All posts in “business”

Here is where CEOs of heavily funded startups went to school

CEOs of funded startups tend to be a well-educated bunch, at least when it comes to university degrees.

Yes, it’s true college dropouts like Mark Zuckerberg and Bill Gates can still do well. But Crunchbase data shows that most startup chief executives have an advanced degree, commonly from a well-known and prestigious university.

Earlier this month, Crunchbase News looked at U.S. universities with strong track records for graduating future CEOs of funded companies. This unearthed some findings that, while interesting, were not especially surprising. Stanford and Harvard topped the list, and graduates of top-ranked business schools were particularly well-represented.

In this next installment of our CEO series, we narrowed the data set. Specifically, we looked at CEOs of U.S. companies funded in the past three years that have raised at least $100 million in total venture financing. Our intent was to see whether educational backgrounds of unicorn and near-unicorn leaders differ markedly from the broad startup CEO population.

Sort of, but not really

Here’s the broad takeaway of our analysis: Most CEOs of well-funded startups do have degrees from prestigious universities, and there are a lot of Harvard and Stanford grads. However, chief executives of the companies in our current data set are, educationally speaking, a pretty diverse bunch with degrees from multiple continents and all regions of the U.S.

In total, our data set includes 193 private U.S. companies that raised $100 million or more and closed a VC round in the past three years. In the chart below, we look at the universities most commonly attended by their CEOs:1

The rankings aren’t hugely different from the broader population of funded U.S. startups. In that data set, we also found Harvard and Stanford vying for the top slots, followed mostly by Ivy League schools and major research universities.

For heavily funded startups, we also found a high proportion of business school degrees. All of the University of Pennsylvania alum on the list attended its Wharton School of Business. More than half of Harvard-affiliated grads attended its business school. MBAs were a popular credential among other schools on the list that offer the degree.

Where the most heavily funded startup CEOs studied

When it comes to the most heavily funded startups, the degree mix gets quirkier. That makes sense, given that we looked at just 20 companies.

In the chart below, we look at alumni affiliations for CEOs of these companies, all of which have raised hundreds of millions or billions in venture and growth financing:

One surprise finding from the U.S. startup data set was the prevalence of Canadian university grads. Three CEOs on the list are alums of the University of Waterloo . Others attended multiple well-known universities. The list also offers fresh proof that it’s not necessary to graduate from college to raise billions. WeWork CEO Adam Neumann just finished his degree last year, 15 years after he started. That didn’t stop the co-working giant from securing more than $7 billion in venture and growth financing.

  1. Several CEOs attended more than one university on the list.

How banks and finance firms are using AI to better engage with and understand you

Against a global backdrop of emerging technologies and ever-changing relationships between businesses and consumers, one thing is clear: leaders in the finance and banking industries will increasingly look to artificial intelligence to understand and engage with their customers in new ways. 

According to a 2017 Forrester report, the widening gap between financial firms that embrace digital growth and business transformation powered by technology and those institutions that continue to do business in traditional ways will continue to widen. 

SEE ALSO: How this AI platform is taking over the business world

As leading banks choose to experiment with new and emerging tech as an opportunity to engage with consumers in unexpected ways, conventional banks and financial institutions will be less able to compete on the global stage. 

It may seem obvious that businesses choosing to leverage predictive technologies, artificial intelligence and mobile applications will be better able to serve their customers and ultimately deliver results. But the truth is many businesses are reluctant to experiment with new technologies — and those who are investing may not be achieving their desired results. 

“Our research shows the global banking and finance sector spends about $85B annually on digital technologies. We estimate 67 percent of this spend is wasted,” said Tiger Tyagarajan, CEO and President of Genpact

However, according to the Genpact Research Institute, there are four key tactics the banking and finance sector can implement to ensure return on investment in the digital space. 

Leverage analytics the smart way 

The way businesses function, the decisions they make, and how they serve clients in the best way possible thrives on access to information. While data analytics is not new, access to smart data is a direct line to the customer. 

However, an intuitive approach to this data is crucial. Particularly when it comes to harnessing this information to identify growing trends and user behavior, uncovering new insights and fine-tuning operations to make smarter decisions and meet business goals. Ultimately, it takes more than just relying on the tech to make decisions. It means leveraging this information in a way that is truly actionable and inspired by the consumers themselves. 

From mobile-first to AI-first 

In almost every way imaginable, we are now in the age of business reinvention. It’s less of an evolution, and more of a revolution in the way modern banking is done. According to Tyagarajan: “successful companies embrace the digital disruption and are willing to destroy a business model to create a new business model.” 

Banks are already using AI to streamline their formerly manual processes for tracking data, saving time and maximising cost benefits. The new horizon? Leveraging AI beyond internal processes to inform consumer interaction. As the finance world grows and develops with this technology, the next step is machine learning that changes and adapts to improve fraud detection and provides smarter customer service by conversing with users every day. By using AI to inform both consumer-facing and internal processes, the potential return on investment can be huge. 

Integrating customer facing and back end of business 

Through artificial intelligence, the front end of business, which consumers interact with daily, and the back end, the internal workings of the finance institution itself, is becoming one holistic entity. Finance companies can no longer simply promise an experience – they need to deliver on their promise within the same interaction, while giving consumers a transparent view of the entire process. 

Lowering costs and increasing ROI 

Artificial intelligence has the benefits of engaging with customers in intelligent ways that offer significant cost savings, by providing smarter decision-making based on customer behavior patterns. Whether it’s new chatbot technology or behind-the-scenes interactions with marketing communications, AI can assist in the creation of customized, intelligent products in increasingly efficient ways. These products and services can even implement AI themselves, with more intuitive interactions including speech functionality or providing advice for personal finance management – at a moment’s notice. 

Using open architecture and a modular approach, Genpact deliver digital products and consulting services, powered by the Genpact Cora AI-based platform, that connects with both legacy systems and new technologies. The result: accelerated development times, higher ROI, and greater flexibility. Combined with an overarching governance layer which mitigate risks, businesses can get the most out of their journey to using artificial intelligence in newer and smarter ways. 

Whether financial institutions are focusing on risk management, customer experience or behind-the-scenes operations within the business, investments in technology like Genpact’s digital platforms and services can, and will, continue to drive efficient returns on investment and have the potential to reinvent the world of finance.

Learn more about how Genpact Cora can help your business.

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Four MIT students have launched DeepBench to democratize access to expert networks

New European financial regulations requiring fund managers at investment firms to pay banks for research and trading services separately could open the door for new entrants in the professional advisory services marketplace.

The rules, which were approved in 2014, but only took effect in January, are proving to be a boon for four MIT students who launched a company last year to try to grab some of the market.

DeepBench, founded by Devin Basinger, Yishi Zuo, Derek Hans and Nikhil Punwaney, is proposing some novel business model solutions to address what the MIT students see as flaws in the existing market — particularly around the use of expert networks in financial advisory services.

DeepBench co-founders Devin Basinger, Nikhil Punwaney, Derek Hans and Yishi Zuo

Expert networks are communities of experienced professionals in a given field. Fortune 500 companies, hedge funds, private equity firms and other entities rely on individuals from these groups for their insights and expertise. The biggest company in the expert network industry, Gerson Lerman Group (GLG), has nearly 50 percent market share and was on track to reach $400 million in revenue in 2016.

But GLG has had its share of troubles. The company played an integral role in providing the expert that passed confidential information to an SAC Capital trader, which was used as evidence in an insider trading case against the firm and its owner, Steven A. Cohen. The hedge fund ended up paying a record $1.8 billion in fines to the SEC (they did not admit wrongdoing in the case).

There is a significant opportunity to disrupt the expert networking space. As more experienced workers retire, some may want to continue putting their skills to use, albeit in a reduced capacity. Being a part of an expert network allows them to be available for clients who request their expertise in a flexible, convenient capacity. Facilitating this specialized knowledge sharing is a billion-dollar market for the taking.

Aside from established players like GLG and its European competitors, AlphaSights and Third Bridge, other startups like Clarity, Slingshot Insights, Catalant (formerly known as HourlyNerd) and Dūcō are also looking to transform the way expert networking is done. GLG is known to charge a group of four within a firm $100,000 for basic access to their network for a year. In comparison, these startups have different approaches and business models to improving the way clients access the expertise they need. Their efforts reflect two main segments within the expert network market: expert calls and project-based work.

DeepBench and Slingshot Industries are focusing their efforts on expert calls. DeepBench launched its current service in March 2017, which uses its “technology-driven, human-assisted” platform to connect individual clients with available experts for a 30 to 60-minute conversation at an agreed-upon rate. In addition, the startup does not require “learners” to sign long-term contracts or prepay, unlike other firms, allowing for greater client flexibility. Slingshot Industries matches groups of clients with similar interests to an expert to answer their questions. The group would crowdfund the cost for chatting with the expert.

Catalant and Dūcō have aimed for matching clients that need long-term projects completed with the relevant experienced contractor. These clients are looking for experts who are interested in extended-duration work. Catalant leverages its algorithms to quickly match prospective clients with the experts they are looking for based on the former’s search criteria.

Their goal is to make this process seamless, so more experts and clients will feel enabled to collaborate outside of a conventional consulting framework or contracting arrangement. Dūcō appears to take a more conventional approach to connecting clients and experts. The D.C.-based startup vets its pool of experts before offering them up to potential clients. Like Catalant, Dūcō uses matching algorithms to match clients with project work needs to experts ready to assist them.

As investors seek information to keep their competitive edge, and firms need outside help in solving internal problems, on-demand access to expert networks will become necessary. DeepBench currently has more than 1,000 registered experts for their closed beta platform. Currently, more than 20 clients are using the service. Most are top consulting companies, investors and product designers.

“We are focused on finding quality high-fit advisors right now instead of increasing the volume we can have available for clients,” Basinger said.

With a shift in E.U. financial regulations, expert networks are using their momentum in the Asian and U.S. markets to establish themselves in Europe. This specialized knowledge sharing can be shaped by startups like DeepBench as competition between firms continues to intensify.

How this AI platform is taking over the business world

Despite the pop culture fiction that artificial intelligence is a far-away puzzle just waiting to be unlocked, the truth is that AI is already a tool that most use often, some of us even every day. 

Just think about it: every time you stop to ask Siri or Google Home or any of our friendly neighborhood pocket assistants for directions or help finding the nearest coffee spot, you’re interfacing with an elegant example of easy-to-use AI. 

For businesses, using chatbots as the first line of defence against customer complaints is now common, providing a handy way to triage queries and customer needs. Again, AI is already an efficient solution to an everyday problem. And while it’s easy to imagine moments where the lives of everyday people intersect with artificial intelligence, and even find examples of our interactions with AI within smaller businesses, for global enterprises the reality of large-scale AI has yet to unfold. 

Enter Genpact. This global professional services firm looks to do just that: leverage artificial intelligence, at potentially massive scale, to ultimately bring us closer to making that future a reality. In this effort they’ve unveiled Genpact Cora, an interconnected platform of best-in-class technologies that span from robotic automation to advanced data visualization to artificial intelligence.  

What global business hasn’t dreamed of a future where artificial intelligence can realistically help solve challenges, at a scale? Just think about it: in the same way that we use virtual assistants in our daily lives to help us navigate a busy schedule or find quick solutions to our everyday problems, there could be tech just on the horizon that helps businesses operate more smoothly, in much the same ways. 

There’s a key difference between Genpact Cora and the helpful virtual assistant in your pocket, however. Nitin Bhat, Senior Vice President at Genpact, explains that because Cora is built on AI and other advanced technologies, it can learn and prescribe what actions are needed for business clients to improve their processes and improve their competitive position in the market.

The implications of this are huge. For businesses eager to bring AI into the fold, it’s not about flashy new products and dazzling tech, but more importantly about using those tools work harder to meet businesses’ goals and prove out the value inherent to the tech itself. 

While AI continues to fundamentally change the way businesses at the enterprise level engage with both customers and other businesses, the truth is that it is largely an unmet need. Genpact estimates that more than 70 percent of enterprise processes can be can be automated, for example, by robotic process automation or through machine learning and intelligent automation. 

More than 70 percent of enterprise processes can be can be automated.

While this type of technology is readily available, adoption depends a lot on a company’s culture and DNA. So many functions may be ready for AI-driven automation, while others would benefit more greatly from robotic automation, for example. 

“With the explosion of new digital technologies and solution options, leaders are struggling to determine how to best exploit these disruptive digital innovations in a pragmatic, industrialized (at scale) and risk-mitigated manner,” Bhat says. Just like with the virtual assistants we use in our daily lives, businesses too must rely on the harmony between machine and humans to ensure that things run smoothly. 

 “Math, science and data analytics will still have a huge role to play, but as machines do more of that work, it will have little value without the human connection of creativity, emotion, judgment, and relationships,” Bhat says. Ultimately, a command and control center that is led by humans and powered by AI can reduce risk of possible errors in how these tools are used. 

There’s still so much remaining to be discovered in the future of AI, but Genpact believes it is on the cutting edge of the industry, being the first to combine automation, analytics, and AI engines in one platform that is designed to bring humans and machine together. As with many new tech tools, there’s still a lot of hype and unrealistic expectations of what the technologies can do, but AI adoption at the large-scale enterprise level is now more real than ever, and Genpact is leading the charge in that effort. 

“Digitization, AI, and other emerging technologies are forcing companies to refresh the way they serve their customers. Just like what we’re seeing in the Twitter universe with real time, the most successful companies are the ones who adjust their strategies in real time to reflect current needs and upcoming trends,” Bhat says. 

Find out more about the implications of AI and Genpact Cora here.

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Elon Musk’s latest SpaceX idea involves a party balloon and bounce house

Elon Musk took to Twitter Sunday night to announce a new recovery method for an upper stage SpaceX rocket. A balloon — a “giant party balloon” to quote him directly — will ferry part of a rocket to a bounce house. Seriously.

If anyone else proposed this idea they would be ignored, but Elon Musk lately has a way of turning crazy ideas into reality.

It was just in 2012 that SpaceX launched and landed its first rocket and now the company is doing it with rockets significantly larger. And then early this year SpaceX made a surprise announcement that it would attempt to use a high-speed boat and large net to catch part of rocket. And it worked after a failed first attempt.

This isn’t the first time a balloon has tried to be used to return a rocket. Legendary programmer John Carmack’s rocket company attempted to use a ballute in 2012 to return a rocket body and nose cone. It didn’t work as planned and according to officials at the time, the rocket made a “hard landing” around the Spaceport America property in New Mexico.

Just like SpaceX’s self-landing rockets and its giant net boat, the goal is to reduce the cost of launching rockets by reusing parts. It’s unclear when this latest plan will be implemented but chances are SpaceX will at least attempt it in the coming future.