Redefining Data Sharing for Financial Services

As business continues to shift to increasingly digital environments, the aggregation and sharing of financial data is predicted to have a staggering impact on the global economic future. According to research by McKinsey, “economies that embrace data sharing for finance could see GDP gains of between 1 and 5 percent by 2030.” Ensuring that this kind of data is safely shareable and accessible to all who can benefit from it is paramount.

The issue with data sharing, however, is how it has come to be defined. We often think of data sharing as taking a snapshot of the information and passing it along to someone else. Whether this be internal, between organizations, or with customers, sharing a static image of data is no longer a functional approach for financial organizations. Data itself is by no means static, so a shared view of it should not be either. Sharing idle data limits its versatility, hindering the range of purposes for which it can be leveraged.

Beyond the evident limitations of sharing idle data, financial services (FS) organizations are witnessing a sea change in how the financial industry and its customers are thinking about data collection and use. A general shift towards more open data sharing is taking root, and the FS industry is beginning to adopt practices that make data both more accessible and widely usable for various applications.

How does this shift uproot our prior understanding of data sharing, and where is it poised to go next?

Why is the Current View of Data Sharing Outdated?

The current industry-wide view of data sharing is, for the most part, hung up on an outdated conceptualization. As hinted at above, much of what is discussed as “data sharing” is used to describe the capturing and conveying of data at a moment in time. A customer might request that an investment firm update them on the current state of their assets, and the firm can respond with a fixed view of their funds at the time of the request.

The problem with this idea is twofold. The first issue is the stagnant nature of the data being “shared” between parties in the scenario. Financial information can be extremely dynamic and fluid, adjusting moment-to-moment based on the ebb and flow of the market. Receiving a static view of this data is like going to see a movie and being handed a single frame of film. You only gain an understanding of how the data is at that exact moment, not how it will continue to develop, which limits the insights you’re able to derive from it.

Individuals have come to expect control over their data as collection practices evolve, and in some jurisdictions this has even been enshrined into law. Due to this changing perspective, the traditional view of data sharing can also easily lead to customer discontent. When a bank or fintech service takes that data and offers it back to the consumer under a different label, it can come off as patronizing. No one wants their data to be seemingly relinquished back to them, they want to be able to access it themselves in order to derive their own insights.

Understanding that the current view is limited by these flaws, how should the financial services industry adjust its concept of data sharing to serve modern use cases?

Redefining Data Sharing for Financial Services

Redefining the concept of financial data sharing begins with a simple idea – self-service accessibility.

The idea of sharing needs to shift from the current archaic model to an efficient and accessible one. Rather than simply exchanging a snapshot of time-bound data, financial services should look toward a solution that allows stakeholder access at any point in time. This solves the problem of static data sharing by allowing users – internal, external, or customer – to access the most current version of their data assets at will.

Still, this accessible repository of fresh data should not be entirely open to anyone. Rather, access needs to be controlled appropriately so that different users can carry out distinctly different operations. Think about a bank that decides to migrate its financial data to a major cloud provider like Snowflake or Databricks. Naturally, the bank would want this data to be accessible for analytics stakeholders to analyze and share it as necessary. However, a customer’s checking account information should not be accessible to the marketing department or other customers.

This unified data ecosystem needs effective data access controls in place to allow information to be used for different purposes without unnecessary risk. In doing this, the ecosystem could become a resource for safely and efficiently sharing live financial data across internal departments, between businesses, and with customers – as long as they have the right to see it.

The Changing Standard for Financial Data Sharing

The shift away from exchanging fixed data and towards an open mutual resource is already altering the ways in which FS organizations operate. Data ecosystems are evolving, standards are shifting, and new users are requiring new insights. Some examples of this include:

Exchanging Data to Inform Data Ecosystems

Shared data can inform the construction of more self-sufficient FS data ecosystems. Many organizations have traditionally needed to rely on a patchwork of vendors and tools to effectively manage and analyze their data. When data is regularly and securely made available to the public through a shared resource, this patchwork reliance can effectively be eliminated. Organizations will have the capability to access and assess data on their own.

This self-reliant shift helps banks create a cross-entity view of data, and facilitates tasks like monitoring for fraudulent activity. If George, with a history of bank fraud, tries to open an account at Bank ABC, the data proving his fraudulent activity would be of great importance. If data about George’s fraudulent activity were available, showcasing both prior credit history and documented fraud at Bank XYZ, Bank ABC can make an informed decision about his application. This fraud assessment does not require external analysis when Bank ABC can readily access the data themselves.

What’s essential, though, is that Bank ABC is not receiving sensitive data that they should not have access to. This is where determining the proper access permissions is key. With the right masking measures in place, publicly accessible data could be accessed responsibly and used to make essential decisions in a timely manner. With so much shared information at their disposal, FS organizations can construct a vigorous, self-reliant data ecosystem rather than relying on third party entities.

Combining Data to Create Industry Best Practices

By breaking down silos both inside and outside of company data ecosystems, FS groups can inform a system of best practices that benefit the industry at large. Data can be shared at large in order to provide heightened context for specific pursuits. These guidelines can also inform regulatory adherence and compliance efforts, as well as general industry standards.

These standards are evident through frameworks like the European Central Bank’s Banks’ Integrated Reporting Dictionary (BIRD) and the Financial Information eXchange (FIX).The BIRD database was created with the intention of providing a standardized collection of relevant financial regulations to make regulatory reporting easier for all banks. This shared resource acts as a go-to for up-to-date regulatory financial information, and can be accessed freely as a “public good.” Similarly, the FIX is a standardized protocol for the real-time, international electronic exchange of securities information. Acting as an industry principle and informed by the most current data, each of these frameworks demonstrate the value of commonly defined and shared resources for financial services organizations.

Once again, potent and scalable access control measures are required in order to maintain the integrity of sensitive data in this scenario. By mitigating risk to sensitive data, FS firms can better their industry’s best practices while maintaining safety and compliance.

Ensuring Customer Success Through Shared Data

Customer clarity is a crucial factor in any business relationship. This is especially true in the financial realm, where banks’ transparency helps increase customers’ confidence that institutions are making the right decisions with their money. Beyond this, customers seek assurance that the financial insights they are offered are sound enough to inform personal investment decisions. Delivering on these needs requires balancing data privacy and utility.

Providing customers with access to the same repository of innovative data – while ensuring that this access is properly governed – will be the most effective way to facilitate these user insights. We’re already seeing movement towards commonly shared data through the concept of Open Banking, an ecosystem taking root in places like the U.K. that allows customers and FS institutions to securely share their financial data in order to gain tailored insights and services from third parties. This kind of model gives customers increased autonomy over their financial pursuits, all while maintaining their privacy.

This form of open, secure sharing allows both FS firms and customers to find increased success and satisfaction. Putting more power over data-informed personal financial decisions in the hands of the customer is much more enticing than simply repackaging customer data and sending it right back in an idle bundle.

Achieving Redefined Financial Data Sharing

Enabling accessible repositories of data that allow access for different stakeholder use cases will elevate FS institutions to a new level of shared success. By employing tools with the capacity to discover, secure, and monitor data, financial services institutions can engage in this form of common resource sharing in a safe and effective manner.

The Immuta Data Security Platform combines these capabilities into a simple functional tool, enabling an array of financial services and fintech customers to share data while keeping it protected. With automated data access controls, fine-grained auditing and reporting, and dynamic data masking capabilities, Immuta gives financial institutions the confidence to share data and unlock new opportunities while avoiding putting customers at risk and violating data regulations. Using Immuta, FS customers have seen results such as:

  • Increasing data science productivity by 100%
  • Accelerating data access by 100x and optimizing marketing spend
  • Saving $50 million in spend by automating 95% of data access requests

To learn more about protecting and leveraging financial data, read The Ultimate Guide to Data Security for Financial Services. If you want to experience Immuta’s policy creation skills firsthand, try our self-guided walkthrough demo.

The Ultimate Guide to Data Security for Financial Services

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