<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T23:35:05Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/126966" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/126966</identifier><datestamp>2022-12-19T19:17:24Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Antoinette Schoar.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Wang, Yupeng(Scientist in business management)Massachusetts Institute of Technology.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2020-09-03T16:45:46Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2020-09-03T16:45:46Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2020</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2020</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/126966</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1191221609</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, May, 2020</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from the official PDF of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 55-56).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Fintech mortgage lenders have become an increasingly important source of mortgage credit in the US. Using loan-level data on mortgages sold to Fannie Mae and Freddie Mac (GSEs), I find that compared to traditional lenders, Fintech lenders are more likely to address credit demand from low credit score borrowers. However, they may be able to exploit two frictions in the GSEs' pricing and securitization setup. First, Fintech loans tend to have more risk layers conditional on paying the same guarantee fee, which are charged 15 basis points less of interest rate but translate to 0.5% higher delinquency rate ex-post. Second, Fintech loans get prepaid more often (11%). They get cross-subsidies in the to-be-announced mortgage-backed-securities market since these loans are pooled together with low prepayment risk loans in the same contract.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Yupeng Wang.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Management Research</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="collection" lang="en_US">S.M.inManagementResearch Massachusetts Institute of Technology, Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">56 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">FinTech mortgage lenders solving or exploiting a friction? evidence on risk layering and prepayment risk of conforming loans</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Fin Tech mortgage lenders solving or exploiting a friction? evidence on risk layering and prepayment risk of conforming loans</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Evidence on risk layering and prepayment risk of conforming loans</dim:field>
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   <dim:field mdschema="mit" element="thesis" qualifier="degree" lang="en_US">Master</dim:field>
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   	&lt;Title>FinTech mortgage lenders solving or exploiting a friction? evidence on risk layering and prepayment risk of conforming loans&lt;/Title>
   	&lt;Subtitle>Fin Tech mortgage lenders solving or exploiting a friction? evidence on risk layering and prepayment risk of conforming loans&lt;/Subtitle>
   	&lt;Subtitle>Evidence on risk layering and prepayment risk of conforming loans&lt;/Subtitle>
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   	&lt;PublicationDate>2020&lt;/PublicationDate>
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        	&lt;DisplayName>Wang, Yupeng(Scientist in business management)Massachusetts Institute of Technology.&lt;/DisplayName>
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    &lt;Keyword>Sloan School of Management.&lt;/Keyword>
   	&lt;Abstract>Fintech mortgage lenders have become an increasingly important source of mortgage credit in the US. Using loan-level data on mortgages sold to Fannie Mae and Freddie Mac (GSEs), I find that compared to traditional lenders, Fintech lenders are more likely to address credit demand from low credit score borrowers. However, they may be able to exploit two frictions in the GSEs&amp;apos; pricing and securitization setup. First, Fintech loans tend to have more risk layers conditional on paying the same guarantee fee, which are charged 15 basis points less of interest rate but translate to 0.5% higher delinquency rate ex-post. Second, Fintech loans get prepaid more often (11%). They get cross-subsidies in the to-be-announced mortgage-backed-securities market since these loans are pooled together with low prepayment risk loans in the same contract.&lt;/Abstract>
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