1. What is data asset financing?

At its core, data asset financing is about a company or enterprise identifying data that it owns or has access to, ascribing a value to that data and then monetising that data.

2. How did it come about?

Data is a highly valuable asset. Its global value is already something like $3trn and counting. But companies and advisers are only just starting to scratch the surface of what that means; it often doesn’t show up on companies’ balance sheets. Imagine there’s a way of raising financing off the back of something you didn’t know you had. It’s like finding tens of millions of dollars behind the sofa.

3. How does it relate to asset-backed lending?

It’s very similar. The skills needed to identify the risks around traditional asset-backed lending are very important in data asset financing. Creating bankruptcy remote structures which house the data is an essential part of the structuring.

4. How do you value data assets?

Not all data is the same. There are a lot of factors which go into valuing data. A company might have a lot of data but quite a lot of diligence needs to be done to determine the value of it. Some of the things which we look at are: exclusive use or other unique rights to use the data; comprehensive, consistent accurate data which is up to date, wide permissions to use the data and opt-in elections by data subjects.

5. How are these deals being structured?

Deals can be structured in different ways. But creating a bankruptcy remote vehicle which houses the data and associated rights is going to be important. The monetisation can then take a variety of different forms. We’re more familiar with debt solutions but we’ve also looked at equity structures too. If people are familiar with J Crew and the use of unrestricted subsidiaries in a leveraged financing context, data asset financing can be a powerful tool in that context too.

6. Why is this important now?

The increasing focus on global data and its value is driving this market. AI is a big driver in adding value to data, and breakthroughs in AI technology is also helping drive the thinking in this area. Although this can be used by performing businesses, it also has potential for stressed businesses; so overlay the fact that companies are looking to raise financing now, and there’s great potential in this product.

7. What are some of the benefits and some of the risks?

The benefits are clear. Financing an asset which up until now hasn’t appeared on a balance sheet? Which companies wouldn’t be interested in exploring that? Once the data is identified, its use is universal and can be used for both performing and distressed situations. It can also be a highly valuable tool in M&A valuations.

The main commercial risks are around protecting against the downside. What happens if the company goes bankrupt? What can the financier do with the data to recover its investment? The main legal risks are around structuring and navigating a complex, global network of laws and regulation which is changing quickly. Investors need experienced advisers to help think about those risks. Each situation is quite unique.

8. Who’re the big players in the space?

Companies in travel, healthcare, retail, telecoms, technology, social media and sports are looking at this product. Some of the big private credit and special situations houses are actively exploring this too.

9. What’s the next step for this market?

Where we are with data now is a bit like where we were 40 years ago with IP and brand values. They only really began to appear as separate line items in the balance sheet in the 1980s, but are now frequently used as securitised financing.

At the moment, the data deals we’re involved in are private and have typically involved stressed businesses. But these deals will hit the mainstream soon and beauty of it is that the value of data globally is only going to get bigger.