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At this year’s Global Pricing Forum, host Nomis Solutions announced the availability of its Discretion Manager software, which supports dynamic price negotiations. The annual event brings together thought leaders and practitioners interested in pricing. Nomis currently has 17 of the largest 100 banks as customers. With more customers, this year’s event had larger attendance than last year’s.
Discretion Manager helps loan agents set and adapt pricing terms and conditions to optimize the trade-off between loan volumes and margin, based on the preferences and characteristics of the lender. By dynamically recalculating the impact of changes on any number of terms being offered, agents are able to price more effectively. By tracking every negotiation, the system enables the agent’s company to capture competitive market intelligence and evolve its pricing tactics to respond to changing conditions. Discretion Manager can be accessed on a tablet, reflecting the vendor’s awareness of the need for mobility in situations such as automobile lending.
Nomis provides price and revenue optimization (PRO) software and services to financial services companies, including banks, automobile credit providers and credit card processors. Financial services is a distinct segment in PRO because customer attitudes and behavior with respect to money are distinct from those they have toward, say, travel and leisure or general merchandise. Especially for lending and insurance, adverse selection is a characteristic that should be incorporated into pricing models, but it rarely is. Riskier borrowers, for example, are more willing to pay higher interest rates so it’s important for the lender to ensure that pricing reflects the degree of principal risk it is undertaking.
Price optimization is based on a concept that is simple to describe but difficult to execute because even buyers with identical demographic characteristics (such as age, income or location) may have different degrees of price sensitivity. In the case of financial services, for example, those with low price sensitivity may place more value on other characteristics of a transaction. These may include service levels or service bundles, features (specific terms and conditions such as prepayment flexibility), convenience or brand values (including security, reliability or efficiency). By appropriately structuring its offers, a financial services company can get closer to its optimal trade-off between volume and risk-adjusted profitability. Nomis claims that it has been able to increase the net interest margins of its customers by five to 25 basis points (0.05% to 0.25%) over the course of a business or interest rate cycle; such an improvement has a meaningful impact on an institution’s return on equity. Margin improvement is partly the result of replacing top-down static pricing approaches (such as weekly or monthly price books sent out by headquarters) with a system that learns and recalibrates optimal terms even for multiple-variant offerings (such as size of down payment, initial and long-term interest rates and length of loan) based on real-time market feedback.
The development and growing sophistication of packaged PRO applications has been one of the most important advances in business analytics over the past decade. The potential benefits of such systems are widespread and evident. At its most basic level, PRO software allows companies to vary the price they offer according to an assessment of the price sensitivity of the individual buyer. Those assumed to be more sensitive are shown a lower price than those who are insensitive. Today’s products can accommodate differences in the context of offerings, especially variations on initial pricing and discount. For example, some customers prefer “everyday low prices” while others crave coupons and discounts. These are retail pricing approaches, but the same tactics apply to consumer banking and finance. In the end, the lender may receive exactly the same amount of revenue, but using the right pricing dynamics to attract a customer can make all the difference in getting the business. Nomis has been increasing its attention to managing the dynamics of the pricing discussion, which can be especially important for auto loans and other consumer finance products.
Optimization methodologies such as PRO are a natural fit for the application of big data analytics. Focus on this topic has increased in recent years because of the opportunity to gain ongoing actionable insights from the mass of data created by internal systems and publicly available data (such as social media). Our benchmark research shows that three-fourths of companies are addressing more than 10 gigabytes of data per day and 10 percent are already dealing with a terabyte or more. It requires sifting through large data sets to collect consumer behavior characteristics that will enable a company to identify customer segments and quantify their price sensitivity. These complex calculations require software designed for the purpose, but most in the financial services industry rely on older methods that produce less than optimal results. Big data analytics software can help organizations more closely manage the process of defining offers to customers (and the levels of discretion they allow to account managers and sales people) and the terms and conditions of the transaction.
The conceptual framework for PRO is well established. The challenge is in putting it into practice. For example, it’s not always easy to get reliable data about historical transactions, identify segments correctly and regularly update the data to reflect changes in markets, competitive moves and model refinements. There’s a change management aspect to PRO as well. Changing how an organization interacts with customers to take best advantage of technology can be challenging. For example, the best customers of a bank may be the least price sensitive, yet there’s a tendency to reward them excessively by offering better deals than they need to be satisfied. For that reason, sales incentive management and PRO are highly complementary. I’d say it’s impossible to get full benefit from either without combining them. Incentive management may be the only reliable means to overcome organizational inertia, especially where deep-seated beliefs are concerned.
It seems as if businesses have been struggling with pricing their products and services forever. At the dawn of the Internet age some pundits speculated that the increasing pricing transparency afforded by the Web would drive prices closer together. This hasn’t happened, and vendors are still challenged to set the best price. As well, for decades, financial services companies have been grappling with the difficulty of implementing customer value pricing as a way to deal with the extreme asymmetry of customer profitability in their industry. That is, a small minority of customers are very profitable while most are marginally profitable or even unprofitable. The dilemma facing executives that customer value pricing seeks to address is that some in the larger group can become very profitable if the institution can attract a higher share of their wallets or over time as their age, income and wealth grow. Without the right software it’s never easy to find such diamonds in the rough. Nomis can help financial services companies here, but although software is necessary, it’s not sufficient. Discussions with customers confirm the persistence of intractable cultural and institutional barriers that get in the way of successfully implementing a customer value approach.
Because of the host’s new software release, one area of focus of this year’s forum was managing discretion in setting prices. In many retail settings in western societies, prices are not normally negotiated. However, for many big-ticket consumer items (such as cars and houses), buyers usually expect to negotiate the price with the seller. In these cases, companies need to decide to what degree to give their agents discretion to negotiate charges, terms and conditions. There’s a high degree of dissatisfaction among business executives with how to apply discretion to the negotiation process to optimize revenues and profits; many suspect that too much discretion erodes margins. One reason for this distrust is poor application of incentive management to the process. Much of it, though, stems from a failure to understand buyers’ price elasticity and the optimal method of presenting prices in terms of list and discount in managing a negotiation. As noted, even for the identical product offered by the same company, for some customers it’s better to quote a high list price and offer a sizable discount while for others a more moderate list price and a limited discount works best. Nomis can help manage the dynamics of the price presented and discounts offered in a way that optimizes revenue and pricing.
Price and revenue optimization is only beginning to mature in industries other than travel and hospitality. While some financial services companies run their own internal PRO efforts, most don’t have the resources, desire or ability to do this in-house. Yet there is evidence of the value of PRO as an effective profitability management tool in the financial services industry. The need for banks and other financial institutions to increase their returns on assets and therefore equity in today’s challenging and more regulated environment makes PRO a vital tool. Financial services firms should take steps to incorporate more effective pricing as part of their strategy and consider Nomis Solutions to provide the analytical and operational underpinnings of such an effort.
I recently attended the 2012 Global Pricing Forum hosted by Nomis Solutions, a provider of software and services to banking and finance companies. This annual event brings together thought leaders and practitioners in the area of pricing and revenue optimization (PRO). This technique uses analytics to sift through large data sets to tease out customer behavior characteristics, identify customer segments and quantify their price sensitivities. These complex calculations require software designed for the purpose, but most in the financial services industry rely on older methods that produce less-than-optimal results. Analytics can help organizations more carefully manage the process of defining offers to customers (especially the levels of discretion offered to account managers and sales people) and the terms and conditions.
Pricing optimization is based on a concept that is simple to describe but difficult to execute because even buyers with identical demographic characteristics (such as age, income or location) can have different degrees of price sensitivity. For example, those with low price sensitivity may place more value on other characteristics of a transaction with a financial services firm. These may include service levels or service bundles, features (specific terms and conditions such as prepayment flexibility), convenience or brand values (including security, reliability or efficiency). By appropriately structuring its offers, a financial service company can get closer to its optimal trade-off between volumes and risk-adjusted profitability.
For its part Nomis’s software provides clients with a Nomis Score that measures customers’ price sensitivity. (You can find its patent application here. This score is the foundation for structuring offers. By allowing financial services companies to understand how changes in pricing will affect demand from different segments of customers, it can provide an analytic basis for an effective customer value pricing strategy. Several of the presentations at the conference were case histories documenting how customers have achieved higher returns or increased volumes using the score as part of their optimization efforts.
I’ve been going to this event for several years. For me, the key take-away from this year’s forum could be summed up as “pricing is more than just pricing.” In other words, while the mechanics of executing a price optimization strategy are extremely important, it’s valuable to step back and recognize some of the key reasons why price optimization is a strategic imperative in financial services.
Nomis founder Robert Phillips (also the author of a book on the topic) pointed out that this industry has inherently fewer strategic methods for maximizing profit. Interest rates are a commodity. Unlike for luxury goods, few if any borrowers are willing to pay more for a mortgage because of the prestige of borrowing from a particular lender. As a further complication, those eager to pay a higher interest rate are also more likely to default (a condition referred to as “moral hazard”). Thus the need to segment existing and potential customers to determine, on the one hand, their willingness to pay for loans or services or, on the other, their requirements for the use of their own funds (such as certificates of deposit or checking accounts).
Even though it’s important to consider the bigger picture, the focus of the conference was on improving the execution of price and revenue optimization. This is still a cutting-edge discipline from several perspectives: using the underlying analytics technology, managing the systems and integrating PRO into the day-to-day management of a financial institution.
As well, before diving into the mechanics of PRO, it’s necessary to consider the bigger picture issues at work in applying it successfully. One of the most important elements contributing to the success of PRO is understanding why customers want to do business with a company – not the reasons people within the company think existing and prospective customers have but those revealed by factual market research. Company lore often is out of date and, especially in larger institutions, doesn’t reflect the breadth of motivations and concerns of clients. No doubt this is generally good advice for every business, but it is vital to managing pricing as an ongoing process.
A broader point to come out of the conference is that pricing and revenue optimization will be even more important to the financial services sector in a period of rising interest rates. Today, most of the developed world is living in an environment of “rate suppression.” This will almost certainly end within the next couple of years if there’s any improvement in the world economy or if central bankers decide it is no longer advisable. Yet few people now working at banks or other financial institutions have experienced conditions similar to the 1970s when rates rose sharply. Managing portfolios and sourcing funds in a generally rising interest rate environment poses different challenges than dealing with today’s low rates. If history is a guide, not managing this properly will have severe consequences for organizations unprepared for it.
The underlying analytics are vital because it’s necessary for companies to monitor markets continuously to determine the price elasticities of various customer segments as they set rates, terms and conditions to best reflect the trade-offs customers make. Most customers respond in a predictable fashion to pricing. In financial services, for example, those with good credit ratings are more demanding because they have more options; those borrowing larger amounts are more price-conscious because of the absolute cost; and new customers are price-conscious because paying less is a key motivation for changing banks. However, it’s almost certain that within these general behavior patterns, lenders will find subtle but important variations in how potential customers respond to specific structured offers. Understanding the key lender and customer decisions that occur in the sales process is fundamental for defining an effective modeling approach to predicting customer behavior. These variations usually make the difference in improving an institution’s returns on capital.
Pricing and revenue optimization first took hold in the 1980s in the travel and hospitality industries. It is part of everyday business practices for airlines and hotels worldwide because it works. Yet its use is still immature in most other industries. While some financial services companies run their own internal PRO efforts, most don’t have the resources, desire or ability to do this in-house. Evidence is mounting that PRO is an effective tool in the finance industry, and I believe the outlook for the financial markets means that its use will be even more important in coming years. I recommend that financial services firms take steps to incorporate more effective pricing as part of their strategy and to look into Nomis Solutions to provide the analytical and operational underpinnings of such an effort.
Robert Kugel – SVP Research