The X Factor in personalized financial experiences: Data interoperability

Published: October 15, 2021 by Jean-Claude Meilland, Global Product Director for Decisioning Software

One of the most exciting things about financial services innovation is our growing ability to deliver personalized customer experiences. For example, consider a customer who enters a shopping center during the holiday season. By leveraging decisioning software, lenders can proactively offer that customer more credit—in real-time. The person has the financial ability to get what they need and doesn’t have to experience a rejected transaction based on previous credit availability.

What’s behind such personalized offers? They are powered by the latest data—information that goes far beyond traditional credit ratings and references. For the holiday shopper, that may include geolocalization and behavior data that project a customer’s likelihood of reaching a credit limit while shopping. The information empowers lenders to provide that personalized experience at the exact right time.

But to make that possible, the data must be interoperable across systems, analytical and operational environments, and third-party data providers. Looking ahead, the financial service companies that enable this interoperability will be able to innovate faster, compete better, and scale their personalization to ultimately win more business.

Why interoperability matters

Our most recent Global Decisioning Research Report denotes consumers’ evolving expectations and the increasingly vital role data and analytics play in meeting their needs. Financial service companies must leverage data to understand customer circumstances better, changing risk profiles and emerging credit needs, especially as we move out of the pandemic. Indeed the right data can help lenders support customers across their entire journey.

But utilizing data to improve the customer experience is not as straightforward as it seems. The amount and diversity of the data available are huge. And the data required to power personalized products and experiences are not always readily accessible, well-formed, or high quality. As a result, data integration projects often take longer and cost more than many financial service companies anticipate. Legacy systems add to the complexity and expense.

The evolving open standards for data interoperability are helping alleviate some of these challenges. But companies still need to determine which standards and platforms to use. Selecting the right ones can accelerate innovation and prevent expensive stops, starts, and detours down the road.

Cultivating a healthy ecosystem

The good news is that these challenges are surmountable. The first step is to understand where your organization is in its data interoperability journey. Then you can create a strategy that makes data-based innovation easier, faster, and more cost-effective. For example, consider:

  • Prioritizing industry-leading open standards for interoperability. Requiring CSV and JSON data formats is smart; both are currently ubiquitous across the industry.
  • Using standard APIs to share data. For example, Rest APIs using Swagger provide a description of the API, the data and facilitate the discoverability and use of the API.
  • Exploring API aggregation services and marketplace platforms. These make it easy for developers to add services and for your organization to put them to use.
  • Leveraging low-code data integration tooling. This helps you remove data silos and empower staff to navigate older, traditional data integration methods until they evolve to use open standards.

These actions can make a significant impact on your company’s ability to take advantage of various data sources now, as well as set your organization up for the future.

Data meets decisioning

Selecting the right decisioning software is a crucial way to facilitate the steps noted above. As you consider decisioning solutions, look for products that allow you to publish and consume data using open APIs and simple visual drag and drop approaches.

In addition, evaluate the core data management capabilities of potential solutions, and prioritize those that can natively also support semi-structured data. For instance, applications that allow you to leverage frequently changing data sources ensure that when a source evolves, only the specific areas loading the data are impacted—not the wider solution.

Lastly, as mentioned above, solutions that provide lightweight, low-code middleware allow you to leverage third-party data no matter where you’re at in your interoperability journey. Those new sources of data will inform and enhance your customer’s experience.

Stay in the know with our latest research and insights:

Subscribe to our blog

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Quadrant 2023 SPARK Matrix