Harnessing Modern Data Strategies to Drive Financial Services Success

The Power of Data in Financial Services

Today, data is no longer just a support function—it’s a key driver of business strategy. At Dreamforce 2024, data and AI took center stage, with nearly every keynote emphasizing the critical role of data. In case you missed them, our latest blog dives into the key announcements data included from Dreamforce that financial services need to know.

With an $88 trillion generational wealth transfer and declining interest rates on the horizon, financial institutions face a pivotal opportunity to leverage data for identifying, segmenting, and engaging clients more effectively. However, data often remains siloed within organizations, making it neither unified nor actionable. Our panel emphasized that adopting a data-first approach is critical for navigating regulatory pressures, meeting evolving customer expectations, and staying ahead of rapid technological advancements.

"To stay relevant in five years, you must create a world where your database not only drives everything you do but where the technology around it can truly achieve your goals."

- Cat Davies, CEO, Innovayte

To seize this transformative moment, banks, credit unions, and wealth management firms must act now–establishing a data modernization strategy.

Create a Data Modernization Strategy

The session’s key takeaway was clear: financial institutions must make data strategy a core part of their business plan. By adopting scalable technologies, democratizing data access across teams, and taking a focused, agile approach, firms can unlock the full potential of their data to drive growth and improve customer experience.

How do you build a successful data strategy?

Step 1: Align Data Strategy with Business Value

Engage Executive Leadership with Clear Use Cases

Before investing in new data platforms, it’s crucial to communicate the business value clearly to executive stakeholders. Highlight how modernizing data infrastructure will lead to meaningful business outcomes, beyond just improving backend operations. Focus on specific use cases, like customer segmentation or optimizing marketing campaigns, to show immediate ROI and build a compelling case for investment.

Manvir emphasized the importance of leadership buy-in, stating, “Just like any CRM, data is a significant investment. It’s not just a backend IT concern; it requires full commitment from all stakeholders.”

Step 2: Choose the Right Data Platform for Growth

Select Market/Industry Leading Technologies 

Financial institutions must carefully evaluate cloud platforms (e.g., Databricks, Data Cloud) that can not only handle large volumes of data but also ensure robust security, governance, and scalability. Additionally, it's crucial to unify and curate data from diverse sources, such as CRM systems, transactional systems, and third-party platforms, transforming it into actionable insights using technologies like data lakes or data cloud solutions. 

This naturally leads to a common question many institutions are asking themselves: What is the right technology? The answer lies in a blend of tools that handle both data scale and accessibility.

Databricks
It’s clear that enterprises have an abundance of raw data, but it’s often inaccessible or unusable for meaningful insights. Enterprise Data Platforms (EDP) like Databricks excel at transforming large datasets into standardized and common data models, democratizing data across the organization with superior analytics, machine learning, and AI capabilities. Databricks offers enterprise-scale capabilities with top-tier security and cost efficiency, making it a leading choice for data transformation. However, EDPs are not typically designed for customer engagement.

Salesforce Data Cloud
This is where Salesforce Data Cloud steps in, serving as the optimal platform for customer engagement. With the $88 trillion generational wealth transfer approaching, marketers need tools that can interpret customer data, build segments, and personalize engagement journeys. Salesforce Data Cloud, integrated with Marketing Cloud and Personalization, delivers these capabilities, allowing marketers to adjust strategies in real-time.

Integrating Databricks and Salesforce
Salesforce’s “zero copy” integration with Databricks breaks down data silos, enabling seamless data sharing while cutting costs. This integration empowers data practitioners to utilize Databricks for advanced data analytics, machine learning, and generative AI while marketers and business teams leverage Salesforce capabilities for responsive customer engagement. Together, these platforms help institutions stay agile and meet evolving customer expectations. Once FI’s have made these key platform decisions, FI’s should then craft target state Enterprise Data Reference Architecture artifacts to map data sources and the flow of raw data to transformed, unified, and usable data for key stakeholders and applications. Zennify utilizes a market leading approach for this process to drive effective Financial Services Enterprise Data strategies.

Step 3: Establish a Roadmap for Quick Wins

Start with Agile, Iterative Steps

Instead of attempting a complete overhaul of legacy systems right away, focus on quick wins that deliver immediate business value. For instance, leverage existing data resources to enable customer segmentation and engagement, even while transitioning to a full-scale data platform.

Bell Bank is an excellent example of how quick wins can drive impact. Over the past two years, they’ve used the Salesforce platform to enhance customer experiences through technology. As Abbey Meitin shared, “Salesforce helped us recognize that data is the most critical asset for our business.” Recently, Bell Bank established an enterprise data and reporting team to strengthen their infrastructure, ensuring they provide a consistent experience both in-branch and digitally. By prioritizing data, they’re successfully bridging the gap between traditional markets and growth areas, allowing customers in regions like Fargo to receive the same high-quality service online as they do in person.

Step 4: Ensure Strong Governance and Security

Prioritize Governance and Compliance

While technology is essential, financial institutions must also address significant compliance challenges. Cat and Abbey discussed how their organizations overcame these hurdles by selecting the right technologies and adopting an agile, use-case-driven approach. It's critical that any new data platform adheres to strict governance and security requirements, particularly when handling sensitive financial data. Unified governance is key to maintaining regulatory compliance. Involve your InfoSec teams early and continuously to proactively mitigate risks and ensure robust data protection protocols are in place. While leading data platforms are cloud-based products, Databricks is often the preferred choice, as this solution operates seamlessly within Azure and AWS Cloud environments. With Azure typically being the preferred cloud for most financial institutions and their InfoSec teams.

Step 5: Enable Data-Driven Insights for Business Teams

Democratize and Activate Data

Make data easily accessible to marketing, sales, and other business teams by leveraging platforms that unify customer profiles and enable key actions like segmentation and targeted outreach. Cat Davies described MuleSoft as an "API highway," enabling real-time data integration across systems. With both standard and real-time data inputs, such as pricing, flowing into these systems, the industry is undergoing a transformation in how it operates.

Many institutions already have this data within their organization but lack the ability to fully activate it. Once data is centralized and accessible, teams can unlock its potential to drive growth and improve customer engagement.