The financial services industry appears to be at something of an impasse between the urgency of their data modernization needs and the challenge of migrating to a modern data stack.
Fortunately for data leaders in the space, this clash between critical need and uncertainty about how to proceed coincides neatly with major disruptions in the data migration landscape, catalyzed in part by emerging AI capabilities.
In this blog, we will highlight how AI-accelerated data migration can help financial services and insurance companies slash time to value on their Snowflake AI Data Cloud investments while laying a scalable, quality-controlled foundation for further innovation, including powerful AI use cases and data monetization efforts.
Financial Services Data Leaders Understand They Need to Modernize, But the Challenge Persists
According to findings from Hakkoda’s State of Data report, financial services and insurance organizations continue to struggle with legacy tech stacks, with only 30% of Financial Services and Insurance (FSI) organizations reporting that they have managed to modernize their data stack and centralize operations on a primary cloud platform.
Despite this latency in their data maturity journeys, financial services leaders are also keenly interested in monetizing their data and leveraging the power of recent AI capabilities. Indeed, a whopping 97% of organizations in the space indicate that they believe generative AI will be important to their success in the next three years. The scaffolding of a modern tech stack will play a critical role in determining the winners of this AI rat race, and leaders in the industry understand its critical importance.
This urgency, however, has yet to catalyze significant industry change. In fact, only a meager 8% of FSI data leaders report that their existing data stores and pathways are “extremely efficient and scalable” as of this year. 37% of respondents in the industry, meanwhile, specifically indicated that modernizing legacy data systems poses a major challenge for their enterprise.

Why A Modern Data Platform like Snowflake is Essential for AI Integration and Data Monetization
For financial services and insurance institutions, the need to manage large volumes of data while adhering to stringent regulatory standards translates into the need for a scalable data platform with both real-time processing power and reliable security capabilities—three requirements that the Snowflake AI Data Cloud is well-equipped to meet.
Snowflake is also uniquely situated to help organizations break down data silos between their existing systems and departments, giving stakeholders a unified source of truth spanning the entire business. By unifying their data ecosystems, financial services institutions are able to quickly and accurately extract insights and react to shifting markets with greater agility. The array of data quality and governance capabilities that Snowflake boasts, meanwhile, make it an ideal choice for laying the foundations of AI success.
As financial services and insurance enterprises work to escape the high maintenance costs associated with outmoded and on-premise systems, Snowflake’s consumption-based pricing model also translates into direct and immediate savings. For some companies, this amounts to a cost reduction of up to 60% when they sunset their legacy platforms.
Finally, Snowflake’s support for data monetization through its Native App framework opens up new revenue streams for financial services. Firms can securely share and exchange data with partners and third parties, creating innovative products and services that cater to the evolving needs of their customers. This enables organizations to transform their data into a strategic asset, driving business growth and innovation.
How Hakkōda’s AI-Accelerated Migration Approach Shortens Migration Timelines and Improves ROI for Financial Services Institutions
Traditional data migration strategies can be cumbersome and inefficient, often involving merely transferring existing data to the cloud without addressing data quality problems or optimizing the end state environment.
Hakkoda’s AI-accelerated data migration approach has been engineered as a direct response to the failures of such approaches, enabling financial services organizations to migrate data more efficiently and intelligently into the cloud.
Armed with AI copilots that automate some of the most cumbersome aspects of data migration, coupled with deep industry expertise that takes into account the myriad challenges and objectives unique to the financial services space, Hakkoda’s refactored migration approach is built with speed, security, and data quality in mind.
Hakkoda’s AI copilots are strategically deployed to push through bottlenecks in the migration process and significantly reduce migration timelines. This acceleration allows businesses to sunset their legacy systems and start realizing returns on their data technology investments in a fraction of the time taken by traditional methods—which adds up quickly, considering an estimated cost reduction of 60% seen by some enterprises.
But Hakkoda’s refactored migration approach isn’t just about getting there faster. By automating manual processes with AI copilots, this methodology eliminates the considerable risk of human error that accompanies a manual approach. This provides financial institutions with cleaner and more reliable data, all while reducing service disruptions and ensuring a smoother transition to the cloud.
As a result, organizations can focus on leveraging their new data platform for business innovation rather than getting bogged down by migration challenges.

Modernizing Your Data Stack with Snowflake and Hakkōda
At a glance, financial services and insurance businesses appear to be under attack from both sides.
On the one hand, the urgent need to migrate to a modern data stack continues to grow more dire by the day as regulations continue to tighten and their competitors widen the data maturity gap by introducing innovative AI use cases into their daily operations.
On the other hand, the longer these companies wait to modernize, the less they can afford the lengthy disruptions and drawn-out implementation timelines that such migrations entail.
But financial services and insurance data leaders don’t have to panic—yet. The necessity of a modern data platform may not go away any time soon, but that doesn’t mean they have to keep relying on the same flawed migration approaches. And they don’t need to take on the complexities and risk of migrating alone, either.
For businesses still struggling to get their migration off the ground, collaboration with a trusted data partner that combines a deep understanding of industry pain points with equally deep technical and AI expertise presents a new path forward. And this path doesn’t stop at slashed timelines and stronger ROI on a one-time engagement. It also expands the art of the possible, opening new revenue streams and putting down roots that will nourish innovation to come.
Ready to make the leap to the cloud and see stronger returns on your Snowflake investments, faster? Talk to one of our experts today.