Pipeline Pull-through Rate Analysis Explained

In this article, we’ll explain the key concepts related to pull-through rate analysis, and mortgage pipeline forecasting, and discuss its importance in deriving an accurate mortgage pipeline hedging recommendation. This article is an adaptation of Chapter 3 of the Mortgage Professionals Handbook titled “Pipeline Pull-Through Analysis” by MCT’s COO, Phil Rasori.

cartoon business man standing on top of a percent sign on top of a mountain holding binocularsMaintaining optimal hedge coverage mitigates risk between mortgage rate lock and funding, and is one of the most important responsibilities of the Secondary Manager (and their hedge advisor).

A key requirement for maintaining optimal coverage is accurate mortgage pipeline forecasting of the probability that a given application, and the pipeline more broadly, will “pull-through” to close and fund. Loan characteristics, market movements, and extraneous factors add further complexity to the forecast equation in order to accomplish successful mortgage pipeline risk management.


Table of Contents – Pull-Through Rate Analysis Explained


Read on to learn how pull-through forecasts affect how much hedge coverage a pipeline will need.


What is a Pull-Through Rate?

The Pull-Through Rate is the probability at a point in time that a given Interest Rate Lock Commitment (IRLC) will close and fund.

Correctly forecasting this rate is the single most important factor in generating an accurate hedge recommendation and accurate mortgage pipeline risk management. Effective mortgage pipeline forecasting is a key component of determining how much hedge coverage a pipeline will need.

This is different from an application conversion rate because we are measuring the probability of a loan application actually closing and funding. It is calculated by taking the total funded volume of a pipeline and dividing that number by the total locked volume.

Below is an example of the pull-through rate of a mortgage loan pipeline at a point in time. Please note that this is different from the “Forecasted Pull-Through Rate” which is a function of the pull-through analysis model that will be discussed later in this article.

Mortgage pipeline pull-through rate equation total funded volume + total lock volume = mortgage pipeline pull-through rate

Why Pull-Through Rates Matter for Mandatory Hedge Recommendations

As interest rates move up or down, loans will inevitably “fall out” of the pipeline due to any number of reasons. By analyzing what has happened in the past with each individual loan type alongside various market conditions, originators can confidently predict the probability of fallout and hedge only the percentage of loans that are expected to pull through.

“Forecasting a pipeline pull-through rate is the single most important factor in generating an accurate hedge recommendation and mortgage pipeline risk management.” – Phil Rasori, Chief Operations Officer at MCT, from Chapter 3 of the Mortgage Professionals Handbook
Read full chapter from handbook

Executing on a mandatory basis is facilitated by hedging your pipeline. Mortgage pipeline hedging allows a lender to neutralize interest rate-driven changes to loan value between the time a rate is locked with the borrower and the time the loan funds.

Once the associated pull-through ratio is taken into account, financial instruments called To-Be-Announced Mortgage-Backed-Security (TBA MBS) corresponding to the pull-through-adjusted open mortgage pipeline, can be sold as a hedge.

By selling the TBA MBS, you have entered into a short position. When you buy the TBA back in the future (to exit the position), the value of your short position will have moved in the opposite direction of the underlying asset (your “IRLC’”s in this case – Interest rate lock commitments).

Since the value of your IRLC’s are, in large part, derived from the TBA MBS market, TBA’s typically make an ideal hedge vehicle. Your short position effectively hedges your IRLC’s since they move in approximately equal and opposite directions. The volume of TBA’s to be sold for hedging purposes depends on your expected pull-through rate calculation.

graph illustrating the exact balance of TBA securities to locked loans

**While this graph illustrates the exact balance of TBA securities to locked loans, a more realistic representation of coverage would be around the 90% mark. For example, 1MM of locked loans with a 90% pull-through rate would be hedged by 900K of TBA securities.

Pull-through Rate Variability in the Open Mortgage Pipeline

In this section, we will explore the key concepts of fallout and pull-through illustrated in stages of the loan’s lifecycle from lock to hedge to funding. For example, if you have an 80% pull-through rate in your mortgage pipeline, then you have a 20% fallout rate.

Regardless of the type, origination channel, or purpose of the loan, the actual stage of the loan will be the most important factor to determine sensitivity to market movement. As the loan progresses through its natural stages toward funding, the borrower becomes increasingly committed to the loan. Especially after the appraisal has been paid, the borrower becomes financially invested in the loan and is much less likely to fall out.

High Pull-Through Rate Does Not Equate to Greater Hedge Performance!


As we look at pull-through over the course of the mortgage process, it is important to understand that a high pull-through rate does not necessarily translate to great hedge performance. The extent to which pull-through rates are correlated to the market (also known as market-driven pull-through variability) determines hedge costs and risks over time.

As a lender, you want to drive high pull-through rates for obvious reasons. But, as a capital markets manager, the consistency and predictability of pull-through rate is of primary importance.


How Lock Desk Operations & Loan Stage Affect Pull-Through Rate

The greatest control point that a lender possesses over the future behavior of their pipeline pull-through rate are through their lock desk policies.

When a lender guarantees an interest rate to a borrower in an Interest-Rate Lock Commitment (IRLC), the lender is left in an exposed position with regard to interest rate fluctuations in the market.

This is known as interest rate risk, and is the primary risk addressed by pipeline hedging.

Pushing the rate lock commitment further into the loan process will increase the probability that the loan will pull-through, regardless of loan characteristics.

two scenario equations of mortgage pipeline pull-through rates

The stage in which the loan resides is the most important variable influencing market-driven fallout. As the loan progresses, the borrower becomes more committed and less sensitive to market movements. Meaning, a borrower is less likely to take his/her business elsewhere even if interest rates have improved since locking.

Advancing the lock further into the loan process will increase pull-through and decrease variability, while pushing loans into stages closer to funding will increase pull-through rate, and reduce the chances of a borrower walking due to market conditions.

How Loan Origination Characteristics Affect Pull-Through Rate

Below are several characteristics of loans and borrowers that are taken into consideration with mortgage pipeline forecasting. Later, we overlay the market movement influence on these as well.

  • Purpose of the loan: pull-through is more stable for a purchase loan than a refinance given a change in interest rates.
  • Origination channel: rate locks generated from consumer-direct internet advertising tend to be more volatile than traditional realtor referrals.
  • Borrower sophistication: financially sophisticated borrowers have more lender options and are alerted to market changes at a faster rate.

picture of a graph describing market driven mortgage pipeline pull-through rate variables which make the rate either more stable or less

Individual branches and loan officers may also have unique influences on pull-through which can be measured and forecasted for improved hedge performance.

How Interest Rate Changes Affect Pull-Through Rates

picture of line graph showing the relationship between pull-through rate and interest ratePull-through rate forecasts are used to derive hedging coverage recommendations until the loan is funded or falls out. During this phase, the hedging coverage is adjusted based on changes to the pull-through rate, which occur due to market moves as well as changes in loans’ stages change.

There is an inverse relationship between pull-through rates and interest rates. As interest rates rise, borrowers want to stay with their lower rate which increases the likelihood that the loans will pull-through to funding. As interest rates decrease, borrowers are more likely to jump ship with another lender to go for the lowered rate.

This relationship is the primary source of risk posed to a lender engaged in pipeline hedging.

When interest rates fall, the current IRLC becomes more valuable for the lender, however, fewer of these rate locks can be expected to fund. When interest rates rise the current IRLC loses value from the lender’s perspective, but a greater percentage of these locks will be expected to fund. Note that the lock’s sensitivity to rates changes as loans’ stages change, as described above.

How Fallout Affects a Pull-Through Rate Analysis

At this final stage, the lock completes its lifecycle when it either falls out and/or is funded. For the purposes of pull-through rate, we will discuss the two different types of fallout and how they affect the final calculations.

If a rate lock commitment does not carry through to funding, the lock is recorded as a fall-out. While the lender guarantees the rate and price, the borrower doesn’t guarantee that they will close, leading to the IRLC not closing and “falling out” of the pipeline.

The most common cause of fallout unrelated to market movement is the underlying loan being denied at underwriting due to borrower credit or appraisal value issues.

Soft Fallout in a Mortgage Loan Pipeline

In the scenario of a Soft Fallout result, the terms of the loan are modified to the detriment of the lender in an effort to keep the loan from being cancelled. Soft fallout occurs primarily due to rate renegotiations.

When interest rates fall, pull-through rate goes down because the borrower is more likely to “jump ship” to get a better rate. In order to avoid a complete loss, the lender might agree to reduce the interest rate and/or points charged to keep the borrower from cancelling.

Renegotiated locks are not equivalent to fully pulling through because there is a deterioration in profitability for the lender.

Calculating soft fallout is done on a case-by-case basis with the percentage of total profitability detriment equalling the percentage of effect on the total pull-through of that loan. For example, if the renegotiation resulted in a 50% decrease in profitability for the lender, the soft fallout would be 50% the normal hard fallout effect.

How about interest rate lock extensions? If there is no detrimental effect to the loan’s profitability even if a rate if renegotiated, it is not a soft fallout. An interest rate lock extension is not classified as soft fallout because it’s due to operational issues, not markets. Lock extensions can be charged to the borrower to avoid negative effect on profitability.

Hard Fallout in a Mortgage Loan Pipeline

When hard fallout happens the IRLC is completely terminated and no part of the original rate or pricing guarantee will exist. For example, the loan application can be cancelled by the borrower, declined by underwriting, or the borrower could jump ship to another lender for a more favorable rate or term.

To calculate hard fallout, find the difference between the total locked volume and total funded volume of your mortgage pipeline. This calculation does not happen at one time but takes place over time as more loan data is gathered.

How to Forecast Market Adjusted Pull-Through Rate

Your zero market pull-through rate is the baseline measure for pull-through and represents your pull-through in a neutral interest rate environment. The baseline pull-through rate is calculated for each stage. However, the baseline pull-through changes as interest rates move.  Through regression analysis, we can quantify how much influence interest rate changes have on your baseline pull-through. We call this measure the Market Beta.

picture of the five steps of regression analysis of forecasting market adjusted mortgage pipeline pull-through rate

Complete steps to make a Pull-through Rate Analysis:

  1. Access data on the loans that have been in the pipeline and have either funded or fallen out. Check the Market Levels on the initial rate-lock date for all units.
  2. Note the market rate of each loan when the IRLC began, then compare that to the market rate when the loan exited the pipeline. This is the market experience.
  3. All of the loans should then be grouped into tranches based on their magnitude and direction.
  4. Separately, calculate the Pull-through rates for each of the tranches (remember, it was total funded volume divided by total locked volume).
  5. Out of this scatterplot data, you create a regression, or a line of prediction through the data that will illustrate the percentage effect that each bps market movement will have on your baseline pull-through rate. The regression is calculated against loan pricing so the line will be downward sloping. The line of best fit is a Market Pull-Through Curve, also referred to as a the Pull-Through Beta or Market Beta.
  6. When you look at the pull-through percentage when the market is at zero (not moving), that is when you have identified your baseline pull-through figures, also known as Zero Market Movement figures.equation for a mortgage pipeline pull-through rate analysis, tranche pull-through beta x market movement experience = market adjustment
  7. Apply the market adjustment in real time to the slope you have created to determine the market adjustment that you need to make to that baseline pull-through figure to generate the pull-through forecast.

line chart image showing the relationship between mortgage pipeline pull-through % and market movement

Lastly, take the weighted average of the resultant pull-through values. This is your forecasted locked pipeline pull-through rate!


Get Started with a Pipeline Pull-Through Analysis

Calculating a forecasted pull-through rate may be the most critical factor involved in generating a hedge recommendation, but the fundamental building block of an accurate forecast is a robust historical pull-through analysis.

The lender that draws upon the current environment from the borrower perspective along with historical data trends will be able to generate the most accurate pull-through forecasts and the most effective hedge strategies.

Schedule a meeting with MCT and get started with a robust Pipeline Pull-Through Analysis, to examine how you can improve efficiency and profitability.


Further Learning About Mortgage Pipeline Hedging Strategies


By reading this overview, we hope you have obtained a comprehensive view of how pull-through rates affect hedging on a mandatory basis. If you would like to learn more, we encourage you to read Chapter 3 of the Mortgage Professionals Handbook titled “Pipeline Pull-Through Analysis” by MCT’s COO, Phil Rasori, on which this article is closely based.

Have questions and comments? Sometimes it seems like the more you learn, the less you know, that’s why the mission of MCT is to provide the leading capital markets content to bring clarity to complex subjects such as this.

Contact us to learn more about the many ways that we support lenders in hedging their mortgage pipelines.


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