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Revolutionizing Corporate Banking: The Power of Data Analytics Implementation

Writer's picture: WAU MarketingWAU Marketing

WAU has been at the forefront of leveraging technology as an enabler for over two decades, empowering businesses across industries to achieve their strategic and market objectives. The banking sector is no exception, with corporate and commercial banking standing out as areas poised to reap significant benefits from technological advancements.


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The Data-Driven Transformation of Corporate Banking


Drawing insights from McKinsey’s article “The data and analytics advantage in corporate and commercial banking,” we’ve analyzed the profound impacts and challenges of implementing data analytics in this crucial banking sector.


The Evolving Landscape of Corporate Banking


Corporate and commercial banking, with its staggering $2.3 trillion in revenues, plays a pivotal role in the global banking sector’s income. In the United States, this segment has outpaced GDP growth by twofold. However, the market has become more challenging than ever before.


Today’s corporate and commercial clients are no longer satisfied with traditional loan and credit offerings. They seek personalized services that provide a broader range of solutions, including:

  • Real-time digital payments

  • Fee-based transactional services

  • Advanced financial solutions beyond traditional banking, such as:

    • Detailed expense analysis

    • Comprehensive liquidity forecasts


Furthermore, these clients expect banks to possess specialized capabilities and industry expertise to support their global supply chains and address evolving customer needs. The rise of fintech competitors, making significant inroads in payments, lending, and securities trading, further compounds this expectation shift.


The Digital Transformation Imperative in Customer Service


In recent years, banks have implemented various technological tools to enhance the efficiency and effectiveness of their Relationship Managers (RMs). However, many of these solutions fall short in usability and fail to leverage data comprehensively to generate actionable insights. Key challenges include:

  • Due to incomplete automation, account planning, customer potential estimations, and pricing strategies often require additional time and effort.

  • Data is frequently fragmented and rarely combines internal and external sources to provide a holistic view of customer needs.


The Shift Towards Unified Data Analytics Platforms


Progressive banks are pivoting their approach. Instead of offering many tools for different tasks, they harness advanced data analytics to build unified, intuitive platforms integrated within their CRM systems. This approach empowers RMs to gain deeper customer insights and generate new sales opportunities in every interaction.


These advanced analytics-powered platforms offer personalized insights such as:

  1. Identification of new client opportunities

  2. Recommendations for additional product acquisitions

  3. Potential revenue estimations

  4. Detailed pricing guidance

  5. Early detection of at-risk clients


Designed as centralized hubs, these tools consolidate all the information an RM or team leader needs to navigate the complexities of customer expectations and deliver superior service.


The State of Data Analytics Adoption in Banking


A September 2022 McKinsey survey of 70 corporate and commercial banks revealed that all participants had accelerated the adoption of data analytics-enabled digital solutions for frontline operations in the past two years. However, many organizations are still in the learning phase:

  • Approximately 75% of respondents indicated they were in the experimentation stage.

  • Some faced challenges in realizing tangible results from their investments.


The Transformative Impact of Integrated Data Analytics


Adopting an integrated, data-driven approach can radically transform how frontline employees utilize technology, significantly improving efficiency and results. McKinsey’s pilot tests revealed:

  • RMs using data analytics platforms experienced a 9% growth in their portfolios over a year, compared to 5% in control groups.

  • They successfully distributed this growth across a broader client base.

  • RMs received five times more cross-selling ideas.

  • Time spent on account planning was reduced by 90%.


This level of performance can substantially impact a bank’s revenue. For instance, a leading European bank implemented a data analytics model that optimizes account planning and estimates revenue potential for each existing and prospective client. By empowering RMs with this data, they achieved revenue growth three times faster than the market average.


Overcoming the Challenges of Data Analytics Implementation


Implementing data analytics platforms presents significant challenges for banks:

  1. Legacy System Integration: One primary hurdle is integrating these tools with legacy systems, often ill-equipped to handle complex, real-time data flows.

  2. Data Quality and Consistency: Many organizations operate with fragmented information and misaligned internal and external data sources, creating obstacles to data quality and consistency.

  3. Organizational Resistance: There’s often resistance to change within bank structures, where teams may be accustomed to manual processes or traditional tools.

  4. Initial Investment: The upfront investment in technological infrastructure and specialized talent can be substantial. If not appropriately managed, results may take longer to materialize, potentially hampering the organization's ROI and enthusiasm for change.


Conclusion: The WAU Approach to Data Analytics Implementation


At WAU, we’ve supported a diverse clientele in implementing Data Analytics systems across various industries. We’ve assisted numerous clients in modernizing their systems and processes in the financial sector, starting from legacy systems. Our approach enables seamless integration with other systems and data sources, reducing the complexity of applying Machine Learning models for these analyses. This results in significantly reduced implementation times and associated costs.


We believe that leveraging insights from internal resources with extensive market knowledge and efforts from technology partners specializing in the modernization and digitization of financial systems is the path forward. This approach facilitates the implementation of data analytics technologies, supports the success and time-to-market of these solutions, and empowers relationship managers to grow and maximize their portfolios.


By embracing data analytics and cloud infrastructure, banks can streamline their operations and make more informed decisions, manage risks more effectively, and ultimately deliver superior value to their corporate clients in this rapidly evolving digital landscape.

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