Financial firms clear a path for emerging tech

by Michael Hill

As they look toward IT to solve business problems, financial firms and the software developers that cater to them are expanding their acquisitions of emerging technology companies. While overall fintech deal volume subsided slightly in 2018, the number of blockchain and machine learning transactions by those buyers rose sharply.

According to 451 Research’s M&A KnowledgeBase, the number of fintech blockchain deals increased sixfold in 2018, to 19 transactions. Those same acquirers also expanded their appetite for machine learning, printing eight purchases of machine learning targets, from just three a year earlier. The high multiples – including two deals that went north of 20x trailing revenue – and volume of tuck-ins and ‘acq-hires’ attest to the early stage of those technologies. Still, the rationale behind such transactions shows that these technologies, at least in financial services, are entering the mainstream.

Take Ernst & Young, which in July purchased the assets of cryptocurrency accounting software developer Elevated Consciousness. That deal suggests that at least one of the big four accounting firms views cryptocurrencies as an asset class that’s viable enough that it needs to help its clients assess the risk and tax implications of such investments. Elsewhere, TD Bank’s January reach for predictive analytics specialist Layer 6 was driven by its recognition of machine learning’s potential to improve customer experience.

As our surveys demonstrate, financial services rely on IT to meet business goals more so than other industries. In 451 Research’s recent Voice of the Enterprise: Digital Pulse, 56% of financial services executives have business-focused IT goals, compared with 48% for the entire study, while blockchain and machine learning were among the top four technologies anticipated to have the most transformational impact on business operations by 2020.


Snapping up smarts

by Brenon Daly

Having gotten a little richer in its mid-March IPO, Zscaler is now looking to get a little smarter with some M&A. In its first-ever acquisition, the cloud security vendor has reached for TrustPath, a startup that Zscaler plans to use to help speed and sharpen its analysis of the billions of transactions that flow over its platform each day. Not much is known about TrustPath, which is still operating in stealth mode.

Zscaler’s inaugural print continues the trend of information security (infosec) providers emerging as some of the busiest buyers of machine learning (ML) startups, a market that itself is pretty busy. In fact, for the past two years, tech investment bankers we have surveyed have forecast ML to be the single biggest driver for M&A in each of the coming years, ahead of other notable themes such as the Internet of Things and cloud computing.

More importantly, that sentiment is coming through in the actual deal flow. According to 451 Research’s M&A KnowledgeBase, the number of overall ML transactions is on pace to top 120 deals in 2018, three times the number announced just in 2015. Infosec is playing a key role in the record number of ML transactions, with Zscaler joining Amazon Web Services, Splunk and even PayPal in the parade of recent security-focused ML acquirers.

Collectively, infosec buyers are punching well above their weight in the emerging field of ML M&A. Look at it this way: Infosec accounts for roughly 15% of total ML deals in the M&A KnowledgeBase, despite security acquisitions making up less than 5% of all tech transactions we record in any given year.

The main reason for infosec’s outsized role in the ML market is that there’s actually business to be done there. In fact, in a recent survey by 451 Research’s Voice of the Enterprise: AI & Machine Learning, Adoption, Drivers and Stakeholders 2018, infosec emerged as the second-highest rated use case for ML, trailing only ‘business analytics.’ Importantly, the rankings in our survey came from folks who actually have ML technology up and running or are nearly there. With that kind of demand from customers, it’s no wonder infosec suppliers are leading the charge in snapping up smarts.

MIPS takes Wave to the edge

Eyeing a move from training to endpoints, Wave Computing has acquired MIPS Tech, a pioneer in the development of RISC processors. The target, recently spun off of Imagination Technologies, provides the buyer, a designer of artificial intelligence (AI) semiconductors, the chance to sell its wares more broadly as organizations look to run AI algorithms directly on the endpoint.

Founded in 2010, Wave is one of multiple startups producing accelerators for AI workloads, and one of a smaller select group (along with Cambrian Systems, Cerebras Systems, Graphcore and Horizon Robotics) that have already raised over $100m in venture funding. Wave emerged from stealth in 2016 and made its compute appliance for training neural networks available to early-access customers in 2017. In March, Wave said it would be using the MIPS core as the integrated CPU within its next-generation Dataflow Processing Unit.

We noted in a previous report that MIPS would likely prove a valuable asset for AI applications. It’s been in business since the 1980s and has a significant embedded systems user base and a range of extensible cores. Once owned by SGI, MIPS ended up as part of UK-based GPU maker Imagination Technologies, but when Imagination was sold to China-based investor Canyon Bridge Capital Partners, US-based MIPS had to be divested separately to Tallwood Venture Capital for $65m. Tallwood is also an investor in Wave.

It’s likely that the power-efficient MIPS cores will be useful for the development of inference processors within edge devices, giving Wave an end-to-end story beyond its initial training focus, increasing its potential total addressable market significantly. MIPS will continue to be run as an independent unit, and will continue licensing its cores to third parties. 451 Research’s recent VotE: Internet of Things report shows that many companies are already making advanced calculations right on the endpoint – 40% of respondents claimed to run data analysis, cognitive computing or AI at the network edge or perimeter.

For more real-time information on tech M&A, follow us on Twitter @451TechMnA.

No more caution flags with autonomous vehicle M&A

Contact: Mark Fontecchio,

Autonomous vehicle (AV) targets are in the driver’s seat again, this time with Ford Motor’s majority acquisition of software firm Argo AI through a five-year, $1bn investment. The finish line for Ford is 2021, when it aims to roll out a fully autonomous vehicle. To get there, Ford plans to combine its existing self-driving tech with Argo’s artificial intelligence (AI) and robotics software.

Before 2016, Ford had only made one tech purchase in the previous decade, for software to connect smartphones with in-car entertainment. Then last year – a year when tech vendors including Google and Uber were already testing self-driving cars on the roads of Pittsburgh and elsewhere – Ford awoke, buying computer vision and machine-learning software firm SAIPS. That deal followed similar moves by its peers in 2016, as Toyota nabbed Jaybridge Robotics and General Motors paid $581m for self-driving navigation systems provider Cruise Automation.

Auto manufacturers are far from the only companies – or even the only non-tech companies – inking transactions in this space. We are also seeing activity from automotive parts suppliers like Continental AG and Delphi, both of which made an AV acquisition in the past two years, as well as tech vendors such as Google, Uber, Intel, HARMAN and TomTom, the last of which purchased a company in the sector called Autonomos just last month. According to 451 Research’s M&A KnowledgeBase, there have been 20 acquisitions of AV tech since the start of last year, compared with just six in the four years before that.

We highlight AI and machine learning in our 2017 Tech M&A Outlook for application software, as we predict that companies will buy technology and expertise in this area. Subscribers to 451 Research’s Market Insight Service can also access our report on M&A trends and predictions in AI and machine learning.

For more real-time information on tech M&A, follow us on Twitter @451TechMnA.