The Data Modernization Imperative for Financial Services 

The financial services industry relies on a high volume of constantly moving data. To remain competitive, financial services firms must evolve legacy approaches to data storage, management, access, and analysis.

In-person banking is being phased out and replaced by digital banking options that offer the flexibility, convenience, and immediacy customers demand. Financial services businesses that embrace digital transformation and modernize their systems will be far better equipped to adapt to emerging challenges and meet shifting customer expectations.

Data directly drives outcomes across business functions, enabling personalization, more accurate forecasting, advanced fraud detection, regulatory compliance assurance, accelerated new feature development and overall performance enhancement.

Recognizing the growing need for data modernization, financial services firms are adopting cutting-edge tools and technology designed to extract greater value from their data. These tools include data integration platforms, hybrid or multi-cloud data management solutions, flexible architectures, real-time data analysis technologies powered by AI and much more.

Modern data strategies are driving rapid transformation within the industry. An Enterprise Strategy Group (ESG) Survey, co-sponsored by StreamSets, aimed to better understand how financial services firms approach data-driven initiatives and incorporate modern tooling, technology, and processes into data and analytics strategies.

ESG surveyed 403 technical and business data professionals at organizations in North America (US and Canada) involved in data and analytics. One hundred thirty-nine of the respondents were financial services professionals. This report outlines key findings from ESG research related to the financial services industry.

The financial services industry has faced enormous and unprecedented challenges over the past two and a half years. Multiple global crises rattled the markets, testing the resilience of financial services (FinServ) organizations. Heading into 2023, the industry will have to navigate a potential recession, ongoing inflation, and increased regulation.

Amid economic uncertainty, it will become even more crucial for FinServ firms to leverage technology and creative strategies to increase efficiency, productivity, and customer satisfaction. Deloitte experts also predict that 2023 will present financial services leaders with opportunities to “define the future” and “move the industry forward.” Data modernization, management, and integration are critical parts of this.

Financial services leaders rely on modern data strategies to support top business objectives:

• Advanced data tools will enable FinServ organizations to improve business decisions and strategy, enabling continuous data and real-time analysis and the ability to pull actionable insights from multiple data sources (on-premises, hybrid, mainframe, cloud) rapidly. 
• Modern data strategies improve the quality of products and services delivered by offering unprecedented visibility into what’s working, what isn’t, and why.
• More than any other industry surveyed, FinServ businesses see data strategies as essential to increasing customer spending. Data modernization helps teams identify sales opportunities and optimize for success.

Because of the industry's highly sensitive nature, financial services organizations are under increased scrutiny from regulators and customers. Mistakes in data approaches can lead to privacy and security issues that compromise customers’ financial assets. At the same time, customer expectations are ever-evolving. Banks and financial services businesses that don’t accelerate digital transformation initiatives through data modernization are likely to see customer attrition and revenue losses.

FinServ firms must work with urgency and sensitivity to overcome data challenges:

• The FinServ industry notably has a more difficult time finding the right data than other industries surveyed. The high volume and continuous nature of transactions drive this, as industry professionals also identified data growth and complexity as core challenges.
• FinServ professionals are concerned about skills gaps and identified that data teams are overwhelmed with requests. As the talent shortage continues, businesses will need to explore technology and tooling that helps to fill those skills gaps and increase data access to relieve pressure on data stakeholders. 
• Maintaining data quality is the greatest challenge facing financial services organizations, which presents serious regulatory and customer experience consequences.

Additionally, in our digital age, customer expectations and needs have shifted dramatically, as has the way business is done. FinServ firms must update their data and analytics approach to meet the shifting conditions, outpace competitors, and navigate economic headwinds.

The business benefits of modernizing data initiatives include increased revenue, cost savings, and customer experience-enhancing feature improvements. Capital One recently modernized its core data platform and transformed itself from a traditional bank to a digital-first organization with a cloud-native infrastructure. As a result, it can now rapidly release features, shorten capacity planning cycles, improve business continuity, and enhance digital experiences 

Concurrent evolution and constant adaptation are key to survival. To evolve data and analytics initiatives, financial services firms will need to identify sustainable solutions to common issues preventing valuable strategies from moving forward:

• The costs associated with data services and tools can be onerous long-term, even with the increased revenue potential they bring. To circumvent this, businesses must seek reusable, scalable, and largely self-service solutions. 
• Strategic selection of technology partners will also help FinServ companies overcome the top obstacles to managing and integrating data within and from complex and distributed environments.

StreamSets has helped financial services organizations around the world overcome significant data challenges and improve operations.

In the case of one Fortune 500 financial services firm, data modernization improved cross-enterprise data visibility, availability, and usability. For just under 100 years, this organization has provided insurance to its community. It now facilitates the financial security of more than 13 million members through a full range of financial products and services, including banking and investment alongside insurance.

To meet the firm’s commitment to provide highly competitive rates to its members, it prioritizes efficiency and lower internal costs. But legacy infrastructure and a decentralized data management model made accessing data difficult and costly. Siloed data was scattered in legacy systems, and each business unit chose and ran its own data integration solution.

The organization had significant vendor and solution redundancy and interoperability challenges. To add to the tool sprawl, many of the IT teams across the company preferred to build their own custom solutions. Unfortunately, this model generated a tangle of fragile custom-coded data pipelines that break easily when confronted with any change (and changes to data structure, semantics, and infrastructure are unending).

The Enterprise Technology Team realized that if they wanted to scale and keep pace with the business, they had to automate data pipeline development and operations, migrate to cloud data platforms, and evolve to a shared service model. Long known for their innovation, they embarked on an ambitious plan to transition their on-premises data platform 100% to the cloud (eventually multi-cloud). They developed a strategy to create a foundational managed pipeline (FMP), a scalable, repeatable, and auditable shared data service for all business units. By adopting the Snowflake Data Cloud on AWS and using StreamSets to migrate data from every part of the business, the team was able to:

• Improve data visibility, quality, and insight accuracy with StreamSets' ability to operate and monitor pipelines in real-time globally. 
• Upgrade data availability and accessibility by consolidating and modernizing all data in one system using best-in-class vendors AWS, Snowflake, and StreamSets. And by eliminating overlap, they decreased costs and significantly improved efficiency. 
• Empower faster data consumption with StreamSets’ automated and programmatic data pipelines that reduced the time to onboard data from business units by 6 months. With StreamSets’ patented data drift solution, these repeatable pipelines repair themselves, ensuring that faster data is quality data too.