As AI Targets Business Banking, Will Relationship Managers Become Obsolete or Superpowered?
Commercial banking stands at a crossroads where human expertise meets artificial intelligence. While relationship managers remain essential to client service, new technologies are reshaping how they work. It's a shift that could redefine how banks deliver their most valuable service: personalized, informed advice.
By Garret Reich, Senior Project Manager at The Financial Brand
The report: Supercharged banking relationship manager
Source: Deloitte
Why we chose the report: There is very little information available to financial institutions on how to integrate AI into business relationships. However, there are plenty of use cases for it — especially when financial institutions struggle to find that their banking provider understands, and can personalize, their UX.
Executive Summary
In an era where artificial intelligence dominates headlines, one critical banking role remains stubbornly human: the business banking relationship manager.
The human touch isn’t going anywhere. However, emerging technologies are poised to dramatically enhance how these key players serve their commercial banking clients. A new Deloitte report reveals that while 70% of commercial banking clients prioritize customized solutions, only 37% feel their relationship managers truly understand their needs — highlighting a crucial gap that smart technology could help bridge.
This technological evolution isn’t about replacing relationship managers but rather "supercharging" them with AI-powered insights, API-driven data integration and strategic alliances. With 82% of relationship managers actively seeking better tools to serve clients, the banking industry stands at a pivotal moment where human expertise meets artificial intelligence to deliver truly personalized service at scale.
Key Takeaways:
- Only 37% of commercial banking clients say their relationship manager understands their wants and needs, despite 81% preferring to work directly with their relationship manager
- A typical relationship manager maintains about 100 client relationships, but only about 37 of those are deep, high-functioning relationships where they truly know the client’s goals and challenges
- Emerging technologies like generative AI could help relationship managers increase their portfolio of deep relationships to upwards of 50 to 60 clients by automating administrative tasks and providing real-time insights
What we liked about the report: We have not seen many other reports that dug into AI in B2B relationship management — a generally neglected topic in the industry;
What we didn’t: It is very short and open-ended.
The Human Element Remains Central
While digital transformation sweeps through banking, the relationship manager’s role as trusted advisor has only grown more critical. Commercial banking clients — particularly small and medium-sized enterprises — continue to value human relationships in navigating complex financial decisions. The challenge isn’t replacing this human element but rather enhancing it through strategic use of technology.
For most commercial clients, their relationship manager serves as their primary point of contact with the bank, with a little over four out of five (81%) preferring to work directly with their relationship manager over other bank representatives. This preference is particularly strong when the relationship manager is a senior manager or influential figure within the bank, highlighting the value clients place on experience and institutional knowledge.
A Three-Pronged Technology Approach
Deloitte identifies three key technologies that can transform relationship management: APIs, artificial intelligence and strategic alliances. APIs serve as crucial connectors, pulling data from multiple legacy systems to create comprehensive client views. AI (including generative AI) can analyze this data to provide actionable insights and automate routine tasks. Meanwhile, strategic alliances with technology vendors and partners can expand capabilities without massive infrastructure investments.
This modular approach allows banks to implement improvements incrementally, rather than requiring complete system overhauls. By focusing on specific pain points and opportunities, banks can achieve meaningful improvements in relationship manager effectiveness without disrupting existing operations.
Imagine a relationship manager walking into a client meeting armed with AI-generated insights about recent industry developments, the client’s financial patterns and potential product opportunities — all updated in real-time.
This isn’t science fiction. New tools can transcribe meetings, flag action items and even begin generating necessary documentation while the conversation is still happening.
Consider a scenario where a relationship manager meets with a manufacturing client. During the conversation, AI tools could analyze the client’s recent transactions, industry news about supply chain disruptions and market trends to suggest relevant financial products or services. The system might flag that the client’s working capital needs typically increase during certain seasons or that their industry peers are increasingly using specific hedging strategies.
The Power of Predictive Analytics
Beyond day-to-day interactions, emerging technologies can help relationship managers anticipate client needs before they arise. By analyzing industry trends, company financials and market data, AI systems can flag potential opportunities — like when a client might need acquisition financing or hedging products. This proactive approach transforms relationship managers from reactive service providers to true strategic advisors.
For example, if two competitors in a client’s industry announce a merger, the AI system could automatically alert the relationship manager and provide relevant information about financing options and industry implications. This allows the relationship manager to reach out proactively with valuable insights rather than waiting for the client to inquire about financing options.
One of the biggest challenges facing relationship managers is fragmented information. Clients interact with multiple bank departments, but these touchpoints often remain siloed. Modern API architecture can break down these barriers, giving relationship managers a complete view of client interactions across the organization. This comprehensive perspective enables more informed conversations and better service delivery.
These interactions might include everything from routine document submissions to conversations with specialists in areas like trade finance or treasury management. By consolidating this information, relationship managers can better understand their clients’ full relationship with the bank and identify opportunities to deepen engagement.
Enhancing Client Experience Through Technology
While the focus is often on internal efficiency, these technological improvements significantly impact client experience. When relationship managers have better tools and information at their disposal, they can provide more timely and relevant advice. This is particularly crucial for complex commercial banking relationships where clients expect their banking partners to understand their business deeply.
The technology also helps address a common client frustration: having to repeatedly explain their situation to different bank representatives. With comprehensive data at their fingertips, relationship managers can ensure continuity in client interactions and demonstrate a thorough understanding of the client’s history with the bank.
For team managers, new technologies offer unprecedented visibility into relationship manager performance. Analytics can track key metrics like sales cycles, win rates and sector performance. This data helps identify best practices and areas for improvement while giving relationship managers insights into their own effectiveness.
These metrics can also help banks optimize their relationship manager deployment, ensuring that client relationships are matched with the most appropriate relationship managers based on industry expertise, relationship depth and other factors.
Training and Development in the Digital Age
The implementation of new technologies also creates opportunities for enhanced relationship manager training and development. AI systems can identify patterns in successful client interactions and share these insights across the relationship manager team. Additionally, predictive analytics can help new relationship managers get up to speed more quickly on client relationships and industry dynamics.
This is particularly important given the aging workforce in commercial banking and the need to transfer knowledge effectively to the next generation of relationship managers.
While the potential benefits are clear, banking providers must navigate several challenges in implementing these technologies. Privacy and security concerns must be carefully addressed, particularly when dealing with sensitive client information. Additionally, banks need to ensure that relationship managers receive adequate training and support to effectively use new tools without becoming overwhelmed.
The Future-Proofed Relationship Manager
By deploying modular technologies thoughtfully, banks and credit unions can help their relationship managers deepen client relationships and deliver more of what clients value most: knowledgeable, timely advice backed by data-driven insights.
The future of commercial banking won’t be purely digital, nor will it rely solely on human relationships. Instead, success will come from strategically blending both elements — using technology to enhance rather than replace the crucial human connections that drive the industry. For financial institutions willing to invest in "supercharging" their relationship managers, the potential rewards include deeper client relationships, increased efficiency and sustainable competitive advantage in an increasingly complex market.
Editor’s note: This article was prepared with AI language software and edited for clarity and accuracy by The Financial Brand editorial team.
