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How lenders can use dynamic pricing to maximize profits

Oct 26, 2016 / Consumer Banking

Why would a lender want to offer different prices to different pricing segments? One reason is that different pricing segments have different associated variable costs—and the most important cost difference among segments is risk. Lenders have long practiced risk-based pricing to account for risk differences. Another motivation is that customers value various products in various ways. To maximize profit, it is important for lenders to incorporate these differences in customer value into pricing.

Customers also differ widely in their underlying sensitivity to price. Some care only about price and will invest time to apply to different lenders and compare prices. Thus to capture extremely price-sensitive customers, your prices will need to be quite low. But other customers care more about convenience or other features. This group of borrowers is willing to accept a higher price from a lender who can save them time or provide the features they want.

And if you have an offering that appeals to these customers, you can and should charge a higher price.

There are limits to the extent that a lender can (or should) use customer-driven dimensions to differentiate prices. Regulation and corporate prudence limit the extent prices can be differentiated along protected categories such as gender or age. For most lenders, the biggest, immediate opportunity to pricing tiers lies in product differentiations.

Differentiate along product dimensions

Lenders can differentiate prices along product dimensions such as size, term, and loan-to-value ratio. Customers taking out large loans tend to be more price-sensitive than those seeking smaller loans. This is intuitive: Customers naturally tend to spend more time “rate shopping” for a larger loan than a smaller one. Everything else being equal, customers who consider longer-term loans tend to be more sensitive to the rate than customers after shorter-term loans. Customers who have a high loan-to-value ratio are more risky and less price-sensitive: It is thus profitable to charge them more. The relationship between these dimensions and price-sensitivity can be quantified through price testing.

We know some characteristics related to a product, such as loan size, loan term, and loan-to-value ratio correlate to price sensitivity (as well as profitability and risk). Thus it makes sense for lenders to differentiate pricing along these product dimensions. In fact, most commercial lenders do so. However, most lenders do not explicitly calculate the incremental profitability and price sensitivity of each type of loan that they offer. Without doing this, they cannot determine the right price to offer. And as a consequence their prices in the market are likely to generate less-than-optimal results.

Create virtual product differentiation

Lenders should definitely price their loan products differently, based on such real characteristics as size, term and loan-to-value ratio. However, they might also want to consider a virtual products strategy. A virtual product is differentiated by a somewhat artificial distinction in order to appeal to a specific customer segment.  A classic example of such a strategy was adopted by the commercial airlines that created “business class” and “discount class” products. Business class was available at any time without conditions, while discount class required two weeks advance booking and a weekend stay. The distinction was not based on any real cost difference; instead it was designed simply to differentiate between leisure travelers and business travelers. By creating these virtual products, airlines charged higher prices to business customers (who usually need to book closer to departure and are less price sensitive) and lower prices to leisure customers (who can meet the early booking restrictions and are more price sensitive).

How can a lender take advantage of virtual product strategy? A 2015 J.D. Power Primary Mortgage Origination Study found that customers would be willing to pay a premium—as much as $1,448—for faster processing of their mortgage applications. This would imply that opportunities exist for lenders that can reliably process loan applications quicker to charge more money. A lender could also charge a “premium processing” fee. This would allow customers to segment themselves into the “price-sensitive” (who prefer to save money and don’t mind waiting) and the “speed sensitive” (who are willing to pay more for faster service).

Leverage channel price sensitivity

The channel through which a customer approaches a lender also offers a good indication of price sensitivity. Lenders can take advantage of this because everything else being equal, customers who come via the Internet are more price sensitive than those arriving through an in-bound call center. And in turn, call center customers are more price sensitive than those who approach through a bank branch. In a similar vein, customers who use a mortgage broker tend to be more price sensitive than those who approach a bank directly. Additionally, variable and handling costs may be lower for loans advanced through the Internet than through branches, which provides an additional reason to consider lower prices for borrowers working digital channels.

Towards Market-of-One Pricing

“Market-of-one” represents the “holy grail” of pricing differentiation. In market-of-one pricing, all information available for a loan applicant that can be used for pricing is used—and a different price is set for each customer, for each loan product, through each channel. A market-of-one pricing system uses the customer, loan and channel information to calculate an optimal price in real-time.

Increasingly, reliable software architecture makes it possible to implement real-time algorithms in pricing, where optimal prices can be calculated each time a quote request is received. The success of dynamic pricing within a number of industries—notably the airlines and online retailers—has also largely eliminated the belief that every price offered to a customer needs to be reviewed and vetted by a human being.

Finally, new tools enable pricing to be controlled and reviewed at a higher level while allowing individual prices to be determined based not only on customer and transaction characteristics, but also the current state of the market and competitive environment.

There are already moves within consumer lending toward market-of-one pricing. At least one unsecured lender in the UK uses a real-time algorithm to set the prices for each approved application. In Canada, sophisticated pricing optimization software calculates the recommended ranges for mortgage rates on a quote-by-quote basis.

Given the potential benefits and the pattern in other industries, it is likely lending will move more and more toward market-of-one pricing over the next decade. This will provide lenders unprecedented opportunity to provide “the right price for the right customer, at the right time, for the right product.” However, it will also require them to develop the deep customer-specific knowledge that online retailers such as Amazon have obtained in order to compete effectively in the new lending landscape.

This edited excerpt comes from “Pricing in Retail Banking,” an upcoming book by Robert Phillips, PhD, founder of Nomis Solutions, a software company that employs big data, advanced modeling and deep analytics to help large and medium-sized retail banks better understand their customers.