EQUIAM’s proprietary selection model is a systematic and data-driven model that ranks thousands of growth and late-stage private companies using 90+ proprietary investment signals derived from over 60 million data points. Each month, we generate a comprehensive ranking of our private company universe and thus can construct a real-time sector ranking based on the underlying constituents.
After performing our September analysis of private sector performance, we have highlighted a strong performing sector Artificial Intelligence & Machine Learning and a weaker performing sector Insurtech.
The AI & ML sector constituents scored well due to:
- High Capital Usage Efficiency, market share capture, and ultimately, value creation
- Path to profitability and strong balance sheets
- Attractive valuation metrics (e.g. EV/Rev) and growth-adjusted valuation metrics (e.g., EV/Rev/Growth)
On the other hand, the Insurtech constituents displayed poor scores in each of the three above signal buckets, which contributed to the sector, in general, ranking as one of our worst performing sectors.
In the chart below, we highlight AI & ML sector constituents that scored highest on the metrics laid out above, positively contributing to the sector's overall rank. The opposite holds true for the Insurtech companies shown.
Artificial Intelligence & Machine Learning:
Artificial Intelligence and Machine Learning (AI & ML) has seen growth in leaps and bounds over the past decade with successively larger foundation models that have been trained on vast datasets. A large contributor to the growth of the industry has been more efficient GPU processors and decrease in cost of cloud computing. It is important to note that AI & ML is still in the early innings and commercial applications and outcomes remain limited in scope and scale. However, investors and companies are devoting tremendous amounts of capital and time to improving AI & ML and pushing it into new sectors of the economy. VC funding for the sector is on track to hit $90B+ for 2022 and it remains one of the sectors continually attracting capital and strong valuations.
As a complement to Big Data, AI & ML is pushing the envelope in helping companies analyze and synthesize large data sets and provide insights previously missed. Stream analytics can generate insights continuously and integrate with data science frameworks and enable AI inference to apply to data instantaneously, reducing latency in decision making. There are endless applications to AI & ML and private companies continue to innovate and push the envelope.
The correction in the market has driven down EV / Revenue multiples for many of the public AI & ML companies from 20x+ to sub-10x (higher for high growth companies). Private company EV / Revenue multiples are more in the 10.0x - 30.0x range depending on level of maturity and growth trajectory. Of note is that most of the private company multiples have seen a retrade from the stratospheric highs of 2021 where a 50x+ multiple was not only common but expected. It is not uncommon for the private AI & ML companies in the EQUIAM GENIUS model to be projected to grow revenue at 50%+. From an EV/Rev/Growth perspective and the market opportunity for growth and adoption, we believe there are ample opportunities within the private AI & ML sector.
AI & ML companies also generally score highly on EQUIAM’s proprietary Cancer Signal, a measure of combining employee growth, revenue growth, and profitability to filter companies growing at a sustainable rate. Most of the AI * ML companies in EQUIAM’s GENIUS model score in the top quartile of the Cancer Signal suggesting companies in the sector are poised to grow into their valuations and ultimately reach profitability. Given the tremendous amount of funding poured into the sector, these companies also tend to be well capitalized and have strong balance sheets to help fund R&D.
We don’t foresee a slowdown in the adoption of these technologies and ample opportunity for all sectors of the economy to continue to implement AI & ML into their business models.
Insurtech:
There have been few sectors that have fared worse than Insurtech in the public markets with companies like Oscar, Root, and Hippo down nearly 90% from their highs. A lack of path to profitability and margin pressure have pushed Insutech revenue multiples to sub-1.0x inline with legacy insurance companies (which to be fair are profitable).
Many of the Insurtech companies are running into the issue that plagues many tech companies: acquiring customers at a low enough cost and keeping them long enough to turn a profit. The Sales and Marketing expense and/or Policy Acquisition costs of these companies is far outstripping the revenue collected. Insurance Brokers and customer acquisition companies (the middlemen) are finding it difficult to differentiate and sell customers to the insurance companies at a rate that outstrips their marketing cost.
Our data shows much higher multiples in the private sector with many companies valued at 10x+ revenue (with a few below 10x and above 20x), based on most recent price marks. Our proprietary employee data shows a freeze on hiring and increase in layoffs. VC funding in the space has slowed dramatically, down nearly 60% from 2021 and given the reset in public markets we may see flat or down rounds in the near future.
Disclaimer: This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by EQUIAM LLC (an offering to invest in an EQUIAM LLC fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety). Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others.
