By Sanford Bragg January 20, 2022
Canalyst, a Vancouver-based platform offering financial models, closed a Series C financing as the firm repositions as a high-quality provider of fundamental data. The firm expects to double its headcount as it expands coverage.
The $70 million Series C round was led by San Francisco-based Dragoneer Investment Group with participation from the Canada Pension Plan Investment Board among others. The latest financing brings total funding to $90 million according to Crunchbase.
The new capital will mainly be used to scale coverage. Canalyst currently covers 5,000 stocks including US public companies with over $100 million in market cap and Canadian companies over $30 million market cap. The firm recently added US domestic IPOs and SPACs. The firm has notified clients that it intends to double coverage to over 10,000 companies as it expands its data beyond North America.
Since hiring a veteran data professional in April 2021 – Jeremy Payne, a former Cap IQ executive who then managed Bloomberg’s fundamental data – Canalyst has been repositioning itself as a fundamental data provider, competing directly with market data vendors such as Bloomberg, S&P, FactSet and Refinitiv. As CEO Damir Hot expressed it, “This investment is an important step in our journey toward becoming the new fundamental dataset of record.”
The company has been releasing a series of dashboards to showcase its data for key segments such as software-as-a-service companies, internet retailers, payments providers and recent IPOs.
Models remain an integral part of the value proposition, not only as a time-saver for clients but also as means to quality-check its data. The firm currently employs 110 analysts who curate the models and verify data. The analysts often have some buy-side or sell-side experience and are based in Vancouver or New York.
The latest product extension, Candas, offers all the firm’s models in Python rather than Excel. A year ago, the firm hired a former Sentieo data scientist – Jed Gore who was previously an analyst at Millenium and portfolio manager at Diamondback Capital – who has overseen the development of the new product.
Canalyst says it has 2,500 users at 400-plus investment firms, banks and corporations, up from 400 users at 150 firms in early 2020. It claims to have roughly doubled revenues in each of the past two years with current annual revenues between $15 and $20 million. Canalyst is looking to expand its client base beyond North American hedge funds, long-only managers and investment banks to non-US banks and asset managers (as international coverage scales) and those focused on credit, private equity and venture capital. Current clients are fairly evenly split between long-only firms and hedge funds, according to company sources.
The firm employs 185 staff in Vancouver and New York, up from just over 100 as of January 2020. LinkedIn registrations of employees have grown by nearly 20% over the last twelve months and 60% over the last 2 years. Employees include 110 equity researchers who maintain the models and validate data.
The firm is currently recruiting for 26 open positions including 9 equity research roles. The firm is seeking to fill two senior research roles: a head of equities to manage the firm’s 110 analysts and a deputy director of research to share the research management duties. Both positions will report to co-founder James Rife who is the current head of research.
The firm was co-founded in February 2015 by Rife. a former Fidelity Investments analyst, and Damir Hot, a former software salesperson. Model development is overseen by Rife, who worked for Fidelity Canada for four years before leaving to be an assistant portfolio manager for a wealth management firm started by the ex-CIO of Fidelity Canada.
We initially thought Canalyst’s main competitor to be Visible Alpha, a platform for distributing broker models which launched a couple of months before Canalyst. However, Canalyst views Visible Alpha as mainly complementary, used by clients as a source of consensus estimates.
Daloopa is a closer competitor since it focuses on creating fundamental data. Daloopa, which raised $20 million last year, is applying AI to extract financial statement data and, like Canalyst, is seeking to expand its coverage internationally. Canalyst also competes with some elements of Sentieo, which also raised $20 million last year, such as its Data Terminal which has interactive online and Excel plugin-based models. Sentieo has been aggressively leveraging artificial intelligence to quickly extract data and sentiment from earnings calls, among other applications.
Canalyst has moved in a different direction, hiring an army of analysts rather than relying on AI, with the goal of reinforcing the quality of its models and data. It is positioning itself to compete more directly with the fundamental data offerings of market data providers such as Bloomberg, FactSet and S&P. However, expanding coverage internationally is not a trivial task, given differences in reporting, timing and language, while its analyst-intensive process is time-consuming and costly. Nevertheless, if it can truly scale globally, it will be a potent rival for the big dogs in the fundamental data space.