Fintech Staff Writer
Midsize banks have long occupied a unique position within the financial ecosystem. They were large enough to serve the lending needs of local businesses but small enough to maintain a personal touch, building trust with customers in their communities. However, this once-comfortable niche is rapidly becoming more challenging. Midsize banks now face intense competition from a wide range of players—deep-pocketed larger banks, community-centric small banks, and agile fintech startups. Additionally, they are increasingly at risk of losing their traditional lending market to non-bank entities such as pension funds, insurance companies, and mutual funds.
For midsize banks, the shift has made it harder to maintain the face-to-face relationships that were once the cornerstone of customer loyalty. Meanwhile, commercial banking clients now demand the same level of sophistication and convenience in their banking services that they experience in the retail sector. The challenges for midsize banks have been further compounded by the events of 2023, which saw several regional banks fail, causing many small- and mid-cap companies to transition to larger, more secure financial institutions. Midsize banks also have significant exposure to the commercial real estate sector, where rising interest rates and decreasing occupancy levels have put added pressure on borrowers, making it more difficult for developers to meet loan obligations.
For midsize banks, embracing data and analytics is not just an opportunity—it’s a necessity. By leveraging these technologies, they can enhance decision-making, improve risk management, and better serve an increasingly tech-savvy customer base, positioning themselves for long-term growth in an ever-evolving financial landscape.
Top Challenges Hindering Banking Growth
Midsize banks face several key obstacles that are preventing them from achieving their growth objectives. Among the most pressing challenges are data-related issues, which remain a significant barrier for many institutions.
1. Lack of System Integration
A critical inhibitor to growth is the lack of integration between a bank’s various systems and databases. According to 34.2% of banking executives, this fragmented approach hampers their ability to gain a comprehensive view of customer transactions and interactions. In a competitive landscape, this limitation prevents banks from offering the personalized, seamless experiences that customers expect—whether for deposits, lending, or payment services.
A unified system, on the other hand, enables banks to maximize customer retention, identify supply chain vulnerabilities, and ensure cost-effective compliance. Yet, many midsize financial institutions still rely on disconnected IT systems or outdated enterprise resource planning (ERP) software, which require extensive manual support and result in disjointed data. This fragmented approach puts them at a clear disadvantage, particularly when competing with more digitally agile newcomers.
2. Data Gaps and Insufficient Insights
Data is fundamental to managing risk, ensuring compliance, and driving growth. However, 32.5% of respondents identified the lack of reliable data as a major impediment to their growth strategies. From tracking overnight deposit levels to understanding profitability per customer, banks need comprehensive and actionable data to inform their decision-making. Without this data, they risk making uninformed choices that could impact both profitability and operational efficiency.
3. Inadequate Analytics and Decision-Making Tools
The inability to leverage data effectively points to the need for advanced analytics and decision-making tools. Nearly 50% of respondents (49.7%) listed the implementation of updated analytics tools as a top priority to overcome growth challenges. These tools are critical for transforming raw data into actionable insights, enabling better decision-making, and supporting long-term growth.
To address these issues, banks are focusing on new business software systems (44.1%) and improving system integration (41.3%) to streamline operations and improve data accessibility. These investments are not only aimed at addressing growth constraints but also at simplifying workflows and enhancing business processes—an objective identified by 92.2% of respondents as a key priority.
4. Operational Inefficiencies and Business Silos
The lack of integration and fragmented systems also contributes to operational inefficiencies. A significant number of respondents (38.7%) pointed to weaknesses in their supply chains, which further complicate the path to growth. In addition, business silos (32.6%) and system disconnects (34.6%) remain persistent issues that hinder collaboration, data sharing, and agility within the organization.
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Data and Analytics: The Cornerstone of Modern Banking Growth Strategies
1. Maximizing Internal Data for Strategic Advantage
Internal data is one of the most powerful assets available to midsize banks. When properly harnessed and augmented with external datasets, it provides a comprehensive understanding of customer behavior, preferences, and financial needs. By incorporating external data—such as real-time market conditions, credit histories, and industry trends—banks can enrich their internal datasets, enabling more accurate customer profiling.
For example, combining augmented data in Know Your Customer (KYC) and Know Your Business (KYB) processes allows banks to make more informed, context-based decisions. This creates a dynamic, 360-degree view of each client, which enhances risk assessment and facilitates more personalized offerings. By using these insights, banks can tailor their products and services to better meet customer needs, fostering stronger relationships and improving customer retention.
2. Contextual Decision-Making for Improved Customer Service
When banks integrate both internal and external data, they can gain an enriched understanding of their clients, empowering them to make more informed, contextual decisions. This is particularly important when banks are looking to offer products and services that are not only competitive but also aligned with the evolving expectations of digital customers.
The combination of data sources enables a level of precision in decision-making that enhances customer satisfaction. For example, by understanding customer behaviors across multiple touchpoints, banks can predict their clients’ financial needs, offer timely credit solutions, or tailor deposit products to suit changing life circumstances. This move towards data-backed, contextual decision-making positions midsize banks to compete with larger institutions and fintech disruptors that are already capitalizing on these advanced analytics.
3. Building Ecosystem Connections for Enhanced SMB Support
With the right data infrastructure, midsize banks can also integrate into broader B2B ecosystems, creating value for their small and medium-sized business (SMB) clients. Data-powered solutions can connect banks with an array of business partners, allowing them to offer a wider range of services—from supply chain financing to integrated payments and automated invoicing.
Through strategic ecosystem connections, banks can bring the best B2B solutions to their SMB clients, empowering them with the tools they need to thrive in a competitive market. These collaborations also open the door to new revenue streams and business opportunities, further accelerating growth.
Data Governance and Platform Risk: The Pillars of Secure Banking Growth
As data becomes central to every banking strategy, ensuring that it is properly governed and securely managed is paramount. Robust data governance frameworks are crucial in reducing risk and ensuring compliance in an increasingly complex regulatory environment.
1. Proactive Data Governance for Risk Reduction
A proactive approach to data governance is essential for mitigating risks and ensuring that sensitive information remains secure. Banks must establish clear, principle-based frameworks that guide the collection, storage, and usage of data. In a fast-paced world where decisions are often based on real-time insights, a lack of governance can expose banks to significant compliance issues, privacy breaches, and operational inefficiencies.
By putting in place a solid governance strategy, midsize banks can ensure that all data used in decision-making processes is accurate, secure, and aligned with regulatory standards. This, in turn, reduces the risk of costly mistakes and ensures that banks can confidently move forward with data-driven initiatives.
2. Platform Risk Management for Secure Partnerships
As banks increasingly rely on third-party platforms and data partnerships, effective platform risk management becomes crucial. In today’s interconnected ecosystem, banks need to be vigilant about who they engage with and how they manage those relationships. A comprehensive risk management approach involves a real-time, contextual view of all partnerships and integrations, ensuring that each platform complies with internal security standards and regulatory requirements.
Effective platform risk management not only reduces exposure to financial and operational risks but also enables banks to gain deeper insights into their clients. By securing these partnerships, banks can enhance their data analytics capabilities and drive more informed decision-making, ultimately benefiting from richer insights while maintaining the trust and security their clients expect.
Leveraging Data and AI for Growth in Midsize Banks
Data analytics has become essential for midsize banks seeking to overcome growth challenges and enhance competitiveness. By utilizing insights from both internal and external data, banks can refine decision-making, personalize services, and better engage with customers.
- Data-driven strategies help banks improve management decisions and elevate customer experiences, particularly in areas like loan underwriting, targeted marketing, and customer service personalization.
- To fully leverage data, banks must invest in upskilling their workforce. A tech-savvy team is crucial to effectively utilizing data and analytics tools to compete with fintechs and larger institutions.
- As ESG regulations grow, data analytics helps banks meet compliance requirements, providing a unified data source for better risk management and regulatory reporting.
AI: The Next Step in Data-Driven Growth
AI is increasingly a priority for midsize banks, with 93.7% of respondents focusing on using AI for fraud detection, marketing, and predictive analytics. As AI adoption grows, its potential to transform operations and customer experiences will continue to expand.
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