The IFI Interview: Lewis Lee, Founder and CEO of Moat Metrics

Any practitioner in the IP world knows this about financial reporting: among the numerous gaps in GAAP accounting is the treatment of intangible assets. Intangibles, such as patent, trademark, and copyright holdings, are simply expenses incurred when developed in house. When acquired, they’re relegated to goodwill and then amortized over time. Neither accounting method adequately captures IP’s value or importance in a highly creative, knowledge-centered company.

Why make this point? Between 1975 and 2020, intangible assets went from 17% of the S&P 500 market value to a mammoth 90%, according to the most recent Ocean Tomo Intangible Asset Market Value Study. So the biggest publicly traded companies are no longer so concentrated in the world of property, plants, and equipment—the tangible assets that are much simpler to value.

Enter Moat Metrics founder and CEO Lewis Lee, who has spent the latter leg of his career cogitating on the value of IP and how to quantify that for financial practitioners. He spent the first half of his career as a patent attorney, writing claims that protected inventions for the likes of Microsoft and Amazon. He later got turned on to the business side of patents thanks to a famous lawsuit that caught the interest of a hedge fund, which asked for his expertise (more on that below). What he realized: capturing a more accurate value for intangibles is the differentiating factor for, say, a cash-hungry startup with a great set of patents that they can put up as collateral to obtain a loan. Or for a PE firm looking for the distinction of one AI company over another—and then making a capital allocation decision based on the worth of the IP. He started a company in 2010 to help investors understand IP as a business asset instead of a legal asset. That company iterated into another company, which was purchased by insurance behemoth Aon in 2018. Moat Metrics spun out of Aon this past June, with Lee as CEO.

IFI CLAIMS caught up with Lee in August to talk about his new company, now in the process of perfecting its AI-trained tools designed to illuminate innovation metrics and IP for the financial industry. Lee gave us a sneak peek at the platform. Spoiler alert: It’s impressive. We also engaged in a wide-ranging discussion that had him going deep on why the financial world needs to understand IP, how Moat Metrics values patents using products instead of transactions, the importance of inventor teams in addition to executive teams, and why he chose IFI CLAIMS data for the patent portion of the platform. Below is an edited version of the conversation:

IFI CLAIMS: How did you come to be in the patent business?

Lee: I started in 1988. As an undergrad, I earned degrees in both electrical engineering and business. I went to law school at George Washington University and started working in the field. I would go to the patent office and search the patent shoes on behalf of law firms. During my tenure at GWU, I worked at a D.C. law firm called Cushman, Darby and Cushman, which at the time was one of the largest patent firms in the US – it subsequently merged with Pillsbury in the mid-1990s. I became a patent agent in 1990. I have one of those reg numbers that is fairly old: 34,656. Today they’re minting patent agents somewhere in the 80,000 range. I have a discipline in engineering. I have a discipline in business. And I have a discipline in law. And I thought those three disciplines would help me get a job when I graduated. The way those three disciplines come together is really what intellectual property is all about.

I left Washington D.C. in 1991. My wife and I moved to Spokane, Washington, which is my home state. As a young attorney, I had written a book on how to manage intellectual property rights. Don Banner, a former commissioner of the patent office and professor I had at GWU, provided mentorship and encouragement to write the book. That book went on to sell well for the IP space. As a result, I was asked to speak at the University of Washington and teach about licensing. That’s where I met a group of young attorneys from Microsoft, and Microsoft became my first client in 1994. I started a law firm in 1994 called Lee and Hayes with my friend Dan Hayes. For the first decade, Microsoft was our only client. We wrote software patents. As an electrical engineer, most of my practical experience was in software and coding. Our firm grew and eventually represented several other large U.S.-based companies, including Amazon. By the time I left Lee and Hayes 24 years later, the firm had seven offices, nearly 100 attorneys, and we were a specialized patent and intellectual property firm.

IFI CLAIMS: But you’re not a practicing attorney anymore. You’re the CEO of a different kind of firm.

Lee: Moat Metrics is a little different. When I was a patent attorney, I spent most of my time drafting patents. I’ve written a lot of patents in my career—which means writing a lot of patent claims. During my career, which started in the 80s, the IP world went through a shift; the value in companies is now based on intangible assets more than tangible assets. Since the beginning of human history, we were mostly an agrarian society. Then in the 1800s, there was a shift to a manufacturing economy. Then in the 1970s, we started transitioning to an innovation-driven economy or an idea economy, as some call it. The transition from tangible to intangible assets is well known in the IP world.

As a result, I grew interested in thinking about IP as business assets in addition to being legal assets. If it’s true that the value of companies is mostly in intangible assets today, how do we understand that value in a way that’s not solely coupled to litigation or licensing? Traditional patent valuation focused on litigation and licensing principles, collectively called monetization.

My first opportunity to think about that happened in 2005. There was a very famous litigation going on: Research In Motion vs. NTP. RIM was the maker of Blackberry. I was hired by an investment bank on Wall Street to understand which way stock prices were going to move based on underlying events in the patent world. The patent litigation was going on in the Eastern District of Virginia, as well as a reexamination process going on at the USPTO. That work really excited me. To be able to understand the business implications, financial impact, and valuation of a company based on IP events was something else. Patents are kind of like a derivative. They cover some underlying technology that allows you to protect a potential product and revenue stream that allows your company to become more valuable. They are legal documents defining what you own through a series of words in the patent claims. The investment bank asked if I could build a company around these concepts, and I had never thought about that before. So in 2010, outside of my law firm, I started working on a business. It was called IP Street because we were taking IP to Wall Street. The business was designed to help financial practitioners understand IP as a business asset as opposed to just a legal asset. That business was the first iteration of trying to build software and tools to analyze IP for investors and business professionals. Most of the tools at that time were focused on helping attorneys write solid patents. They weren’t focused on helping a business professional understand these IP assets, which are pretty difficult to understand.

IFI CLAIMS: How did that eventually turn into Moat Metrics?

Lee: IP Street lasted five years. We found it difficult to sell the software into a market that I didn’t know a lot about. We launched a new company called 601West a couple years later. 601West also built tools, platforms, and technology, but rather than being just a SaaS company, we sold consulting services on top of the platform. I started working with Aon at that time, first as a channel partner. Aon eventually purchased 601West and I started working full time for Aon in 2018 as their CEO of IP Solutions. That’s when I left Lee and Hayes, 24 years after starting the firm.

At Aon, we started developing insurance solutions for this intangible asset realm. Insurance had not adapted to the world of intangible assets. Most insurance dealt with the tangible world, such as property (buildings and homes) and real assets (cars and valuables). But the industry had its eye on how to think about intangible assets that are so valuable. We set up ways to insure them. We set up ways to finance companies using their IP assets. Aon IP Solutions helped facilitate the financing and insuring of companies with IP and intangible assets. Over the course of that time, we continued to build a platform to analyze and understand innovation, intangibles, and IP in ways that people had never looked at before.

In June of this year, we spun out of Aon with the technology platform and the valuation team. Now we’re Moat Metrics. Moat is a well-known term in business and finance. Warren Buffett refers to moats as things you want to invest around. In the IP world, we’ve always used the term in a sense of protecting the innovation – building IP moats around the innovative crown jewels. Protected innovation gives you competitive advantages. Patents are a negative right. They give you the right to exclude others from making and using. And if you can exclude others from making and using, you have this thing that allows you to protect that product and revenue stream for a period of time. That’s the bargain we make with the government. We tell them our ideas, and the government gives us this limited exclusive right to prevent others from using it for a period of time. We use the term “moats” to mean competitive advantages that companies have.

We named our company Moat Metrics because we bring that analysis to help people understand how good these moats are, where they’re at, how they are compared to others and what kind of value you can get out of these moats. Our team has done a lot of valuation work and the platform we built was developed to support their work. Valuing IP involves valuing the entire IP stack—patents, trade secrets, copyrights, trademarks and knowhow—that makes up the value of companies today. There are no GAAP standards for how you value this. That’s something the world is still trying to figure out.

As part of my career, I spent five years on the advisory board of the Federal Reserve Bank of San Francisco. I felt that part of my role was trying to understand and help inform how intangible assets play into our economy today. We still measure our economy through GDP, which is a manufacturing measure, as opposed to an idea or innovation measure. CEOs often say innovation is the key to growth and success, that you have to innovate or you die. But if you don’t protect innovation, you turn it over to the public good. Innovation alone is not enough. Value is created when you both innovate and then take steps to protect that innovation. Innovation plus protection is a formula that works on any level: society, companies, individuals. America is good at inventing stuff, and that’s what has kept us in the lead economically.

IFI CLAIMS: How is Moat Metrics serving its customers?

Lee: Moat Metrics offers a couple solutions. We have a SaaS platform that we are bringing to market under the commercial name Innovation Alpha™. It’s very new, with a soft launch in late July. It’s a software platform that is targeted toward the investor class: banks, private equity, venture capital, asset managers, or essentially anybody dealing with the analysis of companies for purposes of investment. Equity investors as well as debt investors. If you were working at a private equity fund and you are tasked to understand an investment opportunity in a private growth-stage target company that has little revenue and needs an infusion, the company could back that infusion with its IP. They would call that an asset-backed loan, or ABL.

IP-backed lending requires understanding what exactly those companies do. An analyst working at a private equity firm usually starts with financial data companies for the basics. They look at funding. They look at the financing rounds. They look at the investors. They try to estimate a cap stack and figure out where this company is in its lifecycle and whether it’s investable. After that, they need to figure out their market and product research. What market does this company play in? What kind of product mix are they bringing to market? What are their innovative technologies, if any? What are their competitive advantages? What makes them unique? They often explore strategy and execution. What is this company doing today and what will it be doing in the future? They need to know who the talent is. Who the leaders are. Who the competitors are. Eventually you have to perform some valuation modeling. To get these answers, analysts often spend money on external resources, like professional networks, and hours of simple raw research before even getting to substantive analysis. That usually takes weeks for an analyst, limiting the number of targets any firm can analyze in a year. You have to pull together a lot of resources and talk to a lot of people to be able to do that. Our tool helps them do these tasks in a matter of minutes, not months, reducing underwriting costs and significantly increasing the number of targets that can be deeply examined in a year.

IFI CLAIMS: How does Moat help with the due diligence on the IP?

Lee: Innovation is the core of any company. To be able to understand that innovation and the protected competitive advantages of that innovation, we first identify the products of a company. We then align innovations with the products. And in a third separate workflow, we align IP coverage of the products and innovative technologies, if any. Our platform shows how that plays into the company strategy, who the people are that are going to execute on that strategy, and the likelihood of them being successful on that strategy. We can compare them to all their competitors or peers at the product, innovative technology, and IP coverage levels. And users can leverage Innovation Alpha™ to financially model the company and determine an innovation-aligned enterprise value that is based fundamentally on the company’s innovation, product mix, moats, and competitive posture. Our platform is a game changer for analysts because rather than taking weeks to gather the raw information to do informed analysis, Innovation Alpha™ brings them up to speed quickly, and then they can do advanced analytics on top of that to decide whether or not they’re going to make the investment.

We built the product for financiers and investors, but it’s also meaningful to practitioners in the IP space: enterprise in-house IP teams, outside IP counsel, corporate lawyers, advisors, accountants, insurers, and consultants.

IFI CLAIMS: Are they using your platform in place of their due diligence? Or are they using it as a check of their work?

Lee: We’re very new in the launch of Innovation Alpha™. While we used the platform inside Aon and the technology works, we have only recently launched a commercial version. The platform is well vetted and well trained. And it’s fully AI, not just some algorithms connected to ChatGPT. We’ve trained our AI agents in a systematic way. We have multiple agents solving multiple problems. We’ve spent a lot of time analyzing each company through the platform that is performing research and due diligence for you. If you came onto our platform and typed in a brand new company, you might see it think for two or three minutes while it’s pulling stuff together.

Our tool, for example, generates a full taxonomy of the company’s products and technologies. Today, analysts build this understanding by hand, which takes a significant amount of time. Our platform does this automatically in minutes. Our platform first identifies the products offered by the company, then ascertains the technology in those products, and then maps patents onto the products and technologies. The output gives analysts a level of detail that is impressive and not something available from traditional financial data companies. They would have gone out to professional expert networks, or they might have called a lot of different people to get this information, adding cost and time to the process. And then they’d have to do this all over again to figure out what kind of technologies are in the products. If you’re selling a LiDAR system, you need to go through the product and know all the stuff in that product. Our platform is like a team of researchers who are sent out to do all parts of the research you need to do to understand a company. Our AI agents do that for you.

The commoditized financial data aspect of this diligence that traditional financial data providers bring is great because most investing analysts come from a finance background, so it’s really important for them to get a financial understanding of that. We’re not trying to replace that. We’re trying to add critical new information that enables people to deeply assess innovation, moats, strategies, talent, and values. We allow analysts to go deep on hundreds of targets, rather than 20 targets. We’re trying to get them up to speed a lot faster so they spend more time on higher level analysis.

IFI CLAIMS: What does the tool specifically do around IP?

Lee: In general, we align IP with products and technologies in those products. This allows us to align IP value with the revenue produced by these products. In an investor context, we believe there is really good signal in IP. We named our tool Innovation Alpha, because we believe that understanding these innovative core and competitive advantages of companies can give you an asynchronous investing advantage.

The UI in Innovation Alpha walks analysts through their journey. For example, if you evaluate a target company on our platform, the UI presents seven tabs that guide analysis on the company: Profile, IP Basics, Moat2Market, Moat2Product, Vulnerabilities, Execution, and Valuation.

The Profile tab gives you an overview of the company and some financial metrics, such as funding rounds (if private) and stock price and ratios (if public).

IP Basics is a tab that gives information around the company’s patent portfolio. We use IFI data here, which feeds very smoothly into our engines. IFI knows this space well. We use patent data throughout this product, but the user really sees it in this tab. We show where the patent portfolio lands in the world of products. And we show how the portfolio was built up over the years. You can see whether a company is adding patents or losing patents by product or sub-technologies.

Everything we do is based on claim language; I’ve been working on claim scope algorithms for the past 15 years, so we have some robust claim scope, momentum, and validity algorithms. We understand how that language maps into products and services. We also have a quality score in this tab, which gives our take on how good the patents are overall. Do they have good scope? Will they stand up in court?

Our next tab shows how patents map into markets. Here again, we’ve taken IFI data and spent time understanding the claim language in those patents and then mapped that claim language into the markets that a company is in. We’ve used a lot of AI to make that happen.

IFI CLAIMS: What are some of the other exciting features?

Lee: One of the revolutionary breakthroughs for us is what we call Moat2Product. The holy grail in the IP industry has been finding a way to map patent claims directly to products. Our Moat2Product tab provides this mapping, helping analysts understand patent coverage of products.

Some companies have built classifiers to index their patents according to a taxonomy of the company’s technologies. Some companies rely on government-assigned codes to index their patents. We use a novel approach of building a product taxonomy from scratch, discerning the technologies involved in the various products, and then mapping claim language onto the products and technologies.

Over the decades, the problem with this idea has been how to get product data. In the last few years, we’ve built AI workflows to get that data ourselves. On our platform, you’ll see a company’s entire product lineup that they currently bring to market. We also map patents from other companies onto the same product and technology taxonomy. This enables sophisticated competitive analysis at the product and innovation levels. For instance, if you were analyzing Amazon, and you look under cloud computing in the “object storage services” tech space, Innovation Alpha™ shows Amazon with 578 patents out of a total of 9,246 patents in this space, where there are another 919 entities that own the balance of patents.

Competitive analysis is enriched because we know the universe of companies, the universe of products offered by the companies, the universe of technologies that go into the products, and the universe of patents that map into these companies, products, and technologies. We know what each company is inventing and what parts of the product their patents cover. So now when we look at company’s peers, we can see it at a company level, a product level, and a moat level. In the Amazon example, an analyst can compare to direct competitors at a company level, or drill down and see competitors or peers in a product sub-technology such as “object storage services.” People care about competition based on the product that they’re looking at. Or sub-technology, for that matter. There might be dozens and dozens of companies that make LiDARs and underneath that, there are probably hundreds of companies that make the various components that go into LiDARs. And there are companies that make the software pieces that control the LiDAR. You can see how these all build on each other, and you can understand the competition at the product level and the component level.

This approach also allows us to see a company’s innovation investment philosophy. We know where they’re investing their innovation dollars by watching over time the changing emphasis of investment across products and technologies. We’re essentially capturing the decisions made by people at a company pertaining to R&D spend on new innovations, the types of products to sell, and what innovations and products rise to the level of importance to apply for patent protection. The Moat2Product tab in Innovation Alpha™ manifests the output of a system of expert AI agents that research and harness the implications of these decisions to reveal invaluable insights previously unreachable from human-based research and analysis.

IFI CLAIMS: What else?

Lee: We recently launched a Vulnerabilities tab that reveals intangible risks like innovation gaps and IP litigation risks. This tab provides very meaningful information to assess these gaps and risks. Analysts can see hot spots for IP litigation by product and technology area. Combining the intelligence in this tab with the knowledge from Moat2Products, in-house IP departments and outside counsel advisors can quickly ascertain potential risks to litigation and innovation deficiencies, and take corrective action.

The Execution tab shows the people who are meaningful for nurturing and executing an innovative culture. For any company, we present the executives and a list of innovators. We know which inventors have patented what products for the company, as well as for any other entity. At a macro level, analysts can discern whether the company is accumulating innovative talent or losing that talent, by product and technology areas. We track where the talent came from over the years, and when inventors leave, we identify where they are going. It’s like seeing a trade secret flow chart because people take their knowledge with them.

But in addition to this, we also have the ability to value these things. We take well known valuation ratios, like price to earnings or P/E, and compare it to an estimated ratio implied by the company’s innovation posture. Since we understand the universe of companies, universe of products produced by those companies, the universe of technologies that go into those products, universe of patents that cover each one of those products across all the companies, we can glean an understanding of relative values of the various innovations of the companies and how those innovations support enterprise value. We can drill down and see market drive innovation-implied P/E ratios by product and by technology to understand how the market perceives those innovations and the values it attaches.

How to value IP has always been the big question. Today people use valuation models for litigation but my entire career has been spent exploring how to value IP in a business context. To do that, we thought there’s going to have to be a market where people are buying and selling patents so that we can understand it. It turns out that we figured out a different way to understand the market value of IP through products. The primary job of patents is to protect a space and give that company an advantage for a period of time to reap enhanced rewards and profits. The only way it’s valuable though is if people are willing to buy that innovation. If there is no market for your innovation, there is no value in your IP covering that innovation. It all ties back to whether the market is willing to buy your products that have innovative components.

IFI CLAIMS: Why did you choose IFI data to power this platform?

Lee: A couple reasons. IFI has worldwide data and the IFI team has developed relationships with patent offices all over the world, which is very helpful. The data comes in a way that lets us work with it well. And the IFI team is great to work with. If we do have concerns or questions, they’ve always been a responsive group. When you get good data from all over the world that is easy to work with and then you have a team that is there to support it all the time, well, that’s a pretty easy decision.