Insurance Backend and Auto Insurance Categories Lead Insurtech Exit Activity

Last quarter we reviewed insurance technology exit activity and saw its healthy upward trend. We are now going one step further on our insurtech report and research platform to examine exits by category. We conclude that the Insurance Backend and Auto Insurance categories are at the forefront of insurtech exit activity.

This conclusion was derived from two key data points:

  • The Insurance Backend category leads in the number of exits
  • The Auto Insurance category leads in acquisition amount

We’ll explore these takeaways in some more detail below.

To help set the stage, the graphic below shows insurtech exit activity over time. As you can see, the sector’s exit activity grew significantly over the past few years with a slight drop in 2017 from 2016.

Insurance Technology Exits by Quarter
Insurance Technology Exits by Quarter

Insurance Backend Leads Insurtech in the Number of Exits

The below graph highlights the number of insurtech exit events by category.

Insurance Technology Exit Counts by Category
Insurance Technology Exit Counts by Category

This graph shows that the Insurance Backend category leads the sector with 50 exit events. Its exit activity is more than 1.5 times the next category, Insurance Marketplace, which has 32 exit events.

Insurance Backend contains companies that help insurance companies with their day-to-day operations. They include CRMs for insurance agents, communication tools for insurance companies, and claim filing tools for customers. Some example companies are CHSI Connections, ClaimKit, Shift Technology, and Unirisx.

Let’s now see how insurtech categories compare with one another by acquisition amount.

Auto Insurance Leads Insurtech in Acquisition Amount

The graph below shows the acquisition amounts in different insurtech categories.

Insurance Technology Acquisition Amounts by Category
Insurance Technology Acquisition Amounts by Category

We can see from this graph that the Auto Insurance category leads insurtech in total acquisition amount with over $16 billion. Auto Insurance companies offer car insurance and car telematics products. These products generally detect your mileage and driving behavior to customize your insurance plan. Some example companies in this category include Metromile, The Zebra, Clearcover, and Cuvva.

Auto Insurance has seen some large acquisitions in recent years. Esurance was acquired by the Allstate Corporation in May 2011 for $1 billion. DriveFactor was acquired by CCC Information Services in May 2015 for $22 million. Tempcover was acquired by Connection Capital in January 2018 for $16 million.

The acquisition amount in Auto Insurance represents 30% of all insurtech acquisition activity. It’s noteworthy that its acquisition amount is more than 1.7 times the next category, Enterprise Insurance, which has just under $10 billion.

Conclusion: Insurance Backend and Auto Insurance Lead Insurtech Exit Activity

In summary, we have examined insurtech exit activity by the number of exit events and acquisition amount. The Insurance Backend category leads the sector in the number of exit events. The Auto Insurance category leads in acquisition amount.

To learn more about our complete insurance technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Retail Technology Sector Matures As Funding Shifts to Mid and Late Stages

As we previously noted, retail technology has shown consistent growth over the past few years. Now we are taking a more detailed look on our retail technology report and research platform to examine its funding by round. From our analysis, we can conclude that the retail technology sector has been maturing over the past few years.

This conclusion comes from two takeaways:

  • Funding amount percentages are shifting to mid and late-stage events
  • Funding count percentages are shifting to mid and late-stage events

We’ll explore these takeaways in some more detail below.

To help set the stage, the graphic below highlights retail technology funding amounts over time. As you can see, the sector’s overall funding experienced a burst of growth from 2012 to 2017.

Retail Technology Funding by Quarter
Retail Technology Funding by Quarter

Retail Technology Funding Amount Percentages Shifting to Later-Stage Events

Let’s examine the retail technology funding amounts by round as a percentage of the total, which show changes independent of the total funding amount by year.

Retail Technology Funding Amount Percentages
Retail Technology Funding Amount Percentages

The above graph shows that the funding amount percentages in Seed and Series A rounds dropped relative to the other round types. In addition, the funding amount percentages in all the other rounds stayed constant or increased.

Specifically, Seed and Series A funding amount percentages fell by over half from 32% to around 13%. On the other hand, Series C and Late Stage funding amount percentages grew from 24% to over 40% during the same time period.

We see that the funding amount percentages by round indicate a shift from early-stage to mid and late-stage events from 2012 to 2017. Would the funding event count graph show the same trend? Let’s examine that in the next section to find out.

Retail Technology Funding Count Percentages Shifting to Later-Stage Events As Well

The below graph shows the retail technology funding counts by round as a percentage of total events.

Retail Technology Funding Count Percentages
Retail Technology Funding Count Percentages

This graph supports our previous conclusion from the funding amount graph. In particular, Seed and Series A funding count percentages dropped significantly from 80% to under 50%. The funding count percentages in all other rounds increased by various magnitudes from 2012 to 2017.

Conclusion: Retail Technology Sector Matures As Funding Shifts to Later Stages

In summary, we have seen retail technology funding amounts and events shift from the early-stage rounds to the later-stage rounds. These observations led us to conclude that the retail technology is in the maturing phase.

To learn more about our complete retail technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Security Technology Startup Highlights – Q1 2018

Here is our Q1 2018 summary report on the security technology startup sector. The following report includes an overview, recent activity, and a category deep dive.

To learn more about our complete security technology report and research platform, visit us at www.venturescanner.com or contact info@venturescanner.com.

Security Technology Sector Overview – Q1 2018

Our security technology report and research platform contains companies that enable enterprises and consumers to secure their data and networks. They often focus on protecting information, authenticating identity, and defending against cybersecurity attacks.

In this post we examine the different components of security technology and how they make up this startup ecosystem. We have classified the companies into 14 categories. This blog post will illustrate what these categories are and which categories have the most companies. We will also look at how these categories compare with one another in terms of their funding and maturity.

Threat Detection and Mitigation Is the Largest Security Technology Category

Let’s start off by looking at the Sector Map for the security technology sector. As of March 2018, we have classified 1063 security technology startups into 14 categories that have raised $25 billion. The Sector Map highlights the number of companies in each category. It also shows a random sampling of companies in each category.

Security Technology Sector Map
Security Technology Sector Map

We see that Threat Detection and Mitigation is the largest category with 283 companies. These companies actively monitor networks to detect attacks and mitigate them in real-time. Some example companies include DarkTrace, Cylance, Menlo Security, and Vectra.

We have seen what the different categories making up this sector are and the number of companies in each. What about their funding and maturity in relation to one another? Let’s look at our Innovation Quadrant to find out.

Most of the Security Technology Categories Are Pioneers

Our Innovation Quadrant divides the security technology categories into four different quadrants.

Security Technology Innovation Quadrant
Security Technology Innovation Quadrant

We see that the Pioneers quadrant has the most security technology categories with 9. The Pioneer categories are in the earlier stages of funding and maturity. The Disruptors quadrant contains two categories: Cloud Security and Computer Forensics. These two categories have acquired significant financings at a young age. The Established quadrant contains Industrial Security, which has reached maturity with less financing. The Heavyweights quadrant includes two categories: Endpoint Security and Email Security. These two categories have reached maturity with significant financing.

We’ve now seen the security technology categories and their relative stages of innovation. How do these categories stack up against one another? Let’s look at the Total Funding and Company Count Graph.

Threat Detection and Mitigation Startups Have the Most Funding and Companies

The graph below shows the total amount of venture funding and company count in each category.

Security Technology Total Funding and Company Count
Security Technology Total Funding and Company Count

As noted earlier, the Threat Detection and Mitigation category leads security technology with 283 companies. In addition, the above graphic highlights that Threat Detection also leads in funding with almost $10 billion. Some of the best-funded companies in this category are FireEye ($841M), Tanium ($581M), and Alert Logic ($387M). It’s also noteworthy that the funding in Threat Detection is 60% higher than the funding in the next category, Data Security.

Conclusion: The Threat Detection and Mitigation Category Leads the Sector

From the above analysis, we can see that the Threat Detection and Mitigation category leads security technology in funding and company count. On the other hand, Endpoint Security and Email Security stand out as the Heavyweight categories in our Innovation Quadrant. They have reached maturity with significant average funding per company versus other categories. It’ll be interesting to see how the security technology landscape will change and develop throughout the rest of 2018.

To learn more about our complete security technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com

Retail Technology Startup Highlights  – Q1 2018

Here is our Q1 2018 summary report on the retail technology startup sector. The following report includes an overview, recent activity, and a category deep dive.

To learn more about our complete retail technology report and research platform, visit us at www.venturescanner.com or contact info@venturescanner.com.

Fintech Sector Matures As Funding Shifts to Later Stages

As previously seen, funding into financial technology has increased significantly in recent years. Now we are going one level deeper on our fintech report and research platform to examine its funding by round. From our analysis we can conclude that the fintech sector is continuing to mature over time.

This conclusion comes from two takeaways:

  • Funding amounts are shifting from early-stage to later-stage events
  • Funding counts are dropping in the Seed round and growing elsewhere

We’ll explain these takeaways with some graphics that show fintech funding activity by round.

To help set the stage, the graphic below illustrates fintech funding amounts over time. As you can see, the sector’s overall funding showed robust growth over the past few years.

Fintech Funding by Quarter
Fintech Funding by Quarter

Fintech Funding Amounts Shifting to Later-Stage Events

Let’s examine the fintech funding amounts by round as a percentage of the total, which show changes independent of the total size.

Fintech Funding Amount Percentages
Fintech Funding Amount Percentages

As shown in the graph, the funding amounts dropped in the Seed and Series A rounds and increased in the Late Stage from 2012 to 2017. Specifically, Seed round funding amounts shrunk from 9% to 3%, and Series A amounts shrunk from 23% to 11%. On the other hand, Late Stage funding amounts grew from 2% to 24% over the same time period.

We see that the funding amount percentages by round indicate a shift from early-stage to later-stage events from 2012 to 2017, would the funding event count graph show the same trend? Let’s examine that in the next section to find out.

Fintech Funding Counts Dropping in Seed Round and Growing in All Other Rounds

The below graph shows the fintech funding counts by round as a percentage of total events.

Fintech Funding Count Percentages
Fintech Funding Count Percentages

This graph supports our previous observation from the funding amount graph. In particular, Seed round funding counts decreased from 63% to 30% from 2012 to 2017. As a result, the funding counts in all other rounds increased by various magnitudes.

Conclusion: Fintech Sector Continues to Mature Over Time

In summary, we have seen that fintech funding amounts shifted from Seed and Series A to later-stage events. Fintech funding counts also dropped in the Seed round and grew in all other rounds. These observations led us to conclude that the fintech sector is continuing to mature over time.

What are your thoughts on this? Let us know in the comments section below.

To learn more about our complete financial technology report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.

Deep Learning Applications and Computer Vision Platforms Lead AI Exit Activity

Last quarter we reviewed artificial intelligence exit trends and saw strong growth. We now dig in one level deeper on our AI report and research platform to examine exits by category. We conclude that Deep Learning Applications and Computer Vision Platforms are at the forefront of AI exit activity.

This conclusion was derived from two takeaways:

  • The Deep Learning Applications category leads in the number of exits
  • The Computer Vision Platforms category leads in acquisition amount

We’ll illustrate these takeaways with some graphics that show AI exit activity by category.

To help set the stage, the graphic below shows AI exit activity over time. As you can see, the sector’s exit activity experienced strong growth over the past few years.

Artificial Intelligence Exits by Quarter
Artificial Intelligence Exits by Quarter

Deep Learning Applications Leads AI in the Number of Exits

Let’s examine the exit events for each AI category. Exit events include both acquisitions and IPOs. The below graph highlights the number of AI exit events by category.

Artificial Intelligence Exits by Category
Artificial Intelligence Exits by Category

This graph shows that the Deep Learning Applications category leads the sector with 71 exit events. Natural Language Processing comes next with 46 exit events.

Deep Learning Applications includes companies that utilize computer algorithms to optimize operations in vertically specific use cases. Examples include using deep learning technology to detect banking fraud or to identify relevant sales leads. Some example companies are Sift Science, SparkCognition, Sumo Logic, and BenevolentAI.

Let’s now see how AI categories compare with one another by acquisition amount.

Computer Vision Platforms Leads AI in Acquisition Amount

The graph below shows the acquisition amounts in different AI categories.

Artificial Intelligence Acquisition Amounts by Category
Artificial Intelligence Acquisition Amounts by Category

We can see from this graph that the Computer Vision Platforms category leads all the other AI categories by far. The total acquisition amount in this category is around $16 billion. Computer Vision Platform companies process images to algorithmically derive information from them and recognize objects. Some example companies in this category include Cortica, Blippar, Kairos, and Clarifai.

Computer Vision Platforms has seen some large acquisitions in recent years. Mobileye was acquired by Intel in March 2017 for around $15 billion. Movidius was acquired by Intel in September 2016 for $400 million. Magic Pony Technology was acquired by Twitter in June 2016 for $150 million.

The acquisition amount in Computer Vision Platforms represents 72% of all AI acquisition activity. It’s noteworthy that its acquisition amount is more than ten times the next category, Deep Learning Platforms. Additionally, Computer Vision Platforms’ acquisition amount is highly concentrated, with 15/16 of the amount coming from the $15 billion Mobileye acquisition.

Conclusion: Deep Learning Applications and Computer Vision Platforms Lead AI Exit Activity

In summary, we have examined AI exit activity by the number of exit events and acquisition amount. The Deep Learning Applications category leads the sector in the number of exit events. The Computer Vision Platforms category leads in acquisition amount. It will be interesting to see which other categories take the lead in AI exit activity in the rest of 2018.

To learn more about our complete artificial intelligence report and research platform, visit us at www.venturescanner.com or contact us at info@venturescanner.com.