The UK mortgage industry is experiencing an unprecedented and significant event. According to estimates from the Council of Mortgage Lenders, 1.4m loans – almost 4,000 a day – are due to mature and reset to the standard variable rate in 2008.
If nothing is done, these mortgage holders will see substantial jumps of 20%, or even as much as 60% with loading fees, in their monthly payments. This equates to an average increase of £210 per month. The large number of customers shopping for mortgages will present lenders with both an opportunity and a challenge.
For banks there are a number of questions that must be addressed. How should they price their retention products?
How should they segment their customer base? Which customers should they aggressively approach? How should they respond to customers who approach them for a new offer?
The banks that are able to adopt the best processes and methodologies to address these burning issues will be the ones best able to navigate through this unprecedented situation. Those that sit back and rely on old and outdated approaches will find themselves losing both profitability and volume.
Visionary executives understand that often the quickest way to improve bottom line results is to get pricing right and they want to improve their pricing practices and processes in order to capitalise on this opportunity in 2008.
Pricing optimisation is a key technology that provides banks and lenders with insight into customers’ response to pricing and retention-pricing decisions enabling lenders to drive improved business performance. It also enables them to determine which customer segments are worth aggressively pricing to retain and which ones are not.
In a 2007 survey of pricing managers across the top 30 banks and finance companies in the UK, 86% felt that their pricing process was in need of improvement. While executives understand that they have some pricing power, they lack the tools to translate business strategy and corporate goals into the operational pricing and retention pricing of mortgages and personal loans.
In fact, it is not uncommon for banks to manage their pricing with Excel spreadsheets. The lack of analytical sophistication in pricing may be surprising since banks have long recognised that quantitative analysis in such areas as risk management is critical to success. The ratio of risk analysts to pricing analysts in the typical bank is probably five to one or higher. Many banks have invested significantly in risk-management technology but have not made comparable investment in understanding how customers respond to their prices and how they can use that understanding to drive better results.
Flawed pricing processes
The pricing and retention pricing processes at many banks suffer from one or more of the following short- comings:
- There is no clear understanding of profit and volume trade-offs.
- Pricing managers often only focus on a handful of headlines. Out of hundreds or thousands of pricing cells, most managers will only perform analysis on 5-10 key rates. The majority of the rates The most common pricing approachesMost banks and finance companies use one or a combination of approaches to guide pricing decisions to determine rates and fees:1. Cost or risk-based pricing: rates and fees are set based on cost (cost of funds plus risk plus fixed margin). This approach ignores competitive pricing, as well as the differential price-response of different types of customer.2. Market-based pricing: rates and fees are set based on competitive prices, which doesn’t take into account the value a customer places on the product or service or the profitability of the loan.3. Anecdote-based pricing: rates and fees are set based on rules of thumb, which does not take into account current market and competitive realities.receive no explicit analysis or consideration at all.
- 80% of rates are too high or too low because price response is poorly understood. Most pricing managers don’t have the tools to determine the impact of a five or 10 basis point rate increase or decrease on customer demand for a particular mortgage.
- Once headline rates have been established, other rates are often calculated using simple rules of thumb. For example, 80-90% LTV customers always have rates exactly 10 basis points higher than the corresponding
- Even when price response models exist, there is no infrastructure to optimise all rates simultaneously across products, markets, customer segments, and channels.
- 3-5% of all prices are erroneous because they were manually coded into loan origination or deposit processing systems.
Without a rigorous performance tracking process, the pricing and profitability team has a difficult time determining whether or not performance targets were met. And, if they were not met, the pricing team is often unable to identify the reasons why performance varied from plans, which could help the team make better pricing decisions in the future.
The first area for improvement
Understanding customer response In the pricing process is the first area for improvement. Ultimately, most banks and finance companies have not managed to connect pricing strategy to a balanced understanding of profitability and market demand. A few innovative banks have invested in the ability to understand customer response (or price elasticity), and they leverage that information to make better pricing decisions to drive both acquisition and retention.
Although this significant opportunity for improvement in pricing practices and process is available across all lines of business within a bank, there are four keys areas on which mortgage lenders should focus:
- Improving understanding of how customers respond to their pricing to make more informed pricing decisions. Lenders need to look beyond a simple ‘market-based pricing approach’ and incorporate customer response as a key input for all pricing decisions, both acquisition and retention.
Mortgage rate shock, when a rate resets to SVR, is both an acquisition and a retention challenge since customers who are not retained by one bank will be acquired by another. Pricing optimisation allows lenders to determine which customers are worth acquiring, and gain a stronger handle on long-term loan performance. Examples of typical pricing approaches used by banks and finance companies are shown in the box ‘The most common pricing approaches’.
- Understanding their customer segments. As banks have experienced, customers vary widely in their response to their rate resetting to SVR on a discount or fixed mortgage. Some will immediately seek to refinance with their current mortgage provider. Some will refinance elsewhere without even contacting their current provider. Others, especially those with small balances and/or poor credit, may continue on SVR for a very long time.
The first step towards an intelligent retention strategy is to understand the customers within your current portfolio and how they are likely to react when their rate resets to SVR. This is a problem of customer segmentation.
Customer segmentation for mortgage retention is an on-going process. The first step is performing an initial segmentation based on how different customers with different product holdings have behaved in the past. However, customer segmentation needs to be continually updated to ensure it is consistent with the most recent market conditions. Pricing optimisation incorporates a process of continuous updates and improvements to ensure this takes place.
- Calculate and utilise the basic retention trade-offs. Mortgage retention poses two questions related to customers whose mortgages are maturing:
– Which customers do we pro-actively approach and what offer do we make?- Which customers do we not approach and what offer (if any) do we make when they contact us (if they do)?
The idea behind price optimisation is to calculate the trade-offs explicitly for different customers segments and, based on that calculation, determine the right action set for each customer segment. For some segments, the best action will be to do nothing – these customers are likely to stay on SVR or are not anticipated to be sufficiently profitable. For some segments, the best action will be to proactively approach them with an attractive offer. For the remaining segments, the most profitable action would be to wait for them to contact you.
- Develop a consistent segment-focused strategy. The final output of the price optimisation process is a consistent strategy across touch-points for all customers in the portfolio who are coming up for renewal. It specifies which customers should be proactively contacted to receive an offer and which offer each one of them should receive. For the remaining customers, it specifies exactly what offer they should receive if they should contact the bank either by phone or at the branch.
Need for a consistent approach
Using a consistent, repeatable and efficient pricing process is critical. For any bank to obtain the maximum profit and volume from its retention pricing, it must establish a disciplined process that updates continually over time.
At any time, pricing decisions should be based on the best understanding of the profitability and responsiveness of different customer segments. As information about customer response is received over time, the parameters of all the statistical models need to be updated to reflect current reality. These will change over time as the underlying cost of funds change, as competitors change their rates, and as the housing market itself changes.
The next few years are going to be critical ones for British mortgage lenders. There is going to be continuing focus on retention and customers are likely to be shopping their rates as never before. The banks that will thrive in this environment will be those that understand how their different customers will respond to their offers and how to use that information to determine the best action and offer for each customer.
About the author
Dr Robert L Phillips is founder and chief science officer and vice-president, research and development, of Nomis Solutions.
He founded Nomis in 2002 to help financial services firms use pricing analytics, optimisation and execution to improve profits and market share by enhancing their understanding of the impacts that customer preferences have on product and portfolio performance.
Before founding Nomis, Phillips was chief technology officer of Manugistics, where he was responsible for developing the company’s pricing and revenue optimisation and enterprise profit optimisation solutions.
Prior to that, he was founder and chief executive officer of Talus Solutions, which was then the world’s largest pricing and revenue optimisation company.
Over the past 15 years, he has helped leading companies optimise price and revenue within a wide variety of industries including airlines, car rentals, hotels, automotive, electric power, freight transportation, and manufacturing.
Phillips is a lecturer at Stanford University Business School and served as a visiting professor at the Columbia University Graduate School of Business. He is a frequent speaker at industry events such as the CBA Auto Finance Conference, the CBA Home Equity Conference, the Credit Scoring & Credit Control Conference and INFORMS.
He is the author of Pricing and Revenue Optimisation and has published widely in the Risk Management Association Journal, Management Science, and Mathematical Programming. He is a senior editor of the journal Production and Operations Management Systems, and an associate editor of Operations Research.