Robert Ambrogi BlogElevator Pitch: Our award-winning platform automates capital markets disclosures drafting, and related diligence processes, for companies and their advisors. The range of techniques we use include data analytics and natural language processing. We are legal and tech experts and build our products with input from top law firms (formal partners include Cleary Gottlieb and Vinge). Since 2021, our solutions have been used on c.50 equity and debt transactions worth billions of dollars by a dozen of Am Law 100.
What makes you unique or innovative? We focus on automating core legal (rather than administrative) work and translating premier legal expertise into practical products. We also forged co-development partnerships with top law firms to help ensure that our products meet practical needs. As capital markets disclosures must reflect an issuer’s circumstances, latest financial results, and market developments, our products produce customized text based on evolving facts, rather than relying solely on templates and past precedents.
What problem do you solve? Drafting capital markets disclosure is highly costly, error-prone, and time-consuming. Some estimated that drafting a Form S-1 for a US issuer’s IPO takes almost 1,000 hours. On top of drafting, significant time is spent on the auditor comfort letter process and consistency checks of data points within and across disclosure documents.
Take an excerpt from a prospectus for a non-exhaustive illustration: “Operating revenue increased slightly by USD 118.6 million, or 3.9%, from USD 3.1 billion for the three months ended 31 March 2019, to USD 3.2 billion for the three months ended 31 March 2020.” A lawyer acting for the issuer would look at the issuer’s financial statements and calculate the trends manually to draft this for each line item.
Our flagship solution, by contrast, generates the discussion for tens of line items across all the relevant periods in seconds after parsing the financial statements. It also flags any gaps and unusual trends for the users to supplement with qualitative disclosures.
A lawyer acting for the underwriters, in turn, would scan the disclosure document manually and draw a circle around each relevant number to seek comfort from the auditor. Our circle-up solution automates this process. This spares the lawyers from hours spent on the monotonous tasks of looking for the numbers and physically drawing a circle around each of them, as well as enhancing accuracy in ensuring all the relevant numbers are captured.
Further, we are developing an expansion solution, supported by a six-figure grant from the UK national innovation agency, to automate the consistency checks of such data points within and across disclosure documents.
Our customers need our solutions because (i) law firms face increasingly tight fee caps for capital markets transactions, particularly for equity matters. The amount of work involved in each offering, on the contrary, has continued to grow. This has led to increasingly unsustainable workload and greater scope for errors; and (ii) public companies’ disclosure teams are faced with the (growing) problem of having to do more for less. Our solutions help alleviate this burden, particularly around quarterly disclosure deadlines when the capacity constraint is particularly severe.
Your competitors? We have identified four broad classes of competitors and describe how we are different from each of them below:
- Natural language generation (NLG) players (e.g., Arria) convert structured data into explanatory text. They are largely focused on other verticals (e.g., journalism) and do not discuss financials to the level of granularity required for securities offerings as we do.
- Document automation players (e.g., Contract Express) overlap insofar as we also use traditional automation techniques for parts of the prospectus. We are different as we also perform bespoke automation through data analytics and adapting precedents.
- Precedent databases (e.g., EDGAR) allow users to search for precedents. We go beyond research and help deliver advanced first drafts based on precedent disclosures. We also provide notes to aid drafting and further research where applicable.
- Document review platforms (e.g., Kira) aid due diligence. That diligence exercise (aimed at uncovering insights and flags and patterns) is different from ours: (1) we focus on fact-checking of disclosures which requires semantic matching at data point level and (2) disclosure documents require advanced entity linking and co-reference resolution (e.g., an entity might be variously described as “it”, “Barclays”, or “Barclays Bank” in different places) techniques.
Demo video: This link points to a playlist of demo videos of three of 10BE5’s products N2N, SendCheck, and Circle-Up: https://www.youtube.com/playlist?list=PLZzIUnNGn5raJm0RAIINogJXMn4cZY2F0
Founded: 11/4/2019, London
Target customer. We principally target large law firms and public companies’ disclosure teams. We currently work indirectly with public companies’ disclosure teams through their external counsel only but intend to work directly with them as well in future as we become more established. One of our offerings is also suitable for small law firms and other professional services firms.
Price. N/A.
Expected 2022/2023 gross revenue? N/A.
Number of users/paying customers? 101 – 1,000/< 20
Traction to date. We started commercializing our first product in March 2021. Our solutions have been used on around 50 capital markets transactions worth around $10 billion in aggregate to date, which included high-profile IPOs and debt offerings across the globe. The listing venues for these offerings included Nasdaq (U.S., Baltic, and Nordic exchanges), the New York Stock Exchange, the International Stock Exchange, the London Stock Exchange, the Luxembourg Stock Exchange, the Hong Kong Stock Exchange, and the Euronext venues.
Despite the substantial market slowdown in the capital markets space from early 2022, our revenue almost doubled from 2021 to 2022. We have ten paying customers as of January 2023, all but one of which are Am Law 100 or Magic Circle law firms. As we principally price by usages and license firms as a whole, we do not track the number of users but estimate that it is between 150 and 300 across all our customers.
Plan for growth over next five years. We consider that the following factors are instrumental to our next stage of growth over the next five years:
- Expansion of sales to public companies’ disclosure teams
- Entry into partnerships with other players in the capital markets ecosystem
- Building out our offerings to become the “go-to” provider for drafting capital markets disclosures.
Our strategy to date has seen us focus on premier law firms that handle high-profile capital markets transactions. This has enabled us to build credibility and market recognition. We intend to capitalize on the progress to date to go after the large untapped segment that comprises public companies that, following the initial listings, must file periodic (typically at least quarterly) reports.
The capital markets ecosystem comprises many players, including law firms, stock exchanges, financial printers, accountants, and other professional services. We view partnerships with other players as a critical enabler of growth, both as complementary offerors and a source of referrals. So far, we have forged formal partnerships with a handful of law firms and are in active discussions with a couple of stock exchanges and financial printers.
In addition to the ones we have already released, we have a pipeline of additional solutions targeting different but related work streams. We intend to cement our position as the “go-to” provider for public companies and their advisors for drafting capital markets disclosures. This would open up significant cross-selling and upselling opportunities.”
Outside funding. Less than $1M in outside funding
Describe any ways in which your company is diverse or promotes diversity. Both co-founders, the head of engineering, and the lead software engineer are from ethnic minorities in Europe/U.S.: they are either Chinese, Arab, or African. The lead software engineer is female, built the initial minimum viable product, and led the engineering efforts until she opted to undertake a master’s degree in data science at Imperial College London.
10BE5 is committed to promoting equal opportunities and diversity in employment. We have a policy in place that applies to all aspects of employment with us, including recruitment, pay and conditions, training, appraisals, promotion, conduct at work, disciplinary and grievance procedures, and termination of employment.