How Banks Can Transform Deposit Rate Management with Customer-Centric Approaches

By Pulkit Bhardwaj,
Head of Sales and Ecosystem – UK and Europe,
SunTec Business Solutions

Deposits are a critical business driver for most banks. But competition for deposits is increasing amidst rising interest rates and macro-economic slowdowns. Banks must improve their deposit management strategies, and they can only do this by focusing on customer-centric approaches. In this article, we will explore why taking a customer-centric approach is crucial and how it can help banks navigate the complexities of interest rates on deposit products.

Refining the Deposit Product Portfolio

Only 25% of banking industry members believe that they have the right product range for customers, with over 50% suggesting they have too few products to meet customer needs.1 But it is important for banks to understand that the number of products offered is not as important as the kind of products and how they meet customer expectations. When it comes to deposit products, one size does not fit all. Understanding customer needs is key to offering a value-driven product portfolio. Segmentation is key: some customers prioritize interest rates, while others value accessibility or channel preferences. By understanding their target audience and developing tailored offerings, banks can ensure they have the right product range to meet both customer and business needs.

Price Optimization Models for Interest Rates

Despite the digital transformation momentum within the industry, over 60% of banks rely on intuition and expert judgement to set interest rates on deposit products, while less than 10% use price elasticity models or analytical optimization tools.2 The former approach is prone to errors, leading to excess payments for funds and revenue leakage. A data-driven approach to price optimization with robust price analytics models is key to optimizing efficiency and driving effective decision-making. These models harmonize portfolio growth with prudent interest rate management, benefiting both customers and the bank’s balance sheet. By using price elasticity models, banks can strike the right balance between attracting deposits and managing interest.

Taking a Behavioral Science-Backed Approach

In the past, customers were passive recipients of banking products and services. They had no other choice, and they did not know that there was any other way to engage with banks. But today, technology has shown them that a hyper-personalized, relationship-based, and value-driven experience is possible, and they expect their banks to deliver this as well. And banks must understand their customers’ wants and likes  to deliver this personalized experience. How they present their products is important, and behavioral science may hold the key to better customer engagement and communication in the digital era. Unfortunately, 80 percent of banks feel their attempts to leverage behavioral science are basic with significant room for improvement.3 They must strengthen their efforts in this area to engage more fruitfully with customers with relevant offerings. For instance, a simple change in the order of presenting offers can significantly impact customer uptake. Banks need to make customer experience the starting point for process design, understand what customers want, and how and when they want it. Behavioral science empowers banks to communicate effectively and maximize engagement.

Technical Challenges in Managing Customer-Specific Interest Rates

Managing customer specific interest rates is quickly emerging as a critical driver of successful deposit management. However, as banks embark on this journey, there are a few technical challenges they will have to address:

  • Dynamic Interest Rate Calculation: Traditional core banking systems are not flexible enough to calculate dynamic personalized interests for individual customers. They were designed for a different era of banking when rates were set at the product level and applied uniformly. But modern banking requires dynamic personalized rates based on customer profile, transaction history, overall relationship with the bank, and risk assessment. This calls for system enhancements and robust data processing capabilities.
  • Granular Customer Segmentation: Most banks carry out broad segmentation strategies based on parameters like location, net worth, etc. But these are proving to be ineffective in this era of hyper-personalization. Effective interest rate management necessitates granular customer segmentation. Banks must be able to fine-tune segmentation strategies to consider parameters like creditworthiness, tenure, relationship depth, and transaction detail in near real time. Data-driven, dynamic, and granular segmentation based on customer behavior can help the bank develop relationship-based offerings and rates, enhance customer experience and foster relationship longevity. Each segment may warrant different interest rate structures. Implementing this segmentation within the core system involves database design, query optimization, and efficient data retrieval mechanisms.
  • Real-time Rate Adjustments: Interest rates can never be static and must change according to market dynamics, regulatory changes, and economic fluctuations. Banks need real-time rate adjustment mechanisms that can seamlessly update interest rates across accounts. This involves integrating with external data sources (e.g., central banks, market indices) and automating rate adjustments. The core system must handle these updates without disrupting ongoing transactions.
  • Regulatory Compliance, Data Security, and Privacy: Banking is one of the most tightly regulated industries in the world. Regulations vary across regions and are constantly evolving in response to global or local developments. Non-compliance carries the risk of punitive action and a negative impact on brand value and image. The core system must validate interest rates against legal limits, monitor changes in regulations, and trigger alerts when adjustments are required. This involves building rule engines and maintaining an up-to-date regulatory knowledge base.
    At the same time, cyber risks and malicious action from bad actors are on the rise, and banking is particularly susceptible. Reports indicate that the financial industry faced the maximum data breaches in 2023, including one that simultaneously impacted almost 1000 institutions.4 The core banking system must enforce robust security measures to protect customer information. Encryption, access controls, and audit trails are essential. Additionally, privacy regulations (such as GDPR) impact how customer data is stored, processed, and shared. Compliance with regulations requires intricate system configurations. Additionally, the threat landscape is constantly evolving with new technologies like AI being leveraged by bad actors to launch increasingly sophisticated attacks. The security strategy deployed by banks must be agile and robust enough to be able to identify and address emerging threats.
  • Integration with Pricing Models: Sophisticated pricing models, such as option-adjusted spreads (OAS) and yield curves play a crucial role in determining interest rates. For instance, OAS can allow banks to assess the value of embedded options within deposit products, such as early withdrawal options or interest rate adjustment features. By incorporating factors like interest rate volatility and depositor behavior, it provides a more comprehensive measure of the risk associated with these deposit products, enabling banks to set appropriate interest rates that reflect the underlying risks. Yield curves, on the other hand, can provide a graphical representation of interest rates across different maturities, reflecting the market’s expectations of future interest rate movements.  Integrating these models can ensure accurate rate calculations, risk mitigation, optimized profitability, and enhanced decision-making. However, this integration requires expertise in financial mathematics, software architecture, and seamless data flow between pricing engines and the core banking platform.

Optimize Deposits Rate Management; Externalize Pricing with a Rule-Based Platform

Banks must improve their deposit management strategies with a customer-centric approach and externalize interest rate management via a rule-based and intelligent platform for flexibility. This would enable them to make quick adjustments to market shifts and regulations without making changes to the core system. Further, such a platform facilitates transparent pricing by explicitly stating the criteria for rate determination. Additionally, externalizing pricing rules reduces the burden on the core system, improving overall performance. Centralized rule repositories maintain consistency across products and customer segments, streamlining management processes. Banks can thereby benefit by adapting to market changes, improving system efficiency, and streamlining processes for better customer service.

Managing customer-specific interest rates is no longer a mere operational task; it’s a strategic imperative. There are challenges for banks looking to transform their deposit management strategies with a focus on customer centricity. But the right externalized rule-based platforms can help banks address these challenges and deliver personalized, value-driven financial solutions to their customers. After all, the future of banking lies in agility, adaptability, and technical prowess.

Sources

1, 2 & 3 Simon Kucher

4 Fortune

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Sources

1, 2 & 3 Simon Kucher

4 Fortune