While community banks have typically had a steady but smaller share of the overall mortgage lending business compared to their independent lenders, record-low interest rates have skyrocketed across the board in both purchase and refinancing volumes. Increased demand leads to higher profits – a welcome sight on any bank's balance sheet. However, given the volume in the current market, banks need to focus on managing mortgage pipeline risk to ensure the long-term health and stability of their mortgage business.
Many banks opt for a mandatory bulk commitment model in order to take advantage of the better rates at the best possible expense, and it's easy to see why. On average, mandatory delivery offers a quarter point or more improvement over best effort prices. Naturally, given bank managers' desire for constant returns, the bank mortgage divisions would opt for the delivery mechanism that produces a higher return on investment.
As is often the case, higher returns come with higher risk, and many banks typically manage the risk of mandatory execution using a combination of institutional / loan level knowledge, spreadsheets, and gut instinct from seasoned secondary marketing managers. In an average market, this strategy works because the pipeline is sized so that the secondary / capital markets department can use the "eyeball test" or spreadsheet to manage the bank's position on its commitments.
The current market is far from average, however, and when the volume reaches the point where the number of loans exceeds the department's ability to track each one individually, the "eyeball test" is no longer enough to ensure that the Bank fulfills its obligations and this avoids financial consequences that result from failure to deliver the promised loans. To truly manage the risks associated with mandatory execution, banks need to invest in more complex models, reports, and analysis to track market movements, accurately calculate expected and actual pull-through rates, and ultimately, maximize profitability.
For example, if a lender fails to meet a mandatory obligation, Fannie Mae and Freddie Mac typically charge a pair-off fee. Once upon a time, this only happened to a loss. However, the GSEs now pay the lenders' pair-off winnings, if any. In both cases, the GSEs charge an eighth of a point administration fee for mandatory pair-offs, and for bank lenders using the "eyeball test" method, this creates significant inefficiencies even if they receive a pair-off win. The GSEs charge an administration fee of 12.5 basis points.
With the help of predictive analytics and modeling, bank lenders can not only avoid mandatory pairings (both positive and negative), they can also avoid payouts for certain high-demand credit groups / types such as credit cards. B. Take advantage of low-balance loans Moving from bulk commitments to more individualized lending. The payouts available for individual commitments can be enormous, ranging from 30 to 300 basis points or more. The total cost of implementing a system to generate these payouts is typically less than six basis points, which is less than half of the management fee the GSEs charge for pair-offs. In addition, a bank can easily cover the cost of such a system with just two small loan payments (less than $ 225,000) per month.
While monthly production of $ 10 million is the oft-cited benchmark, banks can begin to take advantage of a more sophisticated strategy for mandatory execution with pipelines as low as $ 5 million as it not only helps maximize profitability, but The bank also provides flexibility if consumers need to change loan programs or lock pricing structures after the loan has been locked, or request an extension of the interest lock. Additionally, a more sophisticated mandatory execution strategy allows banks to be more strategic in maintaining versus releasing services if desired, by allowing the bank to make those decisions after the loans are closed.
Given the enormous size of the mortgage business currently available, banks would be themselves at a serious disadvantage if they did not take full advantage of this opportunity. Simply put, by avoiding the "eyeball test" in favor of advanced modeling, reporting, and analysis, you can better manage overall mandatory execution risk as the bank can more reliably predict monthly loan commitment revenues, avoid costly mandatory pairings and maximize the overall return on its loan sales .