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Using Merger of Equals Transactions to Accelerate Digital Transformation Efforts at Regional Banks and Credit Unions

Better data management can amplify the benefits of scale available in merger of equals transactions.

Community banks and credit unions historically relied on close relationships with account holders to differentiate themselves from larger competitors. But innovative technologies have put traditional models under pressure, pushing the entire financial industry to deliver a wider range of services across more channels. In response, community and regional banks are looking to merger of equals transactions to muster the resources to build a best-of-breed tech stack that provides superior account holder experiences – online, in-person, or any way in between.

But these types of discrete technology investments can only take an institution so far. Regional banks and credit unions need a scalable, flexible data architecture to continue to adapt to emerging technologies and evolving customer needs. Better data management can allow organizations to unlock account holder insights, streamline and automate regulatory reporting, and use data to distinguish themselves from their peers, rather than simply trying to keep up. Merged organizations can extend the benefits of a merger of equals by prioritizing scalable, adaptable data management as a central component of their technology migration strategy.

How Mergers of Equals Help Banks and Credit Unions Adapt to Changing Times

Merger of equals transactions offer a clear pathway for community banks and credit unions to achieve economies of scale. Multiple small financial services institutions can continue to capitalize on their name and reputation while enjoying the benefits of a combined administrative and operational structure.

Banks often view this project as a rationalization of their combined assets. By consolidating human resources, operational positions, infrastructure and support, community banking institutions can provide common resources for operations across a combined footprint — saving money on payroll and reducing overhead expenses.

Most Merger of Equals Transactions Lean Heavily into Technology Consolidation

Technology stacks are ripe for consolidation in a merger of equals. Banks and credit unions have added innumerable point solutions in the last twenty years in reaction to changing trends and consumer demands. Customers and members expect to open an account, check balances, pay bills and transfer money in real time on a phone or computer. The growing range of product and service offerings available via mobile apps and online banking creates a more sophisticated and complicated support environment. Integrating these solutions and maintaining the systems that connect them can strain IT resources at banks and credit unions.

Meanwhile, digital tools that automate or simplify administrative operations have sped up processes such as collecting signatures, notarizing documents and approving credit. These advancements don’t come without a cost — with each tool that reaches across systems, it becomes more challenging for banks to integrate siloed technologies in use. Integration issues are more pronounced as tools like payment technologies connect various banking systems with disparate merchant point-of-sale systems.

The result has been greater convenience for account holders at the cost of increased complexity in the tech stack. As larger financial services institutions bring more convenience to account holders through digital services, smaller organizations risk losing their traditional edge if they can’t follow suit. But simply adopting new tools in response to customer needs is a recipe for disaster. Banks and credit unions must be proactive about data management and data strategy to avoid having an unruly and unworkable collection of technologies down the road.

To serve account holders efficiently and effectively, data leaders need instant access to authoritative, institution-wide data to deliver quality outcomes. Simply put, bad data leads to bad decisions, and slow data access bogs down processes and degrades the customer experience. The right data strategy gives banks and credit unions a foundation for a better-optimized tech stack today as well as a platform for developing new tools and services to stay ahead of customer needs.

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Maximize ROI by Including Data Management in Merger of Equals Technology Consolidation Plans

A merger of equals offers a uniquely advantageous opportunity to develop a modern data strategy. On day one after a merger, the combined entity has as many systems to choose from as there are banks in the transaction. They also have at their disposal one of the largest data and IT staffs they are likely ever to see, since consolidation and attrition will thin the workforce over time.

Typically, merged organizations lean on combined IT staff to choose existing systems that will integrate smoothly and produce the most cost-effective migration path. This approach is short-sighted. It is ultimately more efficient to take a hard look at the way existing systems deal with data and use that information to identify a data management solution that supports data as a strategic asset.

Overcoming Key Challenges Facing Banks and Credit Unions in a Merger of Equals

The biggest challenge faced by most regional banks and credit unions is siloed operations that make it impossible to scale data strategy. Banks and credit unions tend to rely on the limited reporting and analytics available from the native reporting tools associated with their current platforms. But today’s digital tools provide a whole new set of customer touchpoints that can be mined for actionable data — if banks can tie that information back to performance or attrition metrics. For example, transcripts of conversations between customers and representatives across email, voice and chat channels could provide valuable operational insights to business lines and C-Suite leaders.

A unified data strategy that prioritizes use cases and quick wins with measurable ROI achieves similar outcomes at similar resource intensity over the short term, while reducing the resource requirements for future innovation efforts.

Some banks and credit unions have resisted addressing data management due to the tech resources required to migrate to or adopt new platforms in the first place. This objection may be myopic, however. A unified data strategy that prioritizes use cases and quick wins with measurable ROI achieves similar outcomes at similar resource intensity over the short term, while reducing the resource requirements for future innovation efforts.

Banks and credit unions can address these challenges effectively with a data architecture that provides access to trusted, secure data. That type of modern data stack rests on two key components: 

  • A trusted data lake or data warehouse capable of ingesting both structured and unstructured data. Routing all data to a common repository makes it possible for all systems to draw from a single, constantly updated source of truth. 
  • A scalable and flexible integration layer that provides data to a bank’s systems in the form they can use. The integration layer supports the addition of new technologies as well as enhanced reporting and analytics capabilities, including those drawn from AI-driven insights. 

Targeting Use Cases for Immediate ROI

With the right planning, banks and credit unions can begin to reap the benefits of their new data management strategy almost immediately. A modern data stack can connect information across systems to generate deeper insights about critical factors in an institution’s success, including:

Existing and Potential Account Holders

Many banks and credit unions might be surprised to find out how little they know about account holders until they create a 360-degree record of relationships. Understanding account holder attributes and relationships across the bank can help tailor offerings to existing customers and target market segments that the bank already serves exceptionally well.

Products and Services

Some banking business units, such as wealth management or insurance subsidiaries, don’t interact with core systems at all. With a full view of products and services already in use by account holders across the bank, previously isolated business line users can identify cross-selling opportunities and shape strategic priorities about new offerings that target account holder pain points.

 

 

People and Processes

Better data management provides visibility across siloed systems, making operations more efficient. For example, targeting support and outreach to account holders who truly need it can save representatives’ time. Identifying automation opportunities can reduce administrative burden and eliminate bottlenecks, keeping staff focused on higher-value tasks.

Operational Efficiency & Regulatory Posture

With a consolidated data warehouse, merged organizations can streamline regulatory reporting and enhance cybersecurity data management. In both cases, automation tools can help save time and money, and reduce human error introduced into manual processes. Improved visibility into data lineage across the data ecosystem makes it easier to compile trusted data when regulators come knocking, and cloud-native data security tools help keep sensitive data secure throughout the data lifecycle with robust observability and threshold monitoring.

With enhanced data insights and stronger data competencies, banks can drive revenue and innovation opportunities on top of any net cost savings achieved by combining administrative functions.

Laying the Groundwork for a Merger of Equals Data Estate Modernization

Strategic planning for a merger of equals requires a tech evaluation and due diligence process to decide which solutions or pieces of technology will live or die between organizations. That process involves four core steps that drive the development of a larger technology evaluation and optimization strategy:

  • Inventory the data sources available for all existing products and services. This step should include a review and evaluation of each system’s reporting capabilities in the context of job function requirements and regulatory needs.
  • Map the ways each source system gets access to data. This process should inventory all the ways data can be accessed beyond native reporting, including scheduled and ad-hoc data extractions or data dumps managed through automated systems, API access to batch reports and/or individual records, proprietary data marts and cloud data sharing. This mapping process should be a priority, since consistent data access will be at the core of any comprehensive data strategy.
  • Inventory all integrations that exist between systems. Keep an eye out for systems that could be enhanced or improved via a high-quality, well-governed data layer leveraging a single version of truth as opposed to point-to-point solutions.
  • Inventory the “shadow systems” that maintain data for siloed or legacy solutions. These workarounds are typically ripe for consolidation and optimization. They include internal intranet ticketing systems, database marketing applications that help manage customer relationships and make profitability calculations, marketing automation and email platforms that store information on customer or prospect behaviors and preferences, digital banking platforms with siloed customer preference settings, and microservices that maintain customer-generated information.

With these findings in hand, banks and credit unions can identify platforms that will support a more holistic data architecture. In some cases, existing systems may already be capable of accessing and tapping into a more efficient data management structure when it becomes available. In other cases, banks and credit unions will find that a better data foundation makes it possible to move to a more flexible and efficient solution than the one they are currently using.

These findings also provide the information necessary for potential partners to develop a roadmap and offer project support. Consultants and data vendors can be a valuable resource at this stage to help banks understand what they could do with the right tools and data structures in place.

When banks and credit unions have engaged with partners to leverage this extended evaluation process to create a comprehensive road map and project plan, they can identify training and support opportunities to engage their IT staff efficiently and effectively. This preparation helps the IT team transition from their existing work to higher-value proactive planning. Such higher-level work builds on the knowledge they already have about how the institution’s existing products and services obtain access to the institution’s data sources, and orients them to optimized data processes that leverage an appropriate well-governed data repository.

For many banking institutions, this process results in a data-oriented culture better able to leverage existing information to drive innovation, automation and efficiency across the organization. See how Camden National Bank transformed their data culture here.

By building stronger data skills among IT personnel, banks and credit unions innovate more nimbly and bring new solutions to market more quickly and at lower risk.

Conclusion – Data Management Strategy is Essential in a Merger of Equals

A merger of equals can create more than economies of scale – it can lay the groundwork for a proactive data strategy that scales with the new entity. If banks and credit unions take the extra time and effort to create a unified data management structure, they will achieve even greater benefits — including the ability to replicate the broad offerings of larger competitors while strengthening their traditional advantages of personalized customer service and strong account holder loyalty.

Done right, data management integration provides a platform for innovation and growth that relies on a robust, authoritative data repository rather than a brittle patchwork of systems. A modern data estate provides a scalable foundation for testing and integrating new technologies as they evolve. It also enhances the bank’s ability to use the voluminous and growing amount of data it collects in increasingly sophisticated, strategic ways.

By building stronger data skills among IT personnel, banks and credit unions innovate more nimbly and bring new solutions to market more quickly and at lower risk. Ultimately, this process creates a more agile institution that is capable of identifying and fulfilling account holder needs efficiently and effectively across its entire footprint — setting the stage for merged organizations to get ahead of the competition, rather than just catching up.

If you are a data leader taking part in a Merger of Equals, we can help. During a complimentary 90-minute consultation, we can work with you to assess your technology assets and liabilities, and chart the best path forward.

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