, MOXI and BALO were found to be .   This model allows examiners to match minority and nonminority pairs of applicants with similar credit characteristics, but different loan outcomes, for a more extensive fair lending review. Once the pairs are selected, examiners pull the credit files for the applicants to determine if discrimination played a part in the credit granting process.

    Exploring Racial Discrimination in Mortgage Lending: A Call for Greater Transparency Speech Detection. Oh dear AI models used to flag hate speech online are, er, racist against black people Many of the books and articles in this area cover a wide range of topics. Below is a list of a few of them, sorted alphabetically by title.   4 Conclusion. This paper has studied artificial neural network and linear regression models to predict credit default. Both the system has been trained on the loan lending data provided by Results of both the system have shown an equal effect on the data set and thus are very effective with the accuracy of % by artificial neural network and %.

    STUDY DESIGN. As noted in Chapter 1, the HDS audit involves 60 sites and is a multiphase study: Phase I, including 20 sites, began in ; Phase II began in ; and Phase III will begin in In Phase I, an attempt is being made to obtain national estimates of disparate treatment in home seeking among African American and Hispanic groups; these estimates will be used to measure.   Most of the mortgage lending cases brought by the Department under the Fair Housing Act and Equal Credit Opportunity Act have alleged discrimination based on race or color. Some of the Department's cases have also alleged that municipalities and other local government entities violated the Fair Housing Act when they denied permits or zoning.


Share this book
You might also like
CD of music to accompany Soweto Blues

CD of music to accompany Soweto Blues

Your marriage and family living

Your marriage and family living

Advertising in a recession

Advertising in a recession

My radio radio

My radio radio

catalogue of classed growth claret, burgundy, port, champagne and inexpensive French wines and sherry, which will be sold at auction by Bonhams at their Montpelier Galleries...on Monday, January 19th, 1981.

catalogue of classed growth claret, burgundy, port, champagne and inexpensive French wines and sherry, which will be sold at auction by Bonhams at their Montpelier Galleries...on Monday, January 19th, 1981.

Kali, the mother

Kali, the mother

The First One Hundred Days of President Hillary Rodham Clinton

The First One Hundred Days of President Hillary Rodham Clinton

Digging up Jerusalem.

Digging up Jerusalem.

Oil and gas developments in Pennsylvania in 1986, by John A. Harper

Oil and gas developments in Pennsylvania in 1986, by John A. Harper

Preliminary study for an economic recovery programme for the West Midlands

Preliminary study for an economic recovery programme for the West Midlands

Jewellery

Jewellery

Adventures of an ordinary mind.

Adventures of an ordinary mind.

Path to Enlightenment (Path to Enlightenment)

Path to Enlightenment (Path to Enlightenment)

Eyecandy

Eyecandy

Under-specified models and detection of discrimination in mortgage lending by Jason Lynn Dietrich Download PDF EPUB FB2

Under-specified Models and Detection of Discrimination in Mortgage Lending Jason Dietrich Office of the Comptroller of the Currency Economic and Policy Analysis Working Paper March Abstract: Most empirical studies of discrimination in mortgage lending can be criticized for omitted variable bias.

Get this from a library. Under-specified models and detection of discrimination in mortgage lending. [Jason Lynn Dietrich; United States. Office of the Comptroller of the Currency.] -- "Most empirical studies of discrimination in mortgage lending can be criticized for omitted variable bias.

With access to data and policy guidelines typically unavailable to researchers, the OCC is. Abstract. Most empirical studies of discrimination in mortgage lending can be criticized for omitted variable bias. With access to data and policy guidelines typically unavailable to researchers, the OCC is in a unique position to assess the importance of omitted variables on fair lending models.

Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending Article in The Journal of Real Estate Finance and Economics 31(1) February with 13 ReadsAuthor: Jason Dietrich. This study examines how omitted variables affect underwriting models the OCC estimates during fair lending examinations.

The purpose is to assess the effects of omitted variable bias common to most studies of discrimination in mortgage lending. The results show omitted variables have an important impact on both the estimate of the effect of race and on the identification of outliers Cited by: 8.

Downloadable (with restrictions). This study examines how omitted variables affect underwriting models the OCC estimates during fair lending examinations. The purpose is to assess the effects of omitted variable bias common to most studies of discrimination in mortgage lending.

The results show omitted variables have an important impact on both the estimate of the effect of race and on the. Under-Specified Models and Detection of Discrimination: A Case Study of Mortgage Lending Journal of Real Estate Finance and Economics () Jason Dietrich.

Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending. The purpose is to assess the effects of omitted variable bias common to most studies of discrimination in mortgage lending.

The results show omitted variables have an important impact on both the estimate of the effect of race and on the. Jason Dietrich. "Under-specified models and detection of discrimination: A case study of mortgage lending," Journal of Real Estate Finance and Economics, 31(1), Author contact info.

[email protected]   An analysis of current findings on mortgage-lending discrimination and suggestions for new procedures to improve its detection. Inhomeownership in the United States stood at an all-time high of percent, but the homeownership rate was more than 50 percent higher for non-Hispanic whites than for blacks or s: 2.

An analysis of current findings on mortgage-lending discrimination and suggestions for new procedures to improve its detection. Inhomeownership in the United States stood at an all-time high of percent, but the homeownership rate was more than 50 percent higher for non-Hispanic whites than for blacks or Hispanics.

Homeownership is the most common method for wealth. Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending.

Jason Dietrich Pages Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending. Jason Dietrich Pages A Markov Model of Bank Failure Estimated Using an Information-Theoretic Approach (WP ) March 03/15/ Under-specified Models and Detection of Discrimination in Mortgage Lending (WP ) March 09/15/ A Cross-Country Analysis of the Bank Supervisory Framework and Bank Performance (WP ) September 06/15/ Is there statistical evidence of racial discrimination in home mortgage markets.

The Boston Fed recently addressed this concern head-on by collecting all available data from loan applications in Boston. They find that the extent of discrimination is reduced after one accounts for all of the confounding variables measured in these applications but that it remains statistically significant.

A Markov Model of Bank Failure Estimated Using an Information-Theoretic Approach (WP ) March Economics Working Paper: 03/15/ Under-specified Models and Detection of Discrimination in Mortgage Lending (WP ) March Economics Working Paper: 03/12/ Quarterly Report on Bank Trading and Derivatives Activities: Fourth.

Journals & Books; Register Sign in. Under-specified models and detection of discrimination: a case study of mortgage lending. The J. Real Estate Finan. Econ., 31 (1) (), pp. Stengel M., Glennon ting statistical models of mortgage lending discrimination: a bank‐specific analysis.

Real Estate Econ., 27 (2) (), pp. how they define discrimination and how they detect it. You should see how economists model discrimination in the labor market and what they can say about it in the markets for automobiles, real estate and lending.

Lastly, you should understand what affirmative action is; how, why, and when it came about; and what forms of it. Mortgage Lending Discrimination and Differential Volatility in Neigh borhood Property Values | Chapter 11 | Current Strategies in Economics and Management Vol.4 Observations of significant differences in loan terms between demographically distinct groups of borrowers are often interpreted as evidence of demographic discrimination.

The competitive nature of mortgage lending undermines. Examiners also test the institution's actual lending record for specific types of discrimination, such as pricing discrimination in mortgage lending.

A specialized Fair Lending Enforcement Section on the Board's staff works closely with staff at the 12 Reserve Banks across the country to provide guidance on fair lending matters and to ensure. PSD2 requires strong customer authentication when payments are initiated, however there are exemptions from strong customer authentication for those who can keep their fraud levels under specified reference fraud rates.

This allows payments under. EY, a global leader in assurance, tax, transaction and advisory services, piloted fairness capabilities in the Fairlearn toolkit on a machine learning model the firm built for automated lending decisions. The model was trained on mortgage adjudication data from banks that includes transaction and payment history and credit bureau information.

Free Online Library: Statement by John P. LaWare, Chairman, Federal Financial Institutions Examination Council and Member, Board of Governors of the Federal Reserve System, before the Committee on Banking, Housing, and Urban Affairs, U.S.

Senate, Febru (Statements to Congress) (Transcript) by "Federal Reserve Bulletin"; Banking, finance and accounting. prevent discrimination in lending models. Hiring and credit scoring algorithms can exacerbate inequities due to biased data. Applications such as facial recognition can be inaccurate and biased.

This can be demonstrated in the P2P lending industry. P2P business platform models depend on proprietary and complex algorithms. The interest rates applied.