Imagine the following scenario:

The pricing department in your bank decides on a new pricing policy for a mass market deposit product. Your bank has already realized that using a set pricelist and then allowing each branch/region to negotiate with its customers independently is far from being optimal. Why? Because your typical sales person will find it hard to deliver the right price/product to the right customer without analytical support, and in many cases will provide the maximum allowed discount or benefit in order to close the sale. This practice will lead to losses on two fronts:

  • A bad customer experience: the bank is losing out on engaging with potentially profitable customers that are either not willing to negotiate or are unhappy with the results of the negotiation
  • Providing too many benefits /discounts: the bank is losing money by providing too many benefits to customers that would have closed the deal at much more profitable rates.

With this in mind, your pricing department is looking for ways to exercise better control over the negotiation process by using analytical insights. But before getting started, it is important to understand how changes to the pricing practice tie into your bank’s strategic position. For example:

  • Is your bank planning a strategic move to omni-channel banking (a move that will require a consistent cross-channel pricing policy)?
  • Are there new transparency regulations coming in that might impact the way you engage with your customers?
  • Is there a drive for operational efficiency, forcing your retail network to look for ways to save on negotiation time?
  • Or maybe you have the opposite challenge – current business culture and local negotiations are here to stay and your goal is to find a way to balance central control over pricing while minimizing the resistance from your local branch managers?

How would you design a centralized pricing policy that addresses your bank’s strategy and enables you to explore the different tradeoffs? In this blog I will focus on the amount of control a branch has over the product street price and how analytics can support this process.

Overcoming Organizational & Political Barriers

As we discussed in our first blog on “Centralized Product Pricing In Your Bank – What are The Obstacles?” it is inevitable that certain difficulties will be encountered when deploying a centralized pricing strategy. However, from an analytical perspective, there are several effective approaches in dealing with this situation.

1. Price Recommendation Approach

In cases where only minimal or no changes to the current pricing practices are possible, you might consider “starting small” i.e. branches will maintain full autonomy over setting prices, but will be provided with analytically-based pricing recommendations or target prices. This is a relatively “soft” way of introducing price analytics and centralized pricing into a localized negotiated process (you are only recommending, not dictating). Hopefully as time passes, your branches will start acknowledging the value of your recommendations and they will become the “anchoring” point for any future negotiations. However, in the short term, the final say on the bank’s pricing strategy remains completely in the hands of the local branch managers, so your recommended prices may stay just that – a recommendation.

2. Manual Manager Override Approach

What if your retail network is willing to cooperate with a centrally dictated pricing policy but rejects the idea of completely eliminating localized negotiations? How can you maintain the branches local “veto” right for special cases, and still move forward?

  • From the pricing manager’s perspective: Since the pricing policy effectively becomes the starting point in your customer engagement journey, you can design your pricing policy in a way that it will anticipate a branch’s negotiating behavior. For example, if the recommended price for two sets of customers is identical, but their respective branches have different discount policies (due to culture, local competition or individual manager preferences), your centralized pricing policy can recommend different initial prices for these customers that will take these expected discounts into account.
  • From an operational perspective: This option is very attractive as you can improve your indirect control over the final prices (especially if you introduce negotiation quotas), while leaving the retail network with some leeway to adjust.
  • From an analytical perspective: There are some challenges when trying to analyze both customer behavior and branch behavior, and combining these models requires more careful and frequent analytical monitoring and maintenance.

3. Analytical Discount Approach

The natural next step in your journey towards centrally controlled pricing can be taking control over the branches’ discount behavior. If you know how to calculate the initial price and predict customer propensity to ask for discounts, why not calculate the discount too? This means providing your branches with a centrally-set price range, while keeping their ability to choose the exact level of benefits given to customers (e.g. a minimum price for mortgage rate negotiations). Simultaneously calculating two pricing points is a more complex analytical effort, primarily in terms of data collection (you will have to dramatically improve the documentation of the negotiation process happening in the branch). However, there is greater potential for improving financial results and the customer experience, since you can now identify and address more complex customer preferences: some of your customers will respond favorably to an initial low price, eliminating most discount requests, while other customers will respond more favorably to a slightly higher initial price and the “right” discount offer.

4. Fully Centralized Pricing Approach

Is your bank planning to initiate multi-channel pricing? Are you thinking about improving the operational efficiency of your retail network and realized your branches are spending valuable time on negotiations when they can be focusing on more profitable activities? In order to achieve both goals you should consider a strategy that eliminates the existing negotiation culture in the bank altogether. From the customer’s perspective, the key concept is the idea of “doing the negotiation with the customer in advance”. Instead of relying on the intuition of the local branch manager, you can use analytics to determine the right price for each customer (based on price sensitivity, relationship value, loyalty metrics etc.) and dramatically improve the customer experience by offering the right price from the start. Naturally, such an approach totally restricts your branches from making any pricing adjustments which requires a lot of organizational discipline, and your customers might also have to adjust their expectations if negotiation was a central part of their engagement. On the other hand, the standardization and improved central control over prices, offers a huge opportunity to improve customer experience, volumes and revenues, in both the short and long term.

The figures below demonstrate where the strategies stand in terms of analytical complexity vs. organizational challenges:


Analtyical complexityHow Should You Go About Designing Your Centralized Pricing Policy?

In order to find the right balance between economic and operational gains as well as the organizational challenges of deploying a central pricing policy, you must first map out your bank’s readiness to accept a more sophisticated pricing policy. Depending on your circumstances, there are two effective ways to do this:

  1. If your organization already “feels comfortable” with centralized pricing or even has some experience with pricing analytics, it is suggested to aim for the “Analytical Discount” approach. Over the long run, this approach will provide a deeper understanding of your customer’s preferences and a better control over, and understanding of your portfolio dynamics. This approach has the potential of reaching similar, if not better, financial results as the “Centralized Fixed Pricing” (that can improve profits by up to 20 bps of the portfolio NII).
  2. If your organization has just started analytics to manager your pricing strategies and is less familiar with the process, it would be wiser to aim for the “Manager Override” option. Rather than directly intervening with local managers’ decisions, you simply model their behavior upfront and take this behavior into account when managing your pricing strategies. Although the potential financial benefits in this strategy may be lower (since we allow disruption of recommended prices), less analytical efforts are required for building this scenario and there would be minimal disruption to current business practices.

Conclusion: Striking the Balance when Deploying Pricing Management Solutions

As a pricing manager it should be in your interest to take control over pricing in the long run. As part of the move to omni-channel pricing, I believe that banks will eventually have to move to such pricing practices at their own pace, and harness the full potential of pricing analytics in the process. However for some products, negotiations with the customer are here to stay in the short-medium term (because of local cultural preferences, corporate culture, regulation, etc.) and it is imperative to take into account all aspects of the interaction with the customer when thinking about a centralized pricing policy. Under these circumstances it’s clear that introducing some flexibility into your optimized decision process, and allowing some freedom of choice to local management (while predicting that behavior), can leads to better financial results and improved cooperation with the retail network in the short run, and can help facilitate the shift to centralized pricing in the long run.

Have you tried to implement a centralized pricing policy? Please feel free to share your thoughts in the comment field below.