For more than 25 years, Naranja X has been Argentina’s leading credit card issuer, with its ubiquitous orange cards in the hands of millions of Argentines. But the 37-year-old company’s executives saw the writing on the wall: Customers began to prefer getting all their financial management products and services digitally and securely, from the same vendor.
For Naranja X, getting to this point meant changing its business model to that of a fintech company and using technology to automate the delivery of financial services. The company wanted to expand its ecosystem of online products and services to include transfers, collection offers, loans, insurance, e-commerce, payment services, travel and promotions.
It’s a smart move for well-positioned companies. The global fintech market is expected to grow at a compound annual rate of approximately 25% per year through 2027, according to Market Data Forecast. This growth will be driven by the digitization of financial services, the demand for contactless payments and the potential for Fintech to attract more customers.
But shifting its business model to Fintech required more than the will to do so. Naranja X had to look carefully at its data and figure out how to get more value out of it.
“We had to become a data-driven company, and that meant everyone in the company had to not only have access to the data, but also understand the data,” said Lucia Arando, data governance manager at the company. ‘company.
Naranja X also needed new processes to ensure data security, which involved restricting certain data to the right people for the right purpose. And this data had to be fully controlled and responsible, because the Argentinian Central Bank puts much more requirements imposed on Fintechs than credit card companies.
Data management challenges
The preparation to become a fintech company started about two years before the change itself. Meanwhile, Naranja X has worked to better organize and manage its data.
First, it meant being able to quickly search for any data asset in the enterprise. Naranja X traditionally relied on Excel spreadsheets, using one for each data domain. For example, an Excel file contained only customer data, only one supplier data, etc. While finding data in a specific domain was not difficult, finding specific data in more than one domain was nearly impossible.
The new data management system also had to automatically track any additions, deletions or other changes to existing data; log user activity; and facilitate collaboration around data.
An additional hurdle was the fact that data stewards – the primary owners of data in every field – didn’t really understand why they needed to keep control of their data so closely. “Our data governance is based on stewardship, but because we didn’t have anything tangible, our data stewards couldn’t understand why they should do what we asked them to do,” Arando said. “They didn’t see the value.”
Naranja X needed an automated method to create a comprehensive data catalog, provide secure data access, and provide comprehensive data governance. To save time when evaluating potential products, the Arando team chose to temporarily switch to Microsoft Power BI. The team loaded their existing Excel spreadsheets, each for a different data domain, into Power BI. This allowed users to see all metadata in a large table with a search box and filters.
Although Power BI solved some problems, it was far from the optimal solution. Not only did it only support front-office metadata – the back-office was still entirely manual – but data managers didn’t fully accept it.
It was during this time that the Naranja X data management team learned a valuable lesson. “We had to ask our users what they wanted to have that they didn’t have and what they didn’t like in the current processes,” Arando said.
Implementing the OvalEdge Data Governance Tool
Naranja X’s first step for its transition was to find a way to automate the collection and management of technical metadata – the technical properties of data, including location, credentials, source, schemas and attributes.
Technical metadata tended to become outdated quickly, making it a significant data governance challenge. Relying on data stewards to notify the data governance team when things changed was difficult to enforce and not always reliable, Arando said.
The team decided to standardize on OvalEdge, a data catalog and governance tool that automates the process of locating and displaying technical metadata. It was a good start, but the team also needed a way to automate the collection and access to corporate metadata. OvalEdge could manage enterprise metadata, but only if Naranja X’s data stewards agreed to consistently enter data into the OvalEdge platform.
Given human nature, this was a big ask, but it was big enough for the Data Governance team to come up with a plan. Using Power BI, the team created a game with incentives to add the data to OvalEdge. The game was a Formula 1 racing simulation, where drivers are data stewards and their activity in OvalEdge can earn them points. Every quarter, the company now announces the top three winners, who receive bonuses in their Naranja X app.
These gamification efforts have clearly paid off. Usage is up significantly. Additionally, activity on the company’s Slack channel for data questions and answers has dropped significantly as users become familiar with OvalEdge’s self-service options.
Today, most technical and business metadata is kept in OvalEdge, along with advanced analytics models the company has created, organizational KPIs, queries, and reports. The tool is integrated with the AWS of Naranja X data lake, as well as an on-premises Oracle data warehouse that will eventually be retired (all data will be moved to the data lake). The data governance team has set alarms in the system to trigger data governance actions when a change requires their attention, such as when a user deletes or adds a table.
Internal users can easily search for anything they need. For example, if a user wants to find information related to all active customers, a simple search will find all datasets related to that term. Data analysts and data scientists can also easily access statistical data.
“Having all the data in one place where any data scientist can go to understand key data assets is important, especially since data scientists are hard to retain,” Arando said. “When a new data scientist joins the team, the first thing they want to do now is see what we have in OvalEdge.”
The new system also improved data security, an important requirement for data governance. For example, the organization needed a method to quickly identify the location of sensitive data and ensure that it is secure in terms of darkening. OvalEdge does this by masking strings with an algorithm and then integrating it into Snowflake, the exposure layer, where end users consume data.
Now that many of the data management and governance challenges are under control, the next step is to integrate sources and back-office functions into OvalEdge. Naranja X will also identify and classify all confidential data and integrate transactional data. The goal, Arando said, is to create an end-to-end data lineage.