The demand for advanced data analytics for credit unions and banks continues to grow, driving improvements in personalization, strategic decision-making, efficiency, risk management and competitive advantage.
But with so many options available, how do you choose the right partner?
When Jamie Clisham, vice president of data and analytics at Machias Savings Bank, joined in 2023, she faced the challenge of replacing their outdated platform. She took this opportunity to find a replacement that would also elevate their data analytics capabilities. Here’s her practical advice for selecting a provider, with added insights from the provider’s perspective:
1. Look for Robust Data Integration Capabilities
Seamlessly integrating diverse data sources was critical for Machias Savings Bank. It planned to integrate 12 key systems, including loan origination, online banking, customer relationship management and general ledger systems. Ensuring their provider could handle diverse data sources for a unified operational view of the bank’s information systems was paramount.
Gartner estimates that knowledge workers now use an average of 11 systems, almost double the number they did in 2019. This trend highlights the need for platforms that handle flexible, semi-structured data — Extensible Markup Language (XML), JavaScript Object Notation (JSON) — without limiting operational systems or data types.
2. Empower Data Teams With Flexibility and Customization
Machias prioritized a platform that empowered their data team to build custom analytics solutions without heavy IT reliance. Executives selected a tool with codevelopment capabilities to create tailored branch scorecards and a householding model.
Enabling their employees to self-serve data requests without having to wait on others is helping to foster innovation at a rapid pace. Advanced users can now build custom queries with Structure Query Language (SQL), while other users are equipped with a friendly user interface to ask questions of the bank’s vast data resources in a fraction of the time.
Customizations layered on enterprise analytics help organizations achieve return on investment targets, providing the flexibility to meet unique business needs.
3. Prioritize Scalability and Maintenance Efficiency
Scalability and reduced operational overhead drove Machias’ decision to transition from an on-premises data warehouse to a cloud-based platform. The solution the bank chose offered cost savings and required less internal support. No more surprise phone calls at 2 a.m. when the database server goes down.
This shift also transformed their workforce: Report writers became analysts and system administrators evolved into data stewards, as the provider handled 80% of administrative tasks.
4. Align Data Initiatives With Strategic Goals
Machias aligned its platform selection with strategic priorities like efficiency, measuring initiatives and identifying insights about its most profitable customers and products. It integrated the platform into its legacy modernization strategy to ensure a smooth post-conversion transition with clean, mapped data.
By adopting a platform ahead of their core conversion, the bank mitigated risks associated with simultaneous application changes and unfamiliar reporting.
5. Embrace Emerging Technologies like AI Thoughtfully
Machias factored generative AI into their selection, prioritizing a partner with expertise in emerging tech, data privacy and security. It sought a provider adept with modern database and data visualization tools — such as Snowflake or Tableau — and capable of guiding them through evolving technologies responsibly.
It’s crucial to choose a provider that designs solutions with modernization in mind. Many organizations have struggled with outdated platforms that are now costly to maintain or migrate. Avoid locking into rigid, full-stack solutions that limit flexibility.
6. Invest in a True Partnership, Not Just a Vendor Relationship
Machias valued a provider that aligned with their organizational culture and prioritized partnership. The bank found a partner who truly cares about their successful data journey and will support them the whole way.
By focusing on robust integration, customization, scalability, alignment with goals, thoughtful tech adoption and strong partnerships, Machias Savings Bank turned the platform replacement into an opportunity to transform its analytics strategy.
So, where should financial institutions begin their search for the right data analytics partner? Here are some questions to start with:
Five Key Questions to Ask Potential Data Analytics Providers
1. How well does the platform integrate with my existing systems?
2. What level of customization and flexibility does it offer?
3. Is it scalable and easy to maintain as our needs grow?
4. How does the provider ensure data privacy and security?
5. Do they offer ongoing support and a collaborative partnership?
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