Financial Services State of Data Report



Financial services and insurance (FSI) data leaders paint a complex and challenging picture of their industry today. 

On the one hand, FSI businesses report higher returns on data investments and greater organizational data literacy than any other industry. When it comes to highly specific and scope-limited data capabilities, they surge past their peers, paving the way for interesting new data applications. 

But behind these rosy images of FSI organizations as data literate pioneers, their employees report perpetually accumulating legacy technology debt and an urgent need to modernize.

By every measure of critical modern data architecture, financial services and insurance organizations lag behind their industry peers, and while they’re on top of the heap in a few areas for now, they won’t stay there without making rapid adjustments to their data strategies.

A survey of 500 Director to CEO level data leaders, 145 of those hailing from large financial services and insurance organizations, reveals the top challenges, priorities, and opportunities for the FSI industry through 2027.

Executive Summary

FSI is getting more return on their data investments than other industries–for now.

FSI has prioritized short-term data gains, resulting in higher immediate data tech ROI (136%) than other industries (126% average). This boon is likely to be short-lived, however, as only a small minority of FSI organizations (30%) have modernized their data stack and centralized on a primary cloud data platform. FSI data leaders know there’s a lot to gain by modernizing, however, and 74% of all orgs intend to centralize in the cloud in 2024.

For FSI data leaders, the path to modernization is fraught.

Unfortunately, FSI data stacks lag behind other industries when it comes to modernization tools that make sustainable, long-term success possible. Their data stacks are reportedly less scalable and efficient than other organizations, with only 8% of FSI orgs reporting their data stores and pathways are “extremely efficient and scalable.” They are less likely to have centralized their data on a primary cloud platform than other industries and are less likely to be using cloud data stores, warehouses, and data lakes in general.

FSI has niche applications and big dreams for leveraging GenAI.

FSI orgs are more likely to be using GenAI for Documentation and Metadata Generation than orgs in other industries. On the whole, FSI is emphatic about the disruption GenAI will pose for their industry, with 97% of FSI orgs believing that GenAI will be “moderately,” “very,” or “extremely” important to their success within the next three years. They also indicate they’re ready for the AI revolution, with 81% of FSI orgs reporting that they were “very” or “extremely” confident that their in-house data teams could build the GenAI capabilities they need.

FSI organizations lag behind in key GenAI use cases like governance, compliance, and AI copilots.

FSI orgs were significantly less likely to report that they had defined GenAI use cases that they are ready to implement (26%). FSI orgs were also less likely to be using GenAI tools for data governance and compliance (43%) or AI copilots (31%). FSI leaders are eager to adopt Gen AI, but they lack a “big picture” vision and the data infrastructure required to implement innovative new AI tools. The positive flip side of this? FSI orgs that move quickly and think bigger have a chance to capture big gains with GenAI  in an industry that’s struggling to innovate. 

FSI orgs recognize the need to monetize their data imminently.

Only 22% of FSI organizations monetized their data in 2023, lagging behind several other data-driven industries. But 93% of FSI orgs plan to monetize their data in the next two years in a trend that was largely consistent across industries. Yet FSI orgs were among the most likely to cite data monetization as a “major challenge” for their organization at 38%, trailing only Healthcare in this metric.

External support will be a key factor in overcoming inefficient data stacks.

FSI orgs were among the least likely to report high levels of confidence in the scalability and efficiency of their data systems and processes, and 70% of FSI orgs have yet to centralize their data on a primary cloud platform. Despite these inefficiencies, FSI orgs are outsourcing just 53% of their data management. Looking ahead to 2024 and beyond, FSI orgs know they’ll need external support to modernize their data stack and tap into the revenue potentials of data monetization, with 74% of these orgs reporting they will need a “moderate” to “large” amount of outside help to modernize their data stack this year.

Tracking the Data Journey From Chaos to Innovation

Hakkoda uses the Data Innovation Journey model to assess businesses across 5 transformational capabilities and 4 stages of maturity:
Chaos, Order, Insight, and Innovation.

A Chaos Organization is still at the beginning of its data journey and has yet to identify and harness the strategies, tools, and services that will optimize its data stack; meanwhile, an Innovation Organization is well into its data journey and has moved past centralizing and standardizing its data to leverage advanced capabilities like AI automation and data monetization.

The Data Innovation Journey

Data Apps & Collaboration
Machine Learning
Manually moving data
Data science experiments
QA & documentation issues
Endless reports
Multiple data warehouses
Portals of reports
ML models in production
Standardised tooling
Self services
Centralized data
Leveraging 2nd party data
Automated data prep
Metadata driven processing
Quality data to users
Secure embedded apps
MLOps at scale
Automated pipelines
Rich data services
Multi-model structure

FSI is Prioritizing Short-Terms Payouts while Falling Behind the Modernization Curve

Financial services and insurance organizations are good at making money – you might even say it’s their speciality. So it’s no surprise that when asked to report the return on investment (ROI) achieved from spending on data technology in 2023, financial services and insurance leaders indicated strong returns, beating the cross industry average of 126% ROI with a hearty 136%.

But while their outcomes exceeded every other industry surveyed, the larger picture financial services and insurance leaders painted for their organization was far less rosy, with data leaders pointing to looming gaps in data infrastructure poised to grind future innovation to a shuddering halt.

FSI Leads the Pack in ROI from Data Investments

Financial services and insurance (FSI) organizations are often heralded as early adopters, and when it comes to technology capabilities, this holds true in a few arenas. FSI companies are exceptionally fast to add new data sources to their central data platform, reporting that it takes only 7 days compared to an industry average of 12.


FSI organizations are also ahead of industry peers when it comes to niche GenAI capability adoption.

51% of FSI leaders report that their company is using Generative AI for documentation and metadata descriptions. In this arena, FSI is tied with education and government organizations. But while FSI organizations led the pack in this specific use case, they lagged behind in broader applications of AI tools, falling short of even the cross-industry average in their utilization of AI for data governance, data cleaning, cataloguing, schema matching, and AI copilots. 


A broader look at the overall data maturity of financial services organization renders this apparent shortfall unsurprising. Because while FSI has invested in niche technological capabilities that deliver bursts of ROI in the short term, their total organizational infrastructure grows more and more obsolescent by the year. 


Financial Services & Insurance Organizations Are In Urgent Need of Modern Data Architecture


Only 30% of financial services and insurance organizations have centralized their data on a cloud platform. Compared across industries, FSI companies are in a dead heat for last place with retail and entertainment organizations when it comes to current use of a cloud data store or warehouse. FSI is also less likely to use data lakes, with only 37% of FSI leaders reporting that their business had one in current use. Even with the stipulation of “centralized” use of the cloud removed, FSI businesses report a troubling lack of adoption when it comes to the foundational data architecture that allows companies to modernize, innovate, and ultimately, keep up.

Some of financial services and insurance leaders’ troubles may link back to a lack of organizational alignment around challenges and priorities. Respondents’ self-reported obstacles revealed stark discrepancies between what Director level to VP and C-level executives saw for the organization’s roadmap.

Among data leaders who held Director to Senior Director level titles at FSI businesses, 58% saw building and maintaining advanced analytics capabilities as a “major” challenge for their operations in 2024. At the VP or General Manager level of those same organizations, only 32% agreed. There was only one other concern that ranked as highly for Director level data leaders: ensuring data quality and governance. Given that AI was at the top of the C-levels’ list of priorities, the climb for FSI organizations in 2024 is a steep one. 



FSI is Using GenAI for Documentation & Metadata Generation, But They Lag Behind in Key Applications

Artificial intelligence is poised to disrupt the financial services and insurance industry in a significant way in the next three years, with 97% of financial services organizations indicating that they believe GenAI will be “moderately,” “very,” or “extremely” important to their success within that time frame. 


FSI organizations are also ahead of industry peers when it comes to niche GenAI capability adoption.

81% of these same organizations, meanwhile, report that they are “very” or “extremely” confident that their data teams can build the AI capabilities they need and that they have the infrastructure in place to support AI workloads. 84% believe their teams also have the AI skills and expertise for successful implementation. 


FSI Has Niche Use Cases for AI, but Falls Behind in Governance, Compliance, and Copilot Applications

Interestingly, while the majority of FSI organizations were highly confident in their ability to implement AI, only 26% of these organizations actually reported that they had defined GenAI use cases that were ready for implementation. 

Where FSI organizations have defined use cases for GenAI, they  are significantly more likely to be leveraging it for Documentation and Metadata Generation than orgs in other industries. They are, conversely, less likely to be using GenAI tools for data governance and compliance (43%) and AI copilots (31%).

“Financial services organizations understand the value of their data but have commoditized their technologies and systems to extract its value. This means every identified data transformation project has a business case associated with it and the data team gets buy-in from the start. As a result, it’s possible to deliver truly exceptional ROI from their projects. On the other hand, it also means that financial services organizations are deprioritizing some of the most simple but essential modernization projects because they’re more difficult to show ROI. That means that their short-term metrics and success rates look exceptional, but their long-term projections become increasingly unstable as they continue to accrue tech debt.”

-  Anand Pandya, Global Head of Financial Services at Hakkoda

FSI Needs to Address Data Quality & Interoperability to Get Returns on their AI Investments

Organizations in the financial services and insurance space are highly eager to leverage GenAI and confident that they can do it, but there are a number of fundamental data practices they will need to shore up before their AI goals become achievable.

49% of FSI organizations indicate that ensuring data quality and governance is a major operational challenge, and 41% of these orgs indicate difficulty integrating data across multiple silos. Without high quality, interoperable data on which to train their models, major GenAI projects will struggle to deliver strong returns on investment, as the likelihood of misleading or hallucinated outputs increases in relationship to the prevalence of erroneous or incomplete information.

Without a focused vision that brings concrete use cases together with the data infrastructure required for successful AI implementations, FSI organizations are fighting an uphill battle to keep pace with innovators in other key industries. For businesses ready and willing to move fast in cleaning up their data and implementing a pragmatic roadmap to AI success, however, the industry landscape is ripe with opportunity to outperform the competition. 


FSI Plans to Monetize Their Data in the Next Two Years, They're Uncertain How They’ll Get There

FSI organizations lagged behind when it came to data monetization in 2023, with just 22% of FSI orgs monetizing their data.

But FSI orgs know they need to tap into data monetization to continue to get the most out of their data tech investments, with 93% of FSI orgs planning to monetize their data within the next two years—a trend that was consistent across industries.


The question for all data-driven organizations in 2024 is not whether to begin monetizing their data but when and how to do so, and FSI is no exception.

But like any industry, FSI faces unique challenges when it comes to harnessing the potential of their data, with data monetization reported as a “major challenge” by more FSI orgs (38%) than any other industry except Healthcare.

FSI Needs to Address Data Quality and Interoperability to Get Returns on their AI Investments

So what stands in the way of FSI—an industry that thrives on leveraging data to drive revenue in its day-to-day operations—from effectively monetizing their data?

FSI orgs reported less confidence in the efficiency and scalability of their data stack, with just 8% of orgs reporting that they have “extremely” efficient and scalable data processes.  


70% of FSI organizations had yet to centralize their data on a primary cloud platform in 2023—a factor that likely contributed to these orgs’ inefficient and difficult-to-scale data stacks.

For reference, innovation organizations who followed best data practices were 56% more likely to be monetizing their data than the average FSI organization. 

"As FSI organizations move to the cloud to get around the legacy data and technology silos that currently exist, they need to be mindful of adopting a storage and computing platform (a data cloud) that operates seamlessly across the cloud infrastructure providers. As more and more regulations surround AI and Cloud providers, having multi-cloud interoperability and key focuses around the security, governance, and distribution of data are becoming all the more important to the organization's future."

- Christopher J. Napoli, Snowflake Head of Wealth & Asset Management

FSI Orgs Know They Will Need a Great Deal of Outside Help to Achieve Their Data Goals

External support looks to be the key to data modernization and monetization for FSI organizations in 2024.

FSI orgs outsourced just 53% of their data management in 2023 (compared to 63% of Innovation organizations who follow data best practices).

“The truth is that external support is a necessary element of a successful data strategy in 2024. Forward-thinking FSI organizations know they need talent to adopt modern design patterns and new ways of doing things to tap into important revenue streams like monetization, and they simply can’t wait for their internal teams to develop these capabilities on their own while overseeing their organizations daily data needs.”

- Erik Duffield, Hakkoda CEO & Co-founder


FSI organizations are well aware they will need greater external data support in the coming year, with 74% of FSI orgs reporting they will need a “moderate” to “large” amount of outside help in modernizing their data stack in 2024. 

External data support will not just help FSI orgs monetize their data more efficiently—it will help orgs address the symptoms of their inefficiencies, supporting the  necessary transition to a primary cloud platform and building more scalable and efficient data systems.

Conclusion: Financial Services and Insurance Organizations are Ready to Modernize their Data Stack, Implement GenAI, and Tap Into Data Monetization. Their Success Will Depend on the Right Outside Help.

2024 stands to be a big year for data modernization in the financial services and insurance space, with 74% of all organizations in the industry intending to have their data centralized in the cloud by year’s end. 

This means 44% of organizations will be playing catch-up this year, with an additional 26% intending to follow suit in 2025 and beyond. Unfortunately for FSI leaders, their existing data stacks are less scalable and efficient than those found in other industries, which means they will have a lot of ground to cover to achieve their data modernization goals.

A similar pattern emerges with regards to data monetization. A meager 22% of FSI organizations report that they have already begun to monetize their data in 2023, but an overwhelming 93% of organizations plan to monetize in the next two years. 

Even regarding GenAI, where FSI organizations are bullish in their evaluation of their talent and technological infrastructure, major challenges in data quality and interoperability act as blockers to ambitious implementation goals. 

To their credit, FSI data leaders aren’t afraid to admit they’ll need considerable support from managed service providers, systems integrators, or IT consultants if they want to achieve the data goals laid out in front of them. A formidable 74% of FSI orgs reported they will need a “moderate” to “large” amount of outside help modernizing their data stacks, echoing cross-industry data outsourcing trends.

Unfortunately, FSI orgs are currently outsourcing just 53% of their data management, as compared to 63% of organizations that follow best data practices. Given their unique disadvantages in several arenas of data modernization, FSI data leaders will need to lean that much heavier on outside data experts to close the gap. 

The State of Data paints an ambivalent picture of financial services and insurance organizations in relationship to their data infrastructures and goals. On one hand, it can be read as a wakeup call for FSI data leaders to pursue modernization with a renewed sense of urgency as they see themselves trail behind other key industries. On the other hand, the report points to a unique opportunity for organizations ready to take the challenge head on, signaling that there is no time like the present to establish themselves as innovators in the space and reap the lion’s share of the benefits a modern data stack has in store.