As corporate and commercial banks navigate increasingly complex client demands, the importance of digital transformation through data and analytics has never been more critical. With revenues reaching $2.3 trillion, this sector significantly contributes to global banking revenues. However, meeting client expectations poses new challenges, as corporate and commercial clients now seek more than traditional loan options. They desire personalized offerings that include digital, real-time payments, cash forecasting, and advanced spend analytics, along with support in areas like decarbonization. The emergence of fintechs further intensifies competition across key domains such as payments, lending, and securities trading.
Frontline staff, particularly relationship managers (RMs), bear the brunt of these complex demands. Juggling existing accounts often leaves them little time to explore new client opportunities. Insights from McKinsey interviews reveal that many RMs struggle to acquire new clients, with most securing fewer than five each year. This underperformance represents a significant revenue loss and untapped potential for existing clients.
The Next Generation of Frontline Technology
To address these challenges, banks are rethinking their technological approach. Instead of overwhelming RMs with multiple tools for various tasks, some institutions are leveraging data and advanced analytics (AA) to create a unified platform within their customer relationship management (CRM) systems. This integrated solution empowers RMs to better understand their clients and uncover new sales opportunities.
These AA-enabled workbenches deliver tailored insights, such as potential new clients, product recommendations, revenue potential calculations, and churn risk assessments. By centralizing information and streamlining workflows, these platforms allow RMs to navigate client complexities more effectively and enhance service delivery.
Accelerated Adoption of Advanced Analytics
A recent McKinsey survey revealed that all participating banks accelerated their adoption of AA-enabled digital solutions over the past two years. However, many organizations are still figuring out how to implement these solutions effectively, with approximately 75% still in the experimentation phase.
Impact of Advanced Analytics Initiatives
Implementing an integrated, data-driven approach can transform how frontline employees utilize technology, resulting in substantial performance and efficiency gains. McKinsey’s pilot tests showed that RMs using AA workbenches experienced 9% portfolio growth over 12 months, compared to just 5% for those not using the tools. Additionally, they expanded their growth across more clients, received five times more cross-selling ideas, and spent 90% less time on account planning.
Such improvements can drive significant revenue growth for banks. For example, a leading European bank harnessed client data to develop an AA model that enhanced account planning, leading to revenue growth three times faster than the market average. Similarly, a regional U.S. bank increased its new customer opportunities fivefold and generated three to four suggested actions for each existing client, positioning itself for more than 20% revenue growth over three years.
Key Benefits of AA Workbenches
The adoption of AA workbenches has led to several advantages:
- Improved client prioritization based on intrinsic needs rather than merely wallet size, allowing RMs to allocate their time effectively.
- More time for RMs to engage in value-adding activities.
- A comprehensive coverage model that encompasses all product offerings.
- Easy access to critical information for RMs and team leaders through a streamlined CRM workflow.
- Enhanced performance management and accountability for RMs, facilitating better tracking and benchmarking against peers.
Best Practices for Successful Implementation
For AA workbench initiatives to succeed, frontline adoption is crucial. Here are seven best practices that can enhance the likelihood of successful implementation:
- Integrate Tools into a Broader Strategy: Positioning new tools as part of a comprehensive growth program makes them more appealing to RMs.
- Prioritize Use Cases from the Frontline: Involve RMs in selecting high-impact use cases to drive engagement and relevance.
- Invest in User Experience: Ensuring a seamless and intuitive experience for RMs can significantly impact adoption rates.
- Create a Dedicated AA Team: Deploying a small, focused team can lead to deeper expertise and better alignment with RM needs.
- Build Trust with RMs: Delivering actionable insights and relevant information fosters trust and engagement.
- Plan for Continuous Improvement: A clear roadmap for enhancing AA capabilities will keep RMs engaged and informed about progress.
- Adapt the Operating Model: Align training, incentives, and collaboration between RMs and product specialists to maximize the benefits of advanced analytics.
Conclusion
As corporate and commercial banks strive to meet increasingly sophisticated client needs, embracing digital transformation through data and analytics has become essential. Leading banks that initially leveraged analytics for midsize businesses are now scaling these successes across the entire sector, serving clients from global multinationals to small enterprises.
By prioritizing data-driven decision-making, banks can empower RMs to identify and prioritize client opportunities effectively, leading to improved performance and growth. Mastering digital transformation is no easy task; it requires strategic focus, talent development, agile delivery, and a commitment to continuous improvement. However, getting it right can yield substantial rewards, positioning banks to thrive in high-growth areas of the market.
Based on insights from McKinsey. Click here to read more: https://www.mckinsey.com/industries/financial-services/our-insights/the-data-and-analytics-edge-in-corporate-and-commercial-banking
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