Facing structural limits on origination capacity, lenders often pull the price lever, but with blunt results; better pricing analytics and technology can improve spreads.
Mortgage lenders are losing operational flexibility. They face constraints as never before: the impact of new regulation, balance sheet evolution, fickle investor demand and a less nimble processing capability. As a result, lenders’ ability to “turn on a dime” and profitably originate the product de jour has diminished.
While seasoned mortgage bankers can pull out a tried-and-true toolkit to manage higher volumes, there are drawbacks with each tactic in today’s environment.
Enlarging the processing staff could solve periodic problems with under-capacity, for example, but this surge capacity is too expensive to hold when volumes recede.
Some lenders have considered outsourcing fulfillment to reduce costs, but fear the operational risk given the quality required to issue QM-compliant loans. And while tightening underwriting may improve risk-adjusted returns, it can handicap the sales staff and lower consideration from brokers.
Inevitably, most lenders settle on pricing as the throttle to control origination volumes. But to outperform competitors, a growing number of progressive players are bringing new analytics and technology into the pricing process.
To reap the available incremental spread on capped origination volume, successful analytic mortgage pricing requires three fundamental changes. First, analytically-driven originators need to price against market-by-market competitive pricing benchmarks for each product. Second, these measures of relative competitive position rely on a robust technology platform that can provide daily updates on optimal pricing position. And third, to assure cohesive execution in the field, close coordination with the sales team is needed, especially to manage exception pricing.
Based on Novantas research and client work, advanced mortgage pricing can typically provide a near-term origination margin lift of 10 to 20 basis points. And the long-term potential — as the industry moves into a different rate environment and the organization hones analytic margin/volume tradeoffs — will be higher.
The limitations on management flexibility in the mortgage industry are legion. While each originator faces a unique combination of issues that inhibits the ability to simply push for maximum volume, several challenges are pervasive:
Limited capacity for non-conforming jumbo loans. For originators willing to stretch, one option is to go after high-dollar transactions involving upscale properties and affluent borrowers. These credits are prized for their returns, and bank originators see added value in the cross-sell potential with an elite clientele.
The catch, however, is reduced funding availability for this type of asset. Balance sheet capacity is contracting for most banks. Risk and liquidity standards are tighter in the new regulatory environment, and rising loan-to-deposit ratios are forcing more careful choices about the use of core funding.
The alternative — selling to private investors — exposes the bank to what has proven to be fickle investor demand. While some originators have found buyers for jumbos, these investors have their own constraints and changing preferences, which means this funding source can readily dry up on little notice. This leaves originators uncertain on whether to focus on volume or price at any given point.
General balance sheet constraints for major players. With the introduction of Basel III and other regulations (such as the leverage ratio specified by Dodd-Frank for systematically important financial institutions), major banks see far less profit motivation to carry mortgage assets on the balance sheet. The situation has degraded to the point where in some instances, using balance sheet funding to deliver specialized mortgage products to a high-value customer group is becoming more of a “loss-leader” program to cement relationships and open the door for other kinds of cross-sell.
Dodd-Frank’s rules on qualified mortgages have further complicated balance sheet decisions. Exposed to higher legal risk and regulatory pressure when extending credit into higher risk tiers, banks now must ration non-QM production. Tranches of this type of origination must be carefully selected in order to ensure an adequate return, but high selectivity is difficult to achieve in a retail channel environment.
Slowed origination. Processing capacity has been slashed as the massive post-recession refinancing wave has subsided. Meanwhile new regulatory requirements have increased the complexity of required documentation. While lenders can “slow-walk” their origination times, they face undermining their competitive edge with customers.
Transformational digitization is on the drawing board for many major originators. But for now, traditional, manually-intensive processing dominates. Many originators still must manually touch each loan in the pipeline, slowing turnaround times on applications.
Capacity Management Toolkit
Savvy originators have faced constraints before and have a familiar toolkit of tactical responses, everything from extending lock periods, to expanding origination staff, to outsource fulfillment, to tightening underwriting. But each has its drawbacks (Figure 1: Drawbacks of Traditional Performance Levers).
The fallback tactic is to pull the price lever, often seen as the “one sure way” to reduce volume without the drawbacks identified in Figure 1. Unfortunately, money is frequently left on the table by blunt-force decisions, for example, bumping up rates by an eighth of a point across the board. Originators typically lack the analytics to know, for example, “should I increase price by 1/2 point across the footprint? Or maybe 1/8th in New York and 3/8ths in Saint Louis?” These players lack both the science to pinpoint optimal price variations and the metrics to show what is gained or lost. Unlocking this benefit requires four key elements:
1) Relative Competitive Position (RCP). For a robust view of demand side impacts, originators need a solid grasp of each product’s price position against the market. The important first step is to establish a robust benchmark metric for each major market. Our work with U.S. originators shows that a variety of elements must be combined on a daily basis, including:
- Daily rates posted by competitors;
- Customer points vs. rate selections relative to par;
- Regional variations given each competitor’s unique cost structure, perceived loan values and estimated volume targets; and Proper handling of marginal players in the calculation.
2) Revenue optimization framework. Having developed a competitive position metric, the next step is to build demand elasticity curves that correlate local market position and conditions with RCP. A full understanding of demand elasticity allows the pricing manager to execute tailored strategies for different markets, products and borrowing purposes. Margins can be optimized without putting volume targets at risk, and vice versa.
3) Robust technology platform. The lender must meld high-end calculation capabilities (which tax even large server farms) with nimble delivery so that the right prices are provided each morning. Multiple intraday updates are needed in dynamic market environments, for example, following a Fed announcement or a Treasury rally. It is a formidable exercise to calculate the RCP for each region, generate optimal pricing matrices given each product’s volume constraints, and distribute this information for instant use.
4) Coordination with the field. Normally, most lenders provide leeway to the sales team for “competitive price match,” or on-the-spot rate concessions to close business at the point of sale. While such pricing discretion can help to maintain sound front line relations and competitiveness, it can also defeat pricing strategies intended to temper a temporary volume surge that overwhelms production capacity.
Suspending frontline pricing discretion may put off the sales force when reps see customers walk to the bank across the street. This is why proper communication is need on pricing positions and rationale. Avoiding pipeline overload ensures that closing times will be met and the customer experience is maintained, which in turn has a high correlation with pull-through rates and, ultimately, sales force commissions.
Mortgage lender flexibility is constrained as never before, given the impact of new regulation, issues with balance sheet and investor funding, and the burden of newly complex documentation requirements on shrinking origination processing teams. While seasoned mortgage bankers have a conventional toolkit of coping tactics, each option has its drawbacks in the current environment.
Inevitably management pulls the price lever to shift origination volume and mix, but not nearly effectively as can be done with advanced pricing analytics and technology. In volume-challenged environments, the upside from this added precision can translate into $1 million to $2 million of increased profit margin per $1 billion of mortgage originations.
Zach Wise is a Principal and Andrew Frisbie is a Managing Director at Novantas, respectively in the Charlotte and New York offices. They can be reached at firstname.lastname@example.org and email@example.com.