According to the Federal Reserve Bank of St, IHS Global Insight, Corporate and commercial banking continues to be a substantial contributor to total global banking revenues, with $2.3 trillion in revenue (Exhibit 1). In the U.S., this sector has grown at a rate that is double that of GDP growth.1 Despite this, succeeding in this sector is more difficult than ever before. Clients are no longer content with the traditional range of loans and credits. They are demanding personalized services, such as digital and real-time payments, spend analytics, granular liquidity and cash forecasting and more. Banks must also have the capabilities and industry-specific knowledge to work with corporate and commercial clients across their global supply chains, as well as help them to address new issues, such as decarbonization. Adding to this complexity is the presence of fintechs, which are competing for market share in areas like payments, lending, and securities trading says MCKinsey & Company.
Exhibit 1
Frontline staff, such as relationship managers (RMs), bear the brunt of the responsibility to meet the complex needs of clients. With the demands of current customers, RMs are often too busy to develop new business and find the right solutions for other customers. According to McKinsey’s interviews with executives at 15+ banks, most RMs acquire fewer than five new clients per year. This shortfall results in a loss of revenue, both from new opportunities and from untapped value propositions for existing customers.
Banks Struggling to Fully Leverage Tech Tools to Support RMs
Banks have implemented a variety of technological tools to assist Relationship Managers (RMs) in providing clients with more efficient and effective service. Unfortunately, these solutions often lack in usability and are not fully capable of utilizing data to generate meaningful information for RMs. For example, account planning, client potential, and pricing solutions are not automated and require extra effort from RMs. Moreover, the input data is often incomplete and does not include both internal and external sources to gain a comprehensive understanding of a client’s needs and situation.
Advanced Analytics to Create Unified, Intuitive Platforms for Relationship Managers
Rather than equipping the frontline with a multitude of distinct tools for various purposes (in one case, McKinsey noted more than 30), banks are now turning to data and analytics to devise a unified, navigable platform within the CRM. This can aid relationship managers (RMs) in achieving a deeper understanding of their customers, and give rise to increased sales in each customer relationship.
These analytics-powered workbenches offer tailored insights such as opportunities for new clients, next products to purchase, revenue potential calculations, detailed pricing information, and warnings of clients at risk of churn (Table). Aimed at being a hub of all the information necessary for an RM or team leader, these platforms aid frontline employees in dealing with the complexity of client expectations and better serve their customers.
Table. Leading corporate and commercial banks use advanced analytics to empower relationship managers in key areas.
| Pre-client meeting—preparation | Client meeting—negotiation | Post-client meeting—tracking | |
|---|---|---|---|
| Corporate and commercial banking process | Prospecting Prioritization Demand/opportunities | Product offering Pricing | Target tracking Refinement |
| RM needs | Identify likely-to-convert prospects, assess client potential, recommend products, and pinpoint customers likely to churn | Price multiple products at the same time and support price negotiations and what-if scenarios | Set targets based on client potential, monitor sales execution, and identify behavior tied to high performance |
| Advanced analytic models | Prospecting wallet sizing Next product to buy Probability-to-churn | Reference pricing Pricing leakage | Target setting RM effectiveness Churn management |
Source: McKinsey & Company
In a survey conducted by McKinsey in September 2022, 70 corporate and commercial banks reported that over the past two years, they had hastened their adoption of AI-enabled digital frontline solutions across all regions and tiers. However, many of the organizations are still learning how to create and deploy these solutions. Around three-quarters of the surveyed banks indicated that they were still in the testing phase, and some were having trouble seeing the returns from their investment (Exhibit 2).
Exhibit 2
Impact of a successful advanced analytics initiative
An integrated, data-driven approach can have a remarkable effect on the way frontline workers use technology, leading to major improvements in performance and efficiency. McKinsey conducted a pilot test with multiple banks, which revealed that Relationship Managers (RMs) utilizing AA workbenches experienced a 9 percent portfolio growth within a period of 12 months, whereas the control groups who did not use workbenches only recorded a 5 percent growth. Furthermore, the growth was spread across more clients, the RMs received five times more cross-selling ideas, and the time spent on account planning was reduced by 90 percent.
Adopting an advanced analytics workbench has allowed banks to generate significant top-line growth. One European bank, for example, used client data to construct a model that streamlined account planning and calculated the revenue potential of each existing and prospective customer in the market which resulted in an increase in revenue that was three times faster than the market according to McKinsey.
Additionally, the consultancy found, that a regional bank in the United States was able to increase their number of new customer opportunities by five times and achieved a revenue increase of more than 20 percent over three years. A leading bank in the Middle East also saw a 20 percent improvement in lead conversion, and an increase in top-line growth four times greater for their pilot than for control groups.
These banks have experienced several benefits from their AA workbenches, such as better prioritization of clients based on their needs and value generation potential, more time for RMs to focus on value-adding activities, a coverage model that includes all product offerings, key information available to RMs and team leaders, transparency in RM performance management and accountability, and the ability to set escalation paths to sales managers, monitor initiatives, and compare frontline performance against targets and peer institutions.
Practices for Ensuring Frontline Adoption of AA Workbench Initiatives
For an AA workbench initiative to be successful, frontline adoption is essential. To ensure this, placing the experience and perspectives of frontline employees at the core of the process is essential.
Strategic Growth Program Leverages AA Workbench to Improve Employee Engagement: Presenting the AA workbench as part of a comprehensive strategic growth program is far more appealing than introducing it as a stand-alone initiative. When RMs and other frontline workers understand why the tools were developed and how they can support the bank’s three- to five-year agenda, they are more likely to embrace them.
Banks Should Consider Front-Line Priorities for Use Case Selection: Banks should not make use case selection based solely on financial criteria. Instead, frontline staff should be encouraged to discuss their priorities and pick the three to five of the most vital use cases. Examples of front line-prioritized use cases include client acquisition in China, trade finance cross-selling in the Middle East, client potential in North America and markets/foreign-exchange cross-selling in Europe.
When the workbench is up and running, bank management can add functionality based on their priority. In a September 2022 survey, managers were asked to name the two highest value use cases for advanced analytics. The most frequent responses were customer potential or wallet sizing and RM productivity (Exhibit 3). Additionally, ESG use cases such as net-zero analytics are becoming an increasingly important priority.
Exhibit 3
Maximizing RM User Experience: In order to ensure the highest levels of success when investing in RM user experience, banks should prioritize the incorporation of an ideal AA workbench into frontline daily workflows. Additionally, banks should assign their best designers to create RM journeys that are easy to use, intuitive to navigate, and free of complex messaging.
Furthermore, banks should consider adding additional data to the main client screen that quickly shows RMs the upside potential across various products. Finally, banks should also look into streamlining their technology stack and replacing legacy tools like spreadsheets for lead-tracking with digital ones.
Banks Should Consider Small, Specialized Teams for Corporate and Commercial Banking: Due to the lack of talent in data, analytics, and digitization, it may be tempting for banks to assign their digital team to serve retail banking as well as corporate and commercial banking. However, it is difficult to learn the lingo of RMs and gain domain knowledge in corporate and commercial banking without full immersion. For this reason, it may be more effective for banks to put together a small, specialized team of five individuals, instead of shifting 15 to 20 people between businesses.
Integrating Real-Time Financial Monitoring for RMs: Establishing trust with RMs is paramount for successful client satisfaction. The MVP must not only provide data-driven insights but must also include interesting details such as which other RMs previously won similar deals with similar clients. In the 2022 Finalta Corporate Banking Digital Benchmark survey, 63 percent of banks reported that they have integrated real-time financial monitoring that allows RMs to track their own performance, and over 50 percent said they had included personalized next-action recommendations for specific clients according to a Finalta Digital Corporate Banking Benchmark survey.
Road Map for Enhancing Use Cases: AA workbench initiatives that are designed for long-term success have a plan for continued enrichment and expansion over time. This includes incorporating new data sources, refining existing models, and adding new use cases. Additionally, the delivery channels for these use cases must be able to scale and evolve, allowing Relationship Managers to engage with their clients via digital channels and provide them with the most up-to-date insights.
A Comprehensive Approach: In order to maximize the impact of advanced analytics on banking revenues, banks need to adopt a comprehensive approach that involves training Relationship Managers (RMs) on how to effectively use the new workbench. Additionally, banks should find ways to incentivize RMs and product specialists to work collaboratively, such as through shared client visits and other joint performance metrics.
The Bottom Line
As corporate and commercial banks attempt to meet the ever-evolving needs of their clients, data and analytics have become an essential part of their operations. Initially, leading banks have achieved success in leveraging data- and analytics-driven tools to better serve their midsize business clients. Now, they are in the process of expanding this success to the other sections of the corporate and commercial sector, ranging from global multinationals and large domestic companies to small businesses.
The current generation of data- and analytics-driven frontline tools can help Relationship Managers (RMs) prioritize clients and opportunities, thus allowing them to focus on activities that add value. Additionally, this technology provides transparency on critical information, such as the performance of RMs. The challenge of mastering digital and analytics is difficult and requires banks to effectively manage strategy, talent, agile delivery, technology, data, and their operating model. Nonetheless, doing so well can yield a huge impact and help banks compete in high-growth sectors.
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