—Credit Risk for New Loans Similar to Early 2000s—

• Shift to a higher percentage of home-purchase loans over refinance loans increased credit risk
• Higher share of investor, condo/co-op purchases and lower-documentation lending increased credit risk slightly, offsetting the lower risk of other underwriting metrics

IRVINE, Calif. — (BUSINESS WIRE) — June 20, 2017 — CoreLogic^® (NYSE: CLGX), a leading global property information, analytics and data-enabled solutions provider, today released its Q1 2017 CoreLogic Housing Credit Index (HCI^™) which measures trends in six home mortgage credit risk attributes. The HCI indicates the relative increase or decrease in credit risk for new home loan originations compared to prior periods. The six attributes are: borrower credit score, debt-to-income ratio (DTI), loan-to-value ratio (LTV), investor-owned status, condo/co-op share and documentation level.

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In Q1 2017, the HCI increased to 105.6, up 3.6 points from Q1 2016. Even with this increase, the level of credit risk in Q1 2017 is nearly the same as the average of 105.9 for the period of 2001 to 2003, a time frame that is considered to be a normal baseline for credit risk. The slight loosening in the credit index during the past year was partly due to a shift in the mix of purchase versus refinance originations because purchase loans exhibit higher risk attributes than refinanced loans. Beginning in Q1 2017, the HCI was revised to include a more comprehensive source of loan-level, non-agency, mortgage-backed securities data. The result is that the HCI more accurately captures the loans that exhibited higher risk features during the mid-2000s.

“Mortgage rates during the first quarter of 2017 were up about 0.5 percentage points from a year earlier,” said Dr. Frank Nothaft, chief economist for CoreLogic. “Since 2009, for every one-half percentage point increase in mortgage rates, the average credit score on refinance borrowers has dipped by 9 points, and this pattern will likely continue if mortgage rates move higher. That is because when rates rise, applications drop off and loan officers spend more time with the applicants that have less-than-perfect credit scores, require more documentation or have unique property issues.”

Nothaft also observed that investor activity and condo/co-op lending had increased in Q1 2017. “Overall credit risk for purchase loans was slightly higher compared with a year ago as the investor share and condo/co-op share increased. These increases offset lower-risk signals from the credit score, DTI and LTV attributes to result in an uptick in overall riskiness. Still, overall risk is similar to that of the early 2000s.”

HCI Highlights as of Q1 2017:

• Credit Score: The average credit score for homebuyers increased 7 points year over year between Q1 2016 and Q1 2017, rising from 734 to 741. In Q1 2017, the share of homebuyers with credit scores under 640 was less than 3 percent compared with 25 percent in 2001.
• Debt-to-Income: Holding steady at 36 percent, the average DTI for homebuyers in Q1 2017 was similar to Q1 2016. In Q1 2017, the share of homebuyers with DTIs greater than or equal to 43 percent was 24 percent, down slightly from 25 percent in Q1 2016, but up from 18 percent in 2001.
• Loan-to-Value: The LTV for homebuyers fell by 1.7 percentage points between Q1 2016 and Q1 2017 from 87.6 percent to 85.9 percent. In Q1 2017, the share of homebuyers with an LTV greater than or equal to 95 percent was 43 percent, down from 49 percent in Q1 2016 and up from 29 percent in 2001.
• Investor Share: The investor share of home-purchase loans increased from 4 percent in Q1 2016 to 5 percent in Q1 2017.
• Condo/Co-op Share: The share of home-purchase loans secured by a condominium or a co-op building increased from 10 percent in Q1 2016 to 12 percent in Q1 2017.
• Documentation Type: Low- or no-documentation loans remained a small part of the mortgage market, increasing from 2 percent to 3 percent of home-purchase loans during the past year.

For ongoing housing trends and data, visit the CoreLogic Insights Blog: http://www.corelogic.com/blog.

Methodology

The CoreLogic Housing Credit Index (HCI) measures the variation in mortgage credit risk attributes and uses loan attributes from mortgage loan servicing data that are combined in a principal component analysis (PCA) model. PCA can be used to reduce a complex data set (e.g., mortgage loan characteristics) to a lower dimension to reveal properties that underlie the data set.

The HCI combines six mortgage credit risk attributes, including borrower credit score, loan-to-value (LTV) ratio, debt-to-income (DTI) ratio, documentation level (full documentation of a borrower’s economic conditions or incomplete levels of documentation, including no documentation), status of investor-owned (whether property is a non-owner-occupied investment or owner-occupied primary residence and second home) and property type (whether property is a condominium or co-op). It spans more than 15 years and covers all loan products in both the prime and subprime lending segments and includes all 50 states and the District of Columbia, permitting peak-to-peak and trough-to-trough business cycle comparisons across the U.S. The CoreLogic Loan-Level Market Analytics data includes loan-level information, both current and historical, from servicers on active first-lien mortgages in the U.S., and the Non-Agency Residential Mortgage Backed Securities (RMBS) data includes loan-level information from the securitizers. In addition, CoreLogic public records data for the origination share by loan type (conventional conforming, government, jumbo) were used to adjust the combined servicing and securities data to assure that it reflects primary market shares. These changes across different dimensions are reflected in the HCI. A rising HCI indicates increasing credit risk, while a declining HCI indicates decreasing credit risk.

Source: CoreLogic

The data provided are for use only by the primary recipient or the primary recipient's publication or broadcast. These data may not be re-sold, republished or licensed to any other source, including publications and sources owned by the primary recipient's parent company without prior written permission from CoreLogic. Any CoreLogic data used for publication or broadcast, in whole or in part, must be sourced as coming from CoreLogic, a data and analytics company. For use with broadcast or web content, the citation must directly accompany first reference of the data. If the data are illustrated with maps, charts, graphs or other visual elements, the CoreLogic logo must be included on screen or web site. For questions, analysis or interpretation of the data contact Lori Guyton at lguyton@cvic.com or Bill Campbell at bill@campbelllewis.com. Data provided may not be modified without the prior written permission of CoreLogic. Do not use the data in any unlawful manner. These data are compiled from public records, contributory databases and proprietary analytics, and its accuracy depends upon these sources.

About CoreLogic

CoreLogic (NYSE: CLGX) is a leading global property information, analytics and data-enabled solutions provider. The company's combined data from public, contributory and proprietary sources includes over 4.5 billion records spanning more than 50 years, providing detailed coverage of property, mortgages and other encumbrances, consumer credit, tenancy, location, hazard risk and related performance information. The markets CoreLogic serves include real estate and mortgage finance, insurance, capital markets, and the public sector. CoreLogic delivers value to clients through unique data, analytics, workflow technology, advisory and managed services. Clients rely on CoreLogic to help identify and manage growth opportunities, improve performance and mitigate risk. Headquartered in Irvine, Calif., CoreLogic operates in North America, Western Europe and Asia Pacific. For more information, please visit www.corelogic.com.

CORELOGIC, CoreLogic Housing Credit Index (HCI), and the CoreLogic logo are trademarks of CoreLogic, Inc. and/or its subsidiaries.

Figures 1 through 3 include originations through March 2017 (Q1 2017)

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