Data: The Next Great Alternative Investment Asset Class

By Charles Fisher

For decades, investors have diversified their portfolios beyond stocks and bonds by exploring alternative assets like real estate, private equity, commodities, and intellectual property. These assets offer unique benefits such as lower correlation with traditional markets, long-term appreciation, and opportunities for revenue generation. But in today’s digital economy, a new asset class is emerging—one that is reshaping business strategy, mergers and acquisitions (M&A) transactions, and enterprise valuations: data.

Much like real estate or intellectual property, data has both intrinsic and extrinsic value. It can be bought, sold, licensed, and leveraged for competitive advantage. Yet, many companies and investors fail to recognize data’s potential as an asset class in its own right. Those who do are unlocking new revenue streams and driving higher valuations.

In this article, we will explore why data is a viable alternative investment asset class, how it compares to traditional assets, and what businesses and investors can do to capitalize on its financial potential.

What Makes Data an Investable Asset?

To be considered an asset class, an investment must have distinct characteristics that set it apart from other assets while also offering financial returns. Data meets these criteria in several ways:

1. Scarcity and Uniqueness

Scarcity drives value in many traditional asset classes. The price of real estate, for instance, is influenced by location, supply, and demand. Similarly, some datasets are more valuable than others based on exclusivity and relevance. Proprietary customer insights, supply chain intelligence, or industry-specific benchmarks can be invaluable to the right buyer.

For example, Tesla’s autonomous vehicle data is a unique and irreplaceable asset. The company has collected millions of miles of driving data that competitors, including traditional automakers, do not have. This dataset is not only rare but also critical for the development of self-driving technology. As a result, Tesla’s data alone has substantial strategic value, making it a key differentiator in the automotive and AI markets.

2. Revenue-Generating Potential

Data isn’t just valuable—it can generate revenue in multiple ways, much like intellectual property or rental income from real estate. Companies can monetize data through:

• Licensing and Data-as-a-Service (DaaS): Selling or renting datasets to partners or other businesses.

• Subscription Models: Charging for access to real-time analytics, financial insights, or consumer trends.

• Enhancing Existing Products: Using data to create AI-driven enhancements or improve user experiences.

• Cross-Industry Applications: Leveraging data assets in new markets beyond their core business.

For example, Bloomberg generates billions in revenue annually by selling financial data subscriptions to investors. Similarly, companies like Experian and Equifax monetize consumer credit data by selling reports to lenders and businesses. These models prove that data can be a sustainable revenue stream, making it an appealing alternative investment asset.

3. Value Appreciation Over Time

Unlike physical assets, which can degrade, well-maintained data assets tend to appreciate in value over time. This is especially true in sectors such as artificial intelligence (AI) and machine learning, where historical data is crucial for training better models.

Consider medical data: A company that collects and structures healthcare records today may find that its data becomes more valuable as AI-powered diagnostics improve. Similarly, consumer behavior data collected over several years can be more predictive and, therefore, more valuable to advertisers and retailers.

The appreciation of data is also fueled by increasing regulatory scrutiny. As privacy laws like GDPR and CCPA evolve, compliant, well-structured datasets become even more desirable since they can be used without legal risk.

4. Low Marginal Costs and Infinite Usability

Unlike real estate or commodities, which require ongoing maintenance or consumption, data has low marginal costs and can be monetized repeatedly.

A single dataset can fuel multiple revenue streams across different industries. For example, ride-sharing companies like Uber and Lyft generate valuable urban mobility data. This data can be used internally to optimize routes, but it can also be sold to city planners, real estate developers, and transportation agencies without depleting its core value.

This scalability makes data a particularly attractive alternative investment, as it does not suffer from the same diminishing returns as physical assets.

5. Emerging Liquidity and Trading Markets

Historically, one of the biggest challenges for data as an asset class has been its lack of liquidity—companies had data, but no clear marketplace to sell it. However, this is rapidly changing.

New platforms are emerging to facilitate data exchanges and transactions. For instance:

• Snowflake’s Data Marketplace allows businesses to share and monetize datasets in a secure environment.

• Dawex and other data exchanges are creating structured marketplaces where companies can buy and sell data legally and transparently.

• Blockchain-based data markets are developing to enable secure and trackable data transactions, reducing concerns around misuse and duplication.

As data markets continue to evolve, liquidity will improve, making data a more tradable and investable asset class.

Make it stand out

Whatever it is, the way you tell your story online can make all the difference.

As seen above, data shares characteristics with intellectual property while offering better scalability. Unlike real estate or private equity, data can generate revenue with minimal ongoing costs, making it an efficient asset class.

How Businesses and Investors Can Capitalize on Data as an Asset Class

1. Valuing Data as a Formal Asset

Most companies still treat data as an operational byproduct rather than a balance sheet asset. Businesses that formally value their data can unlock new financing opportunities, justify higher valuations in M&A deals, and attract data-savvy investors.

Key steps in data valuation include:

• Cataloging and structuring data assets to assess their completeness and usability.

• Applying financial valuation models, similar to how intellectual property is valued.

• Integrating data valuation into financial reports to demonstrate its impact on business growth.

2. Direct Monetization Strategies

Companies can treat data as a revenue-generating asset by:

Creating Data-as-a-Service (DaaS) models and selling real-time insights.

Enhancing products and services by leveraging data-driven features.

Building strategic partnerships with firms that can benefit from proprietary datasets.

3. Investing in Data-Focused Companies

Institutional investors, private equity firms, and venture capitalists should assess data maturity when evaluating potential investments. Companies that have structured, compliant, and monetizable datasets command higher valuations and offer better long-term returns.

4. Using Data as Collateral for Financing

Forward-thinking lenders are beginning to use data-backed lending, where proprietary datasets serve as collateral for loans. Data copies can be held in the lender’s possession during the term of the loan, speeding the recovery process in the event of a default. Currently, senior secured lenders technically have their borrower’s data as part of their overall collateral package. They’re just unaware of the value of that data vs other assets and how to monetize it in the event of a default.

A New Paradigm for Investment

We are witnessing a fundamental shift in how businesses and investors perceive data. In the past, it was treated as exhaust—now, it’s recognized as an economic engine. The next generation of investors will treat data as they do real estate, private equity, or gold—an asset class that can be valued, traded, and leveraged for strategic advantage.

The Future of Data as an Asset Class

• Standardized data valuation frameworks will emerge, making it easier for companies to recognize data’s financial impact.

• New data marketplaces will increase liquidity and transparency in data transactions.

• Institutional investors will incorporate data into their portfolios as a long-term asset.

Charles Fisher
Co-Founder
Gulp Data

At Gulp Data, we help businesses realize the true potential of their data through structured valuation, monetization strategies, and compliance guidance. Whether you’re looking to raise capital, enhance M&A valuations, or develop new revenue streams, our expertise ensures you make the most of your data assets.

Contact Gulp Data today to explore the value of your data assets.