In this month’s post, Tal Schwartz notes that financial institutions worldwide are using sophisticated data modeling to incorporate disparate and somewhat unusual information to price products at a granular level. This approach lets them offer competitive pricing to specific customer segments, while also monitoring the impact of pricing strategies to their overall lending goals.
The pricing dimensions used in a typical bank rate sheet is pretty basic. Most banks will price by debt-to-income, loan-to-value, and the super adventurous ones may throw in a credit score band.
While there is definitely value in pricing by these broad dimensions, it is only skimming the surface of what is possible. Banks that truly embrace granular client segmentation are able to tap into pockets of price elasticity. A bank that understands price sensitivity, is a bank that can drive overall profitability.
PRICING FINANCIAL SERVICES IS AN ART...AND A SCIENCE
Just like any retail brand, banks are competing for customers. In order to attract and retain them, banks need to deliver bespoke customer experiences. To do this, many are experimenting with non-conventional dimensions in their pricing.
Here are a few examples from banks we spoke to:
A large commercial bank in the UK incorporates climate data into the pricing of their real estate secured loans. So in this example, property located by a flood plain would be priced to reflect the increased risk to the business operating there.
A large retail bank in Europe uses relationship scoring to arrive at a customized price. This calculates the client’s value to the bank by evaluating assets and liabilities across multiple customer accounts (retail, wealth, business, etc.) and using that “value score” as a pricing attribute during rate sheet creation. We’ve also seen these scores used to impact fee waivers and cashback.
A mid-sized credit union in the US uses customer tenure to better price clients that have proven loyalty over long periods of time. Tenure is strongly correlated with elasticity, which is essential for optimizing your rates.
HOW TO FIND THE RIGHT PRICING STRATEGY
By moving away from cookie-cutter pricing, these financial institutions are capturing more business at a price that works well for them – and for their customers. By moving towards a more granular segmentation, banks can capture more customers at more profitable rates.
Sounds great, you’re thinking, but how do we get there?
First define your “why.” What is the overall goal you hope to achieve? Is it to drive more volume? Do you want to increase your per-loan or per-portfolio profitability? Regardless of the outcome you hope to achieve, knowing what is ultimately driving your decision-making process helps ensure the additions you make to your pricing dimensions are in alignment with your overall goals.
From here, take a look at the customer data you already have: where are they from, how often do they come into a branch, what products do they have, what other financial relationships do they maintain. If those datasets reside in different systems, you may need to find technology to pull them together.
Now it’s time to brainstorm. Get your team together and think about what factors should influence pricing in addition to those you’re already using. There is a lot of data out there so think in very broad terms. What makes a customer attractive or not attractive to your business? How would more or fewer of those customers impact your bottom line? And how can you limit your risk while still aggressively meeting your targets?
Those answers will be different for every product & pricing lead reading this blog. And that’s the whole idea.
FLEXIBLE LOAN PRICING SOFTWARE IS CRUCIAL
Forward-thinking financial institutions around the world can use a tool like Nomis Price Optimizer to create optimized rate sheets based on unique attributes, specific to their growth and profitability goals. Of course, your own goals will define your pricing strategy.
If your goal is to have the biggest portfolio, you can adjust your rate sheets accordingly to provide ultra-competitive pricing.
If your goal is to be more profitable, with less concern for volume, you can be fairly aggressive with your pricing to capture more margin per loan.
But in both scenarios, you’ll have the flexibility to price less aggressively in the small pockets where you find more price sensitivity in your client base.
The important theme here is that regardless of your goals, you need software that’s configurable, flexible and allows you to include whatever pricing dimensions you want.
So ask yourself, how can you use data in creative ways to improve pricing outcomes? We’d love to hear what you come up with and your results.
Tal Schwartz is a Senior Product Manager at Nomis Solutions. Previously, he was Head of Policy and Research for the Canadian Lenders Association. He is also the author of the popular newsletter, Canadian Fintech (https://canadianfintech.substack.com/).