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Getting a lead on servicers’ need for speed
admin | February 28, 2020
This document is intended for institutional investors and is not subject to all of the independence and disclosure standards applicable to debt research reports prepared for retail investors.
Mortgage servicers clearly have an impact on whether borrowers prepay, and comparing servicer performance in 2018 and 2019 shows that slower servicers tend to remain slower and faster servicers tend to remain faster. However, the market matters. Servicer speeds in years with heavy refinancing correlate more strongly with other refi years than with years where turnover becomes a bigger part of the mix.
Servicer prepayment behavior in 2018 helped predict speeds in 2019
Comparing servicers’ relative prepayment performance from 2018 to 2019 shows a correlation of 0.59 year-over-year for the 150 largest conventional servicers (Exhibit 1). A positive number indicates the servicer’s loans prepay faster than expected. Most fast servicers remained fast, and slow servicers remained slow—112 servicers, almost 75% of the sample, did not flip across the average speed line from 2018 to 2019.
Exhibit 1: Servicer performance in 2018 helped predict speed in 2019
Note: Servicer performance is the percentage faster or slower that servicer’s loans prepaid compared to a comparable cohort of all loans. The comparison controls for a servicer’s mix of factors such as loan balance and geography to try to measure a servicer’s unique contribution. A score of +25 represents 25% faster than the market benchmark, and -25 represents 25% slower. Performance in 2018 includes the 12 months ending December 2018, and performance in 2019 includes the 12 months ending December 2019. Data includes Fannie Mae and Freddie Mac 30-year fixed rate loans. Source: Fannie Mae, Freddie Mac, eMBS, Amherst Pierpont Securities
Servicer performance isn’t perfectly correlated from year to year. United Shore, for example, was slightly slower than average in 2018. However, that servicer priced mortgages more aggressively in 2019, causing the servicer to become one of the fastest servicers. Another difference is that 2018 was primarily a turnover environment while 2019 was primarily a refinance environment. A servicer with aggressive refinancing practices won’t necessarily be faster when purchase loans dominate production.
Comparing 2019 servicer performance to 2016 pairs two years with relatively heavy refinancing—refinanced loans were roughly 53% of GSE production in both years. The correlation between servicer performance from 2016 to 2019 is stronger at 0.75, suggesting that servicers’ refinancing behavior is roughly consistent, although other factors beyond servicer alone also matter even after controlling for loan balance, geography and the like.
Exhibit 2: Servicer performance in 2019 is more strongly correlated to the refinance environment of 2016.
Note: Servicer performance is the percentage faster or slower that servicer’s loans prepaid compared to a comparable cohort of all loans. The comparison controls for a servicer’s mix of factors such as loan balance and geography to try to measure a servicer’s unique contribution. A score of +25 represents 25% faster than the market benchmark, and -25 represents 25% slower. Performance in 2018 includes the 12 months ending December 2018, and performance in 2019 includes the 12 months ending December 2019. Data includes Fannie Mae and Freddie Mac 30-year fixed rate loans. Source: Fannie Mae, Freddie Mac, eMBS, Amherst Pierpont Securities
The market routinely trades pools from different servicers at different prices in expectation of different prepayment speeds. The data show good reasons for that, especially when markets become dominated by refinancing.
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