The Inefficiencies of Commercial Product Pricing: How Banks Are Losing Value

In the competitive world of commercial banking, pricing across products such as credit, treasury, and commercial cards is a critical process. Unfortunately, many banks still rely on outdated methods to determine pricing, leading to inefficiencies that hurt their bottom line. These inefficiencies affect speed, transparency, and the ability to leverage data effectively, which can significantly impact profitability. In this blog post, we’ll dive deep into the root causes of these issues and discuss how modernizing the approach to pricing can unlock enormous value for banks.

1. The Reliance on Excel: A Hidden Drag on Efficiency

It’s hard to believe that in today’s data-driven world, many banks still rely on Excel spreadsheets to manage complex pricing processes. While Excel is undeniably a versatile tool, it is far from ideal for something as critical as pricing in a multi-product environment. Let’s explore why this reliance is problematic.

• Lack of Transparency: When pricing is done through Excel, only a few individuals usually have access to the entire pricing model, input, assumptions, and output. This creates a lack of visibility for others in the organization, leading to confusion or misunderstandings. For example, if an RM (Relationship Manager) has to price a new deal involving cash management and a C&I loan, they often must reach out to specific team members in different lines of business to price both products separately. The speed and transparency rely on how quickly specific team members can produce pricing (you enter a black box).

• No Centralization or Control: Excel files tend to live on individual desktops, creating significant challenges for maintaining control and consistency. Different departments or even teams within the same LOB might have their own versions of pricing models, leading to discrepancies in how similar deals are priced. This lack of centralization also makes it challenging to apply consistent guidelines across the board, which can hurt profitability in the long run. Or, it requires rigor, structure, and manually checking to ensure everyone is using the latest approved version to price credit deals.

• Risk of Losing Key Knowledge: Another critical issue is that Excel does not provide institutional memory. When employees leave, often “lost” pricing of deals are lost with them. New team members do not have the saved data/pricing of similar clients in which deals were not successful, or they rely on fragmented documentation. This situation results in an extended ramp-up time and a loss of institutional knowledge.

• Manual Coordination Across Teams: Pricing deals one at a time using Excel is a cumbersome process that requires significant manual coordination. There’s often no pipeline visibility or automated tracking. Moreover, there are no automated guardrails such as ‘hurdle rates’ (the minimum acceptable rate of return for a project or deal), so banks risk underpricing deals and price “leakage,” which can erode profitability over time.

This over-reliance on Excel creates a pricing environment that is slow, opaque, and inconsistent—none of which are conducive to maintaining a competitive edge.

2. Banks Are Not Leveraging Their Own Data Effectively

Perhaps one of the most frustrating inefficiencies is that banks are sitting on a wealth of historical data, but they are failing to use it effectively. Rather than using this data to streamline and improve pricing decisions, banks often start from scratch for each new deal. This results in significant wasted effort and longer timelines for closing deals.

Consider this scenario: a bank is responding to an RFP (Request for Proposal) for treasury services. The client provides a statement from a competitor bank to use as a base: “Make me an offer to make me want to switch to your bank.” In theory, banks should be able to leverage the mapping of treasury codes (or AFP codes) from similar prospect clients who made the same request in the past from the same competitor. Instead, many banks don’t tap into that historical data or even save these historical RFP mapping of codes to create a repository for future use. They re-price each deal manually, relying on institutional knowledge held by a few, and banks end up reinventing the wheel for every proposal.

The inefficiencies are glaring:

• Wasted Time: What should take minutes—using existing templates and data—ends up taking weeks due to manual rework.

• Missed Opportunities: Banks lose the chance to leverage data from previous RFPs, which could provide competitive intelligence and expedite pricing.

Why aren’t banks leveraging this data more efficiently? One reason is that existing systems aren’t designed to collect and analyze this data in a user-friendly way. Most pricing models live in Excel spreadsheets or siloed databases, meaning historical information isn’t readily accessible or useful. Most banks are still focused on trying to get their best price to a client to win a deal, but not on storing and leveraging pricing data to be more efficient in the future.

3. Siloed Pricing: The Failure to Price Holistically

Another major inefficiency lies in how banks price different products. Often, each LOB (Credit, Treasury, Commercial Card) works in a silo, pricing their products independently. While this might seem logical from an operational standpoint, it often results in missed opportunities when it comes to bundling products, offering better pricing based on total ROE, or understanding the overall profitability of a client relationship.

For example, when pricing a combination of credit products and treasury services for a single client, the individual LOBs may only focus on their own margins without considering the full picture. The failure to price holistically means that banks are often unaware of how offering more competitive pricing on one product might increase profitability across the entire portfolio.

Banks need to move away from this disjointed approach and start pricing clients more holistically. A comprehensive view that considers the return on equity (ROE) or return on assets (ROA) across all products will allow banks to create more compelling offers for clients, which can improve both client satisfaction and overall profitability.

4. No Single Product Can Solve It All… But We Can

Despite these widespread inefficiencies, there isn’t currently a single product on the market that addresses all of these issues across all commercial product lines. Most solutions available today solve parts of the problem, but they tend to focus on specific LOBs or fail to offer a truly integrated pricing model.

However, we are setting out to change that.

We’re not just creating a good solution; we’re developing the best solution. RO Price is designed to be the best commercial product pricing tool by addressing all of the inefficiencies outlined above.

WHAT WE AIM TO ACHIEVE

1. Simplicity: Our solution is designed with simplicity in mind. It’s both easy to launch and intuitive to use. Anyone in the bank, regardless of technical expertise, should be able to get started with minimal training. By making the interface user-friendly, we ensure that banks can deploy the tool quickly and see immediate results.

2. Efficiency: We believe that pricing should take minutes, not weeks. By leveraging past data, our platform eliminates the need for manual rework and dramatically reduces the time it takes to price deals. Teams can respond to RFPs faster and more efficiently, freeing up time for value-added activities.

3. Speed of Implementation: Our platform is designed to be fast to implement. Gone are the days of lengthy, six-month implementations that slow down progress. We focus on delivering immediate business value, ensuring that banks can start using the platform within weeks—not months.

4. Immediate Business Value: The benefits of our solution go beyond just speed and efficiency. We aim to provide immediate business value in several key areas:

• Pricing Guidance for RMs: Relationship managers will receive smart pricing recommendations, helping them price deals more intelligently and consistently.

• Access to Historical RFPs: RO Price provides full transparency and quick access to historical RFPs, ensuring that teams don’t need to start from scratch every time they price a new deal.

• Increased Efficiency: By automating much of the pricing process, banks can handle higher volumes of deals with fewer resources. This leads to more revenue and better margins.

• Improved ROE: Our holistic pricing approach ensures that banks can improve their return on equity, driving profitability across all lines of business.

• Track Changes: We log every single change done to any opportunity or scenario, so there is full transparency of progress and speed of delivery.

THE FUTURE OF COMMERCIAL PRICING

The inefficiencies in commercial product pricing are more than just inconveniences—they’re barriers to profitability and growth. By modernizing pricing processes and leveraging existing data, banks can dramatically improve their pricing strategies and unlock significant value.

Our vision is simple: to create the best solution for commercial product pricing. One that is easy to use, fast to implement, and delivers immediate business value. It’s time to move away from outdated methods and embrace a future where pricing is transparent, efficient, and holistic. The banks that do will not only improve their ROE but also strengthen their competitive position in the market.