Thinking of Acquiring a Neobank? Evaluate How Its Data Is Organized

The financial industry has seen a frenzy of mergers and acquisitions over the past few years that looks different from the type of activity we saw not 10 years ago. What’s the difference?

Today, most of this activity involves neobanks – the fintech companies that provide online banking services, often in partnership with an established bank.

If your organization is considering acquiring one of these newcomers to the financial industry, one of the most important steps to take in advance of talks is to get your own data organized. Here, I’ll explain why data organization is critical to the success of your neobank merger and acquisition.

Pay Attention to Data Governance Framework from Day Zero

You’ll receive data governance information in the onboarding process before any paperwork is signed; don’t ignore the importance of this information in your discovery process. You need to make sure that the data is properly secured and governed first and foremost.

To do this, find out where the company, its data, and its customers are located. Understanding the neobank’s current data governance framework will help you ensure that your data transformation plans will work in accordance with applicable CCPA or GDPR rules.

Make a Data Transformation to Facilitate a Smooth Transformation Process

Once you have a handle on the neobank’s governance requirements…

1. Pull all their data and map it accordingly
2. Identify common attributes. While the attribute names to label the same shared data points will differ, finding common attributes (like a customer’s first and last name) will help you integrate your records.
3. Eliminate duplicate records, so that each entity has a single record associated with it, whether those are individuals or companies.
4. Determine which data warehouse(s) you’ll move toward in this transformation process. This may be yours, theirs, or a new destination altogether.

By creating this high-level roadmap, you’ll be well positioned to clean the data and prepare it for the end-state that will best serve your new organizational goals.

Critical Questions to Answer When Acquiring a Neobank’s Data

In the early stages of discovery, you’ll answer questions like who has access to this data, what is the encryption method, and what are their security protocols? But to merge your data, you’ll need to ask even higher level questions to meet your strategic goals.

1. How is the data stored and what database do they use?

Some companies still use Excel files to store their data, but most neobanks rely on cloud providers. This is important to know because cloud providers typically do their own maintenance, which comes with fees attached.

2. How is their data structured?

Whether a company’s data is structured, unstructured, or semistructured will determine what technology you’ll be able to use and shape what solutions you select to warehouse your combined operations.

It can be difficult to de-silo different types of data that are housed in multiple locations, which is why the data transformation process is so important to map out before any paperwork is signed.

3. How many attributes does their system have (and how many does your system have)?

I hinted at this issue above, but the process of finding common attributes to help you align your customer records is a critical step in this process. Beyond matching up Fname, LName, address, and payment records to eliminate duplicate instances in your new system, you’ll need to determine how to resolve mismatched customer records up front.

For example, if you have one record for my first and last name in both systems at the outset but the two are associated with different cities, which will you give priority to? Ultimately, you’ll need to arrive at having one row per entity, whether you’re dealing with individuals or business users, in order to deliver an excellent customer experience after the merger is complete.

4. How mature is their data?

At Apexon, we often talk about where an organization falls on the automation maturity model, and this is true of a neobank’s data operations as well.

• Level 1: They rely entirely on manual process.
• Level 2: At this stage, the neobank likely uses some form of integrated automation in their data warehousing solution or courtesy of their cloud-provider solutions. At this level, customer data is typically located in one location that serves as a single source of truth. The data is cleaned and governed.
• Level 3: The cleaned and governed data is regularly pulled and analyzed for insights that drive internal decision-making. These insights are likely available to C-level employees in the form of automated dashboards or reports.

The final level of analysis presents an additional consideration, which is often of great interest to executives: how quickly will you be able to integrate the new data you’ve acquired into reports for your C-suite?

If you already produce regular reports that drive executive decision-making, it’s in the best interest of everyone at your company to include an estimate of how long this transformation will take in your plans from the start.

Don’t Overlook the Operational Challenges of the Merger and Acquisition Process

While the executives steering the acquisition of a neobank won’t likely be concerned with the details of how compatible your data warehouses are before they sign the paperwork, it’s important to advocate for a thorough discovery process and ensure you have a plan to clean and integrate their data sooner rather than later.
If you have any questions about how to navigate this process or think your team could use outside support in this process, contact our team of experts.