As banks address more intricate customer needs, new data-driven and analytics-enhanced tools can assist the front line in comprehending their clients better and boosting sales.

In some countries, banking revenues have grown at twice the rate of GDP growth. However, excelling in this industry has become increasingly difficult. Customers now expect more than the standard selection of loans and credit products. They seek personalized services from a broader spectrum, including transactional and fee-based offerings like digital, real-time payments, and additional features such as spend analytics and cash forecasting. Compounding these challenges, FinTech companies are competing for market share in areas like payments and lending.

Meeting complex client demands largely falls on a bank’s frontline staff, particularly its relationship managers (RMs). These employees, who handle customer interactions, are often overwhelmed by the current demands. Consequently, RMs frequently focus on a small subset of existing customers, leaving little time to pursue new opportunities for the bank or to find suitable solutions for other valuable clients. Many executives admit to difficulties with client acquisition, resulting in significant lost revenue from both new prospects and untapped value propositions for current customers.

Advanced technology for the frontline

Banks have implemented various technological tools to aid RMs in serving clients more efficiently. However, many of these tools are not user-friendly and fail to utilize data comprehensively to provide insights. Solutions for account planning, assessing client potential, and pricing often lack full automation, demanding extra time and effort from RMs. Additionally, the data inputs are frequently incomplete and rarely integrate both internal and external sources to offer a holistic view of a client’s needs and circumstances.

Some banks are adopting a new strategy. Rather than equipping the front line with numerous tools for various tasks (one bank had over 30), they are leveraging data and advanced analytics (AA) to create a unified, user-friendly, and intuitive platform within the Customer Relationship Management (CRM) system. This method aids RMs in comprehending their customers better and facilitates generating new sales opportunities within each customer relationship.

Driven by data, these CRM (Customer Relationship Management) systems provide a range of customized insights, including new client opportunities, recommendations for next products to purchase, calculations of client revenue potential, detailed pricing guidance, and identification of clients at risk of leaving. These platforms serve as a comprehensive hub containing all the information needed by an RM (relationship manager) or team leader, helping frontline employees manage the complexity of client expectations and deliver superior service.

A significant number of banks have expedited their integration of AA(advanced analytics)-powered digital frontline solutions across various regions and tiers in the past couple of years. However, numerous institutions are still in the process of developing and deploying these solutions. About three-quarters of the banks mentioned that they are currently in the experimental phase, with some encountering challenges in realizing the benefits of their investment.

The effects of a prosperous advanced analytics endeavor

A cohesive, data-centric strategy marks a notable shift in how front-line workers leverage technology and can result in considerable enhancements in performance and productivity. Various trial runs conducted across several banks indicate that relationship managers (RMs) utilizing CRM systems experienced a 20% expansion in their portfolios over a year, in contrast to control groups that witnessed 5% growth without CRM usage. Furthermore, these individuals distributed this growth across a wider client base, received fivefold more cross-selling suggestions, and reduced the time spent on account planning by 90%.

A unified, data-focused strategy marks a transformative shift in how front-line staff harness technology and has the potential to yield substantial improvements in performance and operational efficiency.

Such heightened performance levels can translate into notable revenue expansion for a bank. For instance, a prominent European bank leveraged customer data to construct a CRM model, refining account planning and quantifying the revenue prospects of each current and potential customer. Empowering RMs with this data facilitated revenue growth three times faster than market norms. Consequently, the bank anticipates a revenue surge exceeding 20% over a three-year period.

In addition to these outcomes, banks that have adopted CRM systems have observed additional advantages:

• Enhanced client prioritization based on their specific needs and their capacity to generate value for the bank, rather than relying solely on wallet segmentation. This approach empowers RMs to allocate the right amount of time and attention to individual accounts.
• Increased availability of time for RMs to engage in activities that contribute value.
• A refined coverage model that encompasses all product offerings.
• Access to crucial information for RMs and team leaders, facilitated by a revamped front-end workflow within the CRM system.
• Transparent RM performance evaluation and accountability, including the ability to establish escalation pathways to sales managers, track initiatives, and compare frontline performance against predefined targets and peer institutions.

The execution of a plan holds significant importance

In CRM initiatives, the primary determinant of success is the adoption by frontline staff. Even with advanced tools, their effectiveness hinges on whether RMs perceive their value. Placing frontline employees’ experiences and insights at the forefront is crucial for ensuring the initiative’s success.

Here are seven common practices observed in banks with impactful CRM initiatives:

1. Presenting new front-end tools within a broader strategic growth program:
   Framing CRM systems as integral parts of long-term strategic plans rather than standalone initiatives increases frontline adoption rates.
2. Prioritizing use cases based on frontline input:
   Involving RMs in the selection of initial use cases fosters engagement and ensures that the CRM system addresses their most pressing needs.
3. Investing in RM user experience:
   Enhancing the usability and integration of CRM systems into daily workflows through intuitive design and streamlined technology stacks improves adoption rates among RMs.
4. Establishing a dedicated CRM team:
   Deploying a specialized team focused on CRM development and implementation allows for deeper domain expertise and more effective communication with frontline staff.
5. Building trust with RMs:
   Ensuring that the initial version of the CRM system provides actionable insights and valuable information tailored to RMs’ needs fosters trust and encourages adoption.
6. Continuously enriching CRM capabilities:Having a clear roadmap for enhancing and expanding CRM functionalities over time, including integrating new data sources and advanced modeling techniques, ensures ongoing relevance and effectiveness.
7. Adapting the operating model:
   Implementing comprehensive training programs for RMs, aligning incentives between RMs and product specialists, and fostering collaboration through joint performance indicators are essential for maximizing the impact of CRM initiatives.

As banks face the challenge of meeting increasingly complex client needs, leveraging data and analytics has become essential. Initially, leading banks found success by utilizing frontline tools powered by data and analytics to enhance client service. The CRM system plays a crucial role in helping relationship managers (RMs) prioritize clients and opportunities, allowing them to focus on value-adding activities and providing transparency on key performance indicators. However, mastering digital and analytics requires banks to address various aspects such as strategy, talent, agile delivery, technology, data, and operating models. Despite the challenges, achieving success in these areas can lead to significant impact and enable banks to compete effectively in high-growth areas.