All posts in “finance”

Juniper Square lines up $25M for its real estate investment platform

Juniper Square, a four-year-old startup at the intersection of enterprise software, real estate and financial technology, has brought in an additional $25 million in Series B funding to fuel the growth of its commercial real estate investment platform. Ribbit Capital led the round, with participation from Felicis Ventures.

Founded in 2014 by Alex Robinson, Yonas Fisseha and Adam Ginsburg, the startup’s chief executive officer, vice president of engineering and VP of product, respectively, Juniper has raised a total of $33 million to date.

The company operates a software platform for commercial real estate investment firms — an industry that has been slower to adopt the latest and greatest technology. Robinson tells TechCrunch those firms raise money from pension funds, endowments and elsewhere to purchase and then manage commercial real estate, using Juniper’s software as a tool throughout that process. Juniper supports fundraising and capital management with a suite of customer relationship management (CRM) and productivity tools for its users.

The San Francisco-based company says it currently has hundreds of customers and manages half a trillion dollars in real estate.

“The private markets are just as big as the public markets … but the private markets have typically not been accessible to everyday investors, and that’s part of what we are trying to do with Juniper Square,” Robinson told TechCrunch. “It’s a tremendously large market that almost nobody knows anything about.”

Juniper will use its latest investment to double headcount from 60 to 120 in the year ahead, with plans to beef up its engineering, product and sales teams specifically as the company expects to continue experiencing massive growth. Robinson said it’s grown between 3x and 4x every year for the last three years.

Felicis Ventures managing director Sundeep Peechu said in a statement that Juniper “is one of the fastest growing real estate tech companies” the firm has ever seen: “They are building technology for an industry that touches nearly every human and every corner of the economy. It’s a hard problem that takes time to solve, but the benefits of making these huge markets work better are tremendous.”

Existing in a relatively niche intersection, Juniper’s job now is to prove itself more efficient and user-friendly than Microsoft Excel spreadsheets, which, Robinson says, are still its biggest competitor.

“Our goal is to be the de facto platform for real estate investment and we are well on our way to becoming that.”

The economics and tradeoffs of ad-funded smart city tech

In order to have innovative smart city applications, cities first need to build out the connected infrastructure, which can be a costly, lengthy, and politicized process. Third-parties are helping build infrastructure at no cost to cities by paying for projects entirely through advertising placements on the new equipment. I try to dig into the economics of ad-funded smart city projects to better understand what types of infrastructure can be built under an ad-funded model, the benefits the strategy provides to cities, and the non-obvious costs cities have to consider.

Consider this an ongoing discussion about Urban Tech, its intersection with regulation, issues of public service, and other complexities that people have full PHDs on. I’m just a bitter, born-and-bred New Yorker trying to figure out why I’ve been stuck in between subway stops for the last 15 minutes, so please reach out with your take on any of these thoughts: @Arman.Tabatabai@techcrunch.com.

When we talk about “Smart Cities”, we tend to focus on these long-term utopian visions of perfectly clean, efficient, IoT-connected cities that adjust to our environment, our movements, and our every desire. Anyone who spent hours waiting for transit the last time the weather turned south can tell you that we’ve got a long way to go.

But before cities can have the snazzy applications that do things like adjust infrastructure based on real-time conditions, cities first need to build out the platform and technology-base that applications can be built on, as McKinsey’s Global Institute explained in an in-depth report released earlier this summer. This means building out the network of sensors, connected devices and infrastructure needed to track city data. 

However, reaching the technological base needed for data gathering and smart communication means building out hard physical infrastructure, which can cost cities a ton and can take forever when dealing with politics and government processes.

Many cities are also dealing with well-documented infrastructure crises. And with limited budgets, local governments need to spend public funds on important things like roads, schools, healthcare and nonsensical sports stadiums which are pretty much never profitable for cities (I’m a huge fan of baseball but I’m not a fan of how we fund stadiums here in the states).

As city infrastructure has become increasingly tech-enabled and digitized, an interesting financing solution has opened up in which smart city infrastructure projects are built by third-parties at no cost to the city and are instead paid for entirely through digital advertising placed on the new infrastructure. 

I know – the idea of a city built on ad-revenue brings back soul-sucking Orwellian images of corporate overlords and logo-paved streets straight out of Blade Runner or Wall-E. Luckily for us, based on our discussions with developers of ad-funded smart city projects, it seems clear that the economics of an ad-funded model only really work for certain types of hard infrastructure with specific attributes – meaning we may be spared from fire hydrants brought to us by Mountain Dew.

While many factors influence the viability of a project, smart infrastructure projects seem to need two attributes in particular for an ad-funded model to make sense. First, the infrastructure has to be something that citizens will engage – and engage a lot – with. You can’t throw a screen onto any object and expect that people will interact with it for more than 3 seconds or that brands will be willing to pay to throw their taglines on it. The infrastructure has to support effective advertising.  

Second, the investment has to be cost-effective, meaning the infrastructure can only cost so much. A third-party that’s willing to build the infrastructure has to believe they have a realistic chance of generating enough ad-revenue to cover the costs of the projects, and likely an amount above that which could lead to a reasonable return. For example, it seems unlikely you’d find someone willing to build a new bridge, front all the costs, and try to fund it through ad-revenue.

A LinkNYC kiosk enabling access to the internet in New York on Saturday, February 20, 2016. Over 7500 kiosks are to be installed replacing stand alone pay phone kiosks providing free wi-fi, internet access via a touch screen, phone charging and free phone calls. The system is to be supported by advertising running on the sides of the kiosks. ( Richard B. Levine) (Photo by Richard Levine/Corbis via Getty Images)

To get a better understanding of the types of smart city hardware that might actually make sense for an ad-funded model, we can look at the engagement levels and cost structures of smart kiosks, and in particular, the LinkNYC project. Smart kiosks – which provide free WiFi, connectivity and real-time services to citizens – have been leading examples of ad-funded smart city projects. Innovative companies like Intersection (developers of the LinkNYC project), SmartLink, IKE, Soofa, and others have been helping cities build out kiosk networks at little-to-no cost to local governments.

LinkNYC provides public access to much of its data on the New York City Open-Data website. Using some back-of-the-envelope math and a hefty number of assumptions, we can try to get to a very rough range of where cost and engagement metrics generally have to fall for an ad-funded model to make sense.

To try and retrace considerations for the developers’ investment decision, let’s first look at the terms of the deal signed with New York back in 2014. The agreement called for a 12-year franchise period, during which at least 7,500 Link kiosks would be deployed across the city in the first eight years at an expected project cost of more than $200 million. As part of its solicitation, the city also required the developers to pay the greater of either a minimum annual payment of at least $17.5 million or 50 percent of gross revenues.

Let’s start with the cost side – based on an estimated project cost of around $200 million for at least 7,500 Links, we can get to an estimated cost per unit of $25,000 – $30,000. It’s important to note that this only accounts for the install costs, as we don’t have data around the other cost buckets that the developers would also be on the hook for, such as maintenance, utility and financing costs.

Source: LinkNYC, NYC.gov, NYCOpenData

Turning to engagement and ad-revenue – let’s assume that the developers signed the deal with the expectations that they could at least breakeven – covering the install costs of the project and minimum payments to the city. And for simplicity, let’s assume that the 7,500 links were going to be deployed at a steady pace of 937-938 units per year (though in actuality the install cadence has been different). In order for the project to breakeven over the 12-year deal period, developers would have to believe each kiosk could generate around $6,400 in annual ad-revenue (undiscounted). 

Source: LinkNYC, NYC.gov, NYCOpenData

The reason the kiosks can generate this revenue (and in reality a lot more) is because they have significant engagement from users. There are currently around 1,750 Links currently deployed across New York. As of November 18th, LinkNYC had over 720,000 weekly subscribers or around 410 weekly subscribers per Link. The kiosks also saw an average of 18 million sessions per week, or 20-25 weekly sessions per subscriber, or around 10,200 weekly sessions per kiosk (seasonality might even make this estimate too low). 

And when citizens do use the kiosks, they use it for a long time! The average session for each Link unit was four minutes and six seconds. The level of engagement makes sense since city-dwellers use these kiosks in time or attention-intensive ways, such making phone calls, getting directions, finding information about the city, or charging their phones.   

The analysis here isn’t perfect, but now we at least have a (very) rough idea of how much smart kiosks cost, how much engagement they see, and the amount of ad-revenue developers would have to believe they could realize at each unit in order to ultimately move forward with deployment. We can use these metrics to help identify what types of infrastructure have similar profiles and where an ad-funded project may make sense.

Bus stations, for example, may cost about $10,000 – $15,000, which is in a similar cost range as smart kiosks. According to the MTA, the NYC bus system sees over 11.2 million riders per week or nearly 700 riders per station per week. Rider wait times can often be five-to-ten minutes in length if not longer. Not to mention bus stations already have experience utilizing advertising to a certain degree.  Projects like bike-share docking stations and EV charging stations also seem to fit similar cost profiles while having high engagement.

And interactions with these types of infrastructure are ones where users may be more receptive to ads, such as an EV charging station where someone is both physically engaging with the equipment and idly looking to kill up sometimes up to 30 minutes of time as they charge up. As a result, more companies are using advertising models to fund projects that fit this mold, like Volta, who uses advertising to offer charging stations free to citizens.

When it makes sense for cities and third-party developers, advertising-funded smart city infrastructure projects can unlock a tremendous amount of value for a city. The benefits are clear – cities pay nothing, citizens are offered free connectivity and real-time information on local conditions, and smart infrastructure is built and can possibly be used for other smart city applications down the road, such as using locational data tracking to improve city zoning and congestion. 

Yes, ads are usually annoying – but maybe understanding that advertising models only work for specific types of smart city projects may help quell fears that future cities will be covered inch-to-inch in mascots. And ads on projects like LinkNYC promote local businesses and can tap into idiosyncratic conditions and preferences of regional communities – LinkNYC previously used real-time local transit data to display beer ads to subway riders that were facing heavy delays and were probably in need of a drink. 

Like everyone’s family photos from Thanksgiving, the picture here is not all roses, however, and there are a lot of deep-rooted issues that exist under the surface. Third-party developed, advertising-funded infrastructure comes with externalities and less obvious costs that have been fairly criticized and debated at length. 

When infrastructure funding is derived from advertising, concerns arise over whether services will be provided equitably across communities. Many fear that low-income or less-trafficked communities that generate less advertising demand could end up having poor infrastructure and maintenance. 

Even bigger points of contention as of late have been issues around data consent and treatment. I won’t go into much detail on the issue since it’s incredibly complex and warrants its own lengthy dissertation (and many have already been written). 

But some of the major uncertainties and questions cities are trying to answer include: If third-parties pay for, manage and operate smart city projects, who should own data on citizens’ living behavior? How will citizens give consent to provide data when tracking systems are built into the environment around them? How can the data be used? How granular can the data get? How can we assure citizens’ information is secure, especially given the spotty track records some of the major backers of smart city projects have when it comes to keeping our data safe?

The issue of data treatment is one that no one has really figured out yet and many developers are doing their best to work with cities and users to find a reasonable solution. For example, LinkNYC is currently limited by the city in the types of data they can collect. Outside of email addresses, LinkNYC doesn’t ask for or collect personal information and doesn’t sell or share personal data without a court order. The project owners also make much of its collected data publicly accessible online and through annually published transparency reports. As Intersection has deployed similar smart kiosks across new cities, the company has been willing to work through slower launches and pilot programs to create more comfortable policies for local governments.

But consequential decisions related to third-party owned smart infrastructure are only going to become more frequent as cities become increasingly digitized and connected. By having third-parties pay for projects through advertising revenue or otherwise, city budgets can be focused on other vital public services while still building the efficient, adaptive and innovative infrastructure that can help solve some of the largest problems facing civil society. But if that means giving up full control of city infrastructure and information, cities and citizens have to consider whether the benefits are worth the tradeoffs that could come with them. There is a clear price to pay here, even when someone else is footing the bill.

N26 says it now has more than 2M customers

N26 announced today that it now has more than 2 million customers — up from 1.5 million in October.

The German fintech startup’s CEO Valentin Stalf was interviewed onstage at Disrupt Berlin with Tandem CEO Ricky Knox, where they discussed the growth of what are sometimes called challenger banks or neobanks — new banks that are taking on the incumbents by focusing on digital tools.

Stalf said N26 is seeing more than €1.5 billion in transactions each month, with €1 billion in deposits. He also discussed the company’s recent launch in the United Kingdom — he didn’t know the exact number of U.K. users, but estimated that the company has tens of thousands of U.K. accounts, with between 1,500 and 2,000 new signups on a single day three days ago.

Meanwhile, Knox said Tandem now has nearly half a million users in the U.K. (“This year, we’re seeing everybody’s growing really quickly.”) He also noted that because Tandem allows users to aggregate different accounts, he’s noticed some of those users are starting to become more focused on individual services.

“What tends to happen, particularly with the early adopter audience, is they will open [an] account with everybody because they want to check it out, they want to get the best product,” he said. “And then what you’ll see is over time, them kind of picking a horse — depending on the functionality they like, depending on, you know, the service they’re getting there — and settling in.”

Tandem is also expanding geographically, specifically to Hong Kong through a deal with Convoy Global Holdings. Asked why he’s making the leap to Asia before launching in other European markets, Knox said, “There are a load of massive Asian markets … The exciting thing here is the opportunity, as I said, for a global bank, and some of these Asian markets are really ripe for disruption.”

In discussing the different models for challenger banks, Knox warned against the dangers of the “marketplace bank” model, where banks make money by connecting customers to third-party services.

“What we found is, the more we try and push revenue in that area there, the less customers love it,” he said. “That’s the challenge with marketplaces: If you build your business model around it, you’ve got an inherent contradiction between customers loving you less when you make more money.”

Instead, Knox argued that customers have a better experience if the bank is willing to recommend free or low-priced services: “And actually at the backend, we’re still making money the same way the bank makes money. So we’re able to fund, if you like, all this great customer stuff at the front end.”

Moderator Romain Dillet quickly pointed out that Stalf was shaking his head while Knox was making his arguments.

“What we see with our customers is, I think if we have a great product, they’re normally also willing to pay a little bit for it,” Stalf said. “It needs to be transparent, and it needs to be a good value to consumers. But I think it’s untrue that customers are always not choosing a product if you price it.”

As for whether we’ll be seeing consolidation in the industry over the next few years, Knox argued, “I’d say there’s plenty of room for the existing cadre of neobanks to be incredibly successful on a global basis without any mergers or acquisitions.” He suggested it’s more likely that the established banks start trying to acquire the challengers, although he said, “That’s not a route we want to take.”

“I think there’s a couple players that are set for being a global bank, and I think we are trying to take the shot to be a global bank,” Stalf added. “I think it’s about building up 50 to 100 million users in the next couple years.”

Spin Analytics automates credit risk modeling for banks

Meet Spin Analytics, a startup that wants to leverage artificial intelligence to automatically write credit risk modeling regulation reports. The company is participating in Startup Battlefield at TechCrunch Disrupt Berlin.

If you work for a big bank, you know how painful it can be to launch a new product. Every time you start selling a new asset, you need to comply with regulations around the world. It can take months and a lot of money to write detailed documents about your asset.

This isn’t like writing a school essay. You need to validate the model, stress test and make sure that everything is sound. “The idea is to automate this process. Today, this process takes 6 to 9 months,” co-founder and CEO Panos Skliamis told me before Disrupt.

Spin Analytics calls its platform RiskRobot. First, you need to get a clean data set. The startup helps you aggregate, merge and cleanse data before processing it. This process alone usually takes 4 to 6 weeks.

Second, RiskRobot makes sure you comply with regulations in Europe, the U.S. and all around the world — Basel III, CECL, you name it.

Finally, Spin Analytics writes the big report. Regulators want to make sure that it’s accurate. That’s why the report contains step-by-step instructions so you can reproduce the model later. Overall, you can expect to leverage Spin Analytics to write a report in less than two weeks.

Spin Analytics has been working on this product for three years and is now testing it with some big banks, such as BBVA and Crédit Agricole. If everything goes well, those banks could end up using Spin Analytics for more and more asset classes.

It’s an easy sell, as banks could end up saving a ton of money. Credit risk management currently costs $500,000 to $1 million per model. “We reduce that by 70 percent,” Skliamis said.

Now, banks need to assess the risk of using this credit risk modeling system. It sounds a bit convoluted, but it also sounds like a great business opportunity.

LearnLux raises $2M from Sound Ventures, Marc Benioff to help employees make financial decisions

Earlier this year, Rebecca Liebman impressed a panel of high-profile investors, including Ashton Kutcher and Salesforce chief executive Marc Benioff, at a SXSW pitch competition. She won and Benioff wrote her a check for $200,000 on the spot.

Today, she’s announcing that her educational fintech startup LearnLux has closed a $2 million seed round from Kutcher’s investment firm Sound Ventures, Benioff, Underscore VC and former Wealthfront CEO Adam Nash. LearnLux operates under a SaaS model, partnering with businesses to offer access to its digital financial wellness product, which helps employees make important financial decisions.

The Boston-based startup was founded by Liebman, 25, and her brother, Michael Liebman, 22, in 2015.

“He was coding from his dorm room when we were first building the product,” Rebecca said. “We’ve had a really interesting experience from a young age. I was working at a lab at MIT with brilliant Ph.D. students and no one could figure out how to open a retirement account. Michael was working at a bank with people who studied finance who still couldn’t figure out how to open a retirement account.”

LearnLux provides interactive learning tools and educational content created in-house to guide workers through their 401k, health savings accounts or stock options, for example. Rebecca says they’ve signed on 10 customers since launching in September.

“There are all these financial decisions you have to make and we allow you to have an interactive experience online where you can playout what those decisions will look like,” she said.

“Finance has been made to confuse people. We had to figure out how to break it down and explain it in a way that makes sense … Whatever kind of learner you are, you will understand more about your financial decisions with [LearnLux.]”