Digital may be binary, but service is not. To improve both the quality of client relationships as well as their own cost performance, corporate banks need to apply digital tools and practices more broadly and with greater nuance. As it is now, traditional corporate banking service relies almost exclusively on the acumen and interpersonal talent of relationship managers (RMs) to build and deepen corporate relationships, acquire customers, and drive revenue. But this approach no longer delivers the revenue that corporate banks need in a slow-growth, yield-deprived environment. 

It’s time for corporate banks to change the way they serve clients. They need to start employing a mix of digital and human-enabled services that will enrich the client experience, improve cost performance, and sustain growth. Leading banks will go a step further and transform their relationship models by providing a different mix of digital and nondigital services for each customer segment: a digital, self-service experience for small businesses, a hybrid “man and machine” offering for midmarket clients, and a highly personalized, digitally augmented service model for large corporations that have the most sophisticated needs and requirements. 

Our work with corporate banking clients has shown that when institutions digitize their relationship models in this way, they have the potential to increase revenue by 15% to 25%, decrease costs by 5% to 15%, and improve return on regulatory capital by 5% to 10%.

Two Emerging Digital Archetypes

Banks can redesign their client service models by incorporating digital tools and techniques in two broad ways: by adopting both a mostly virtual model that allows clients to conduct a majority of their business activities using digital self-service channels and a bionic model that provides a mix of human and digital client service interaction.

The benefits of both the virtual and the bionic models span the entire value chain. On a sales performance level, high-quality data infrastructure can help banks capture internal data on customer journeys and improve pain points. Share-of-wallet analyses can help RMs identify cross-selling and upselling opportunities, while real-time, integrated customer relationship management systems can provide RMs with richer and more accurate insights. From a risk and compliance perspective, integrated systems can help banks meet compliance demands more efficiently, and predictive analytical capabilities can help them assess and prioritize their clients more quickly and more accurately. 

The Virtual Archetype 

The virtual archetype takes a digital-first approach. User-friendly automated platforms and self-service applications allow clients to complete most tasks on their own. Chatbots enabled by robots and human phone teams enabled by artificial intelligence (AI) can provide additional assistance. 

Such applications of digital technology offer banks and customers an array of opportunities. Preapproved credit limits, for example, can be automatically generated using predictive risk models that draw information from shared account balance statements. Both open banking and the new Payment Services Directive 2 (PSD 2) regulations in Europe make this type of information available. Banks can also pull data from public information sources such as Yelp, TripAdvisor, and Amazon to color in additional detail and inform decision making. Credit lines can be rated in real time and credit decisions delivered in minutes instead of the days or weeks it now often takes. Even the client-onboarding process can be completed entirely online, with know-your-customer (KYC) documentation uploaded directly from the customer’s office. Application-programming interfaces (APIs) and other integrated software can be used to check third-party databases, such as the commerce registry, to validate identity and other background information. 

Under the virtual archetype, human interactions won’t go away entirely but will be limited to periodic account reviews and other key moments when one-on-one advice or engagement is critical. This virtual archetype substantially lowers the cost to serve clients by improving productivity and scalability and by allowing banks to reflect those efficiencies in their pricing and fees. This model is especially well suited to small businesses given that most of their banking needs consist of routine monetary transactions and basic services that lend themselves to automation. We also expect that a certain percentage of similarly routine large and midmarket businesses will migrate to this virtual archetype. 

Some banks are already moving in this direction. UK-based Tide, a digital-only bank, uses AI-enabled systems to scan and categorize small-business invoices automatically for quicker, less expensive processing. And JPMorgan and BBVA Compass have teamed up with the fintech OnDeck to make small-business lending decisions in real time via online applications, leveraging advanced analytics that take into account 2,000-plus data points from more than 100 publicly available sources.

The Bionic Archetype

The bionic archetype, by contrast, focuses on providing a high-touch, digitally enhanced relationship. Data-driven processes, dashboards, and metrics allow RMs to offer personalized insights and responsive service on an array of issues—but in a far more cost-effective and repeatable way. Specialized tools and analytics cut down on the need for manual inputting and fact finding and improve the quality and quantity of client-facing time. 

Under this model, RMs can use software and analytics that gather intelligence from internal and external data sources to conduct predictive risk modeling and improve client acquisition and cross-selling. For example, an Indian bank developed a pipeline management tool with “next best offer” insights and integrated share-of-wallet information. The tool integrates information from across the bank’s client base, providing RMs with real-time alerts on this information to their mobile devices—resulting in a 20% to 30% increase in productivity for the bank. Similar steps helped one central European bank improve revenue by 10% to 15% in its large-corporate segment and led to a 30% bump in new clients in its small-business and midmarket segments. 

Better integration of client account histories across the bank can help RMs optimize pricing, on the basis of a client’s known price elasticity, product usage, and commercial potential. Digital dashboards with metrics that track pricing, discounts, and other variables can help RMs and their respective leaders ensure better discipline and transparency across the salesforce. Those insights can help them identify top performers, zero in on the most effective sales practices, and allocate resources more effectively. 

The bionic model is especially well suited to clients that have significant liabilities, capital markets funding, and bespoke hedging needs and that are willing to pay for premium service. This client segment tends to comprise mostly large corporations but may also include some midmarket companies.

Applying the New Archetypes to Different Client Segments

While banks have long segmented clients based on a company’s size, geographic reach, and business requirements, they typically have not differentiated the ways in which they service those segments. RMs may spend a roughly equal amount of time attending to their small and large clients, even though large clients tend to be more profitable. In addition, inadequate process automation exacerbates these productivity issues. Our client work shows that a substantial portion of an average RM’s day is spent tracking needed information internally or dealing with administrative tasks instead of being in front of clients. 

In addition, fragmented data management practices can make it hard for banks to understand client needs and expectations and gauge what types of add-on services or relationship interactions would be most helpful. With the quality of the customer experience becoming increasingly important, accessing such insights has become more crucial than ever.

By redefining the relationship model based on the specific needs of different segments and incorporating digital tools, processes, and techniques into the service experience, corporate banks have an opportunity to improve client satisfaction, productivity, and innovation—factors that are central to bank growth. Following are our recommendations for how banks can use digital tools and practices in support of more effective client coverage.

Small Businesses 

Generally speaking, this segment of smaller players requires simple, effective, standardized solutions. Typical small-business banking needs include basic cash management, term loans and hedging strategies, foreign exchange, and payment facilities. For corporate banks that serve this segment, critical success factors include service integration, the ease and speed of execution, and reducing the cost of serving clients. These needs can generally be met using digital and online channels, given that the simplicity and standardization of the customers’ needs are matched by the efficiency of the platform interaction and the streamlined product offerings. As a result, the bank-client relationship no longer demands substantial human intervention.

Here’s how that might look across different customer journeys:

• Prospecting and Onboarding—Typically a Virtual-Bionic Hybrid. To sign up for an account or service today, small-business clients must call or visit a bank and must confine their interactions to typical banking hours. Banks can meet these clients’ needs more rapidly by digitizing core onboarding journeys—offering user-friendly mobile apps, integrating behind-the-scenes processing, and applying big data analytics to expedite credit checks and reviews.
• Credit and Complex Products—Typically Virtual. Instead of manual credit review processes that rely on static financial information, digitized tools and systems allow banks to source near-real-time data from various internal and external sources. These include transaction histories, online marketplaces, and financial and market trend data. Combined with predictive risk-scoring analytics, such information can enable faster and more accurate credit decisions and can allow banks to service small-business customers whose financial histories may not otherwise conform to traditional credit review processes. 
• Transactions—Typically Virtual. Virtual transactions can streamline payments, billing, and invoicing, making it easier for small companies to do business. Most wire transfers and foreign-exchange transactions can be originated online, with exceptions routed through call center validation processes that are enabled by natural-language and AI techniques.

The basic small-business banking model could be augmented with a suite of simple value-added services such as business-planning tools that can help the bank maximize customer engagement. Banks that shift their small-business segment to this type of predominantly virtual model have the potential to increase revenue by 20% to 30%, reduce costs by 15% to 30%, and raise their return on risk capital (RORC) by 15% to 25%. 

Midmarket Companies

Many midmarket customers can be serviced using a hybrid model in which companies conduct the majority of their banking online while receiving dedicated support for more complex or high-stakes operations. Prospecting tools and advanced analytics can allow banks to refine their service further, helping RMs anticipate client needs and provide tailored recommendations that lead to richer and more personalized conversations with their customers.

Here’s how that might look across different customer journeys:

• Credit and Complex Products—Typically Hybrid. Automated platforms can help midmarket clients receive hassle-free preapprovals for routine lending needs, while specially trained RMs assist companies with more complex financing, risk management, and investment needs. Credit applications would no longer be perceived as the black box they are today—with cycle times that can last weeks. Instead, predictive-risk models with real-time data can provide faster and more accurate credit ratings. Analytics that pick up signals in account statements and across the client’s distribution channels can be used to provide clients with more tailored working-capital solutions. Product specialists can then step in to support the relationship where required—for example, if complex supply chain or multi-entity support is needed, they can tailor suitable solutions and provide pertinent, proactive advice.
• Transactions—Typically Virtual. Banks can automate and augment many common transaction journeys, making it simpler and easier for midmarket clients to access banking services. Data from a bank’s platform, for instance, can be embedded into the clients’ accounting software and treasury tools. Intuitive user interfaces can simplify processes for the client—guiding them through each step and providing real-time confirmation and account statements. The embedded nature of the system can further cement the bonds between bank and client. For clients with large international exposures, banks can offer specialized solutions—programs and digitally enhanced service modules that support foreign exchange, hedging, and trade finance. RM engagement can then be reserved for the most complex service needs and questions.

Banks that adopt this hybrid service could see a revenue uplift of 15% to 25%, cost reductions of 5% to 20%, and a bump in RORC of 5% to 10%.

Large Corporations

Owing to their size and scope, large corporations require more complex, bespoke solutions and advice. Corporate banks that foster long-term relationships with these clients can add significant value through their deep institutional knowledge. While a high-touch relationship is key, the substantial transaction volume means that banks also need to increase their use of automation and should integrate platforms as well as systems to deliver services and advice more efficiently. Winning banks in this segment will use digital tools and practices to enhance the current relationship model and improve transaction costs and speed. 

Here’s how that might look across different customer journeys:

• Overall Relationship—Mostly Bionic. When servicing large corporations with a variety of needs, banks can use digitized tools and services to personalize and enrich their offerings. Automated prompts backed by analytics can send RMs next-best-offer recommendations or flag clients whose profile data shows a change in business volume or a shift in the client’s business makeup, such as a merger or a supply chain disruption. These prompts can help RMs optimize when and how they engage to improve service and retention. By using these tools, RMs can provide more personalized, concierge-style service. 
• Transactions—Typically Hybrid. Large corporations are looking for banks to provide an integrated transaction banking experience to handle core payments, cash management, and other needs. By blending those capabilities with one-on-one RM engagement, banks can give clients a differentiated degree of service—and help them manage complex account management rules, cash pooling, and other needs swiftly and with greater convenience.
• Service—Typically Bionic. Banks can offer large corporate clients superior service through dedicated face-to-face and remote access to specific RMs, transaction specialist support teams, and relationship support teams via phone or email. And integrated analytics and tailored advice allow banks to provide these clients with sophisticated modeling and deep insights from bank experts. 

Banks that adopt this type of hybrid service model for their large corporate clientele could raise revenue by 10% to 20%, lower costs by as much as 10%, and increase RORC by 1% to 6%.

Getting Started

Banks that are interested in taking advantage of these opportunities must first lay the groundwork. That includes investing in the following foundational capabilities:

• Data. They need to harness internal and external data sources to inform and provide insight into the relationship management process.
• Infrastructure. Banks must employ appropriate hardware and software (including cloud computing) to analyze, capture, store, and distribute ever-larger amounts of structured and unstructured data.
• Analytical Toolkits. They should use a variety of analytical tools, from predictive and statistical modeling for simpler processes to AI and machine learning for deeper insights and improved decision making.
• Partnerships. To create the capabilities necessary for digital success, banks also need to consider partnerships. Options include partnering with fintechs (for example, JPMorgan and OnDeck), acquisitions (for instance, BBVA and Openpay), and internal digital incubators (such as the Wells Fargo Startup Accelerator).

Banks can use digital tools and techniques to transform their sales and customer service models. Digitally enabled relationship management models can play a powerful role in improving customer satisfaction while lowering costs and ensuring long-term profitability. The size of the prize is significant and—with the disruption of the traditional model already under way—the time to act is now.