Archive for the ‘Trends’ Category

The Next New New Thing

In 1999 Michael Lewis told the story of “the new new thing” in terms of a single individual, Jim Clark, a “new-capitalist adventurer” in the words of the NY Times reviewer.  It was an exciting story but as we approach 2015, it seems dated, even quaint – dated because the new new things were individual companies – Silicon Graphics, Netscape, myCFO and Healtheon.

Today new new things are explosions of companies that seem to come in waves – waves such as cloud computing, Big Data and now what Shivon Zilis, of Bloomberg Beta, calls machine intelligence.  One wave often drives another, or at least enables it.  Machine Intelligence, perhaps the newest new thing, depends on massive data sets, so Big Data had to come first.

Shivon has done us all a service by scouring the startup world for artificial intelligence, machine learning and data-related technologies and created a landscape that puts them all in context.  Her diagram of the Machine Intelligence Landscape – she’s using “machine intelligence” as a unifying term for machine learning and AI – has five categories, each with multiple subcategories that suggest some of the areas where they will transform the way we work and multiple companies already implementing them (www.shivonzilis.com/machineintelligence):

  • Core Technologies

o   Artificial Intelligence – Deep Learning – Machine Learning – NLP Platforms – Predictive APIs – Image Recognition – Speech Recognition

  • Rethinking Enterprise

o   Sales – Security/Authentication – Fraud Detection – HR/Recruiting – Marketing _ Personal Assistant – Intelligence Tools

  • Rethinking Industries

o   AdTech – Agriculture – Education – Finance – Legal – Manufacturing – Medical – Oil and Gas – Media/Content – Consumer Finance – Philanthropies – Automotive – Diagnostics – Retail

  • Rethinking Humans/HCI (human-computer interaction)

o   Augmented Reality, Gestural Computing, Robotics, Emotional Recognition

  • Supporting Technologies

o   Hardware – Data Prep – Data Collection

Shivon recommends we focus on her core technology category for innovations at the heart of machine intelligence and suggests using the landscape to package some of the technologies into a new new industry application for those of us looking to build a company.  So spot the market opportunities, and you have an amazing map for innovation!  Even Harry Potter didn’t have one of these!

Making Sense of Change

We all live in perpetual information overload and a swirl of new technologies.  Continuous learning is no longer an option.  Learn or be  lost.  Keeping track of it all, fitting pieces together, is a challenge that seems to become increasingly impenetrable.  Now Brian Solis of Altimeter has given us a structure to help us sort through the emerging digital universe.  Thank you, Brian!

Cloud-based social, mobile and real-time technologies are the hub of the Brian Solis Wheel of Disruption.

In the first circle around the three core themes are the following seven emergent technologies and sectors:

  • Big Data
  • Apps
  • Ephemeral (content that disappears in a short time)
  • Geo-location
  • Messaging
  • Gamification
  • 2d Screen

The second circle contains seven more:

  • Wearables
  • Makers
  • Beacons
  • Internet of Things
  • Sharing
  • Virtual AI – AR (Artificial Intelligence & Augmented Reality)
  • Payments

Alongside the wheel are six themes implemented by these technologies::

  • Platforms
  • Alternative Currencies
  • Mass Personalization
  • Crowd Funding/Lending (and I would add, Sourcing)
  • Anonymous/Private web
  • Instant Gratification

Here’s Brian’s marvelous infographic: http://www.briansolis.com/2014/12/digital-transformation-year-review/

My head already feels clearer!  I hope yours will as well!

Media Heads Up for 2015: 12 Takeaways

Media visionaries looked to the future at the Gotham Media’s Digital Breakfast at Frankfurt Kurnit Klein & Selz and made some predictions about social, mobile, TV and more for 2015 and beyond. Here are some highlights:

1. Ever-faster change – new things rise higher faster and fall faster.

2. Sensors all around that are passively aware of you. All cell phones have omnipresent computing.

3. Mobile payments. Apple’s entry will determine whether they make a difference. Most are safer than plastic, says John Abell, Senior editor, LinkedIn.

4. Continued migration of devices to mobile – even Facebook and video on mobile. Increasing importance of the second screen, though it’s still primitive. Monitors are losing to individual devices. “When the first screen gets boring, people go to the 2d screen,” reports Paul Berry, RebelMouse Founder and CEO

5. The steady growth of Facebook and mobile pose a challenge of how many pages per person can be sustained on your site.

6. Niche social networks will be big – a space for passionate sharing. (ED: Vertical networks were lumped into discussion of the category.) Niche networks will be combined with the 2d screen in the future – but with more than Twitter’s limited characters, predicts Berry.

7. People talking in a real voice as opposed to the institutional voice of mainstream media so that you hear individuals.

8. Infinite choice in content. “The quality level has been raised,” said Lockhart Steele, Editorial Director of Vox Media. “Now you have to do great stuff to get attention because there’s so much choice. . . The biggest challenge to media is the conversion to mobile. A lot of journalists are still writing in newspaper style.”

9. “Content is still king. It’s entirely defined by great talent,” according to Eric Wattenberg, Co- Head of Alternative Television at CAA.

10.“Traditional ads aren’t working. Only bots click. Millennials don’t even see the ads,” says Berry. At Vox, an in-house creative agency helps advertisers create native advertising. “The agency relationship is broken,” adds Steele. Every company has the opportunity and responsibility to be a media company, continues Berry. You need a product to be worth someone’s obsessing about it. Then put your money behind them. How do you measure social media effectiveness? Do viewers click? Share?

11 “But then we still don’t know how to measure TV,” Abell reminds us. “Yet, I don’t see how anything can supplant anything as unifying as TV.”

12.“The challenge for TV is how to get and keep an audience and grow it. It may be a combination of traditional TV with live elements in other forms of entertainment so that every week you’ll have to tune in and it’ll be fun and exciting to see what happens,” speculates Wattenberg.

Provenance: Gotham Media’s Digital Breakfast at Frankfurt Kurnit Klein & Selz 12.9.14. Alan Sacks, moderator – Counsel, Frankfurt Kurnit Klein I& Selz PC Panelists: John Abell, Sr. Editor, LinkedIn Paul Berry, Founder and CEO, RebelMouse; Lockhart Steele, editorial Director, Vox Media, and Eric Wattenberg, Co-Head of Alternative television, CAA

Banking without Banks

Banks said it couldn’t be done.  But innovative entrepreneurs are capitalizing on social media, Big Data and machine learning technology to make capital available to people who couldn’t get it before or couldn’t get it at affordable rates.

One company enables middle-class consumers in emerging markets to gain access to short-term loans by using social media to prove their credit worthiness.  Another has, in just 7 years, made $1 billion in business loans to small businesses with poor credit.  A third manages a credit marketplace of borrowers and investors in order to facilitate personal and business loans at lower rates than borrowers can get from banks – $7 billion in loans in 7 years. The fourth provides micro-loans without collateral to low-income Hispanic families who lack a credit history.

The companies are Lenddo, OnDeck, Lending Club and Progreso Financiero, and their founders told their stories at the Data Driven NYC Meetup in May.

The Situation

According to James Gutierrez, Founder & CEO, Insikt, Inc., a financial data analytics company, and formerly CEO of Progreso Financiero, which he founded:

  • New regulations for banks have changed lending:

o   Credit Card Act

o   Dodd Frank

o   Basel II

o   Basel II/II.5.

  • The availability of revolving credit is down – affects small business lending by banks – non-prime consumers are hit hardest
  • Technology is changing lending across the value chain, driving the price down

o   Applications drive higher volume and lower costs

o   Underwriting – big data makes more sources accessible and results in lower risk and increased capital

o   Servicing – electronic payments – ACH means lower costs and lower risks

o   Mobile payments by lower income borrowers – lenders use SMS for collection to lower cost and lower risk.

  • Banks can’t keep up with nonbank alternative lenders, which are transforming all loan products.

Four Nonbank Alternative Lenders Speak

Jeff Stewart, Founder & CEO, Lenddo

  • Launched early 2011
  • Serves middle class consumers in emerging markets
  • Goal was to involve the crowd in lending to the middle class using micro finance techniques and social media data to establish creditworthiness where none exists
  • Social data add value by making it possible to map good vs. bad borrowers in terms of affiliation because “birds of a feather  gather together” – “even two degrees out tells us how you will perform”
  • Integrates social networks with mobile & the cloud to use data sources
  • Works with the community on both demand generation and collections/repayments
  • Storage was a major technology issue – Chose MongDB at the outset with Amazon Web Services – database grew explosively – all opt in
  • User data = social data – grew exponentially – expensive even when only 20K members.
  • Realized “It’s big data, not big database” so they moved data to simple storage, created cache MongoDB for queries and cut costs 70% – they think about data use cases.
  • No database frees you to solve problems
  • Looking closely at bitcoin block chains to add value for transactions.

Noah Breslow, CEO, OnDeck

  • Has made $1 billion in business loans to small businesses with poor credit over 7 years
  • Loan size is small – $100K-$300K; banks need larger loans or they lose money – they need $1 million and up
  • SMEs represent a large and underserved addressable market
  • Built a platform to connect Main St. to Wall St., with OnDeck playing all four essential roles:  originator, servicer, credit bureau for collecting and aggregating data, and credit scoring (FIC0)
  • The database tracks small businesses from birth to death.
  • The digital footprint of different stores is totally different and depends on different data sources
  • Co. adds private performance data to public data and does a lot of fraud management and triangulation
  • Developed a different kind of credit score – it’s a business credit score, not a personal one with the focus on debt service calculations:  cash flow, trade credit, business attributes.  Social data is noisy – need to look at patterns.
  • A large number of small transactions – restaurants, retailers, doctors & dentists, small manufacturers, etc.
  • Gather data for scoring a business from many sources.  Building a data aggregation and learning platform that includes Mechanical Turk and common sense.
  • They price to risk.

Renaud Laplanche, Founder & CEO, Lending Club

  • Has created a credit marketplace of borrowers and investors, where Lending Club facilitates loans but is not involved on the credit side.
  • As a result, LC can operate at a lower cost than banks – banks have 5%-7% of amounts lent in operating expense vs. LC , which is under 2% and declining.
  • LC incurs none of some bank costs, such as the cost of branch offices, reserve requirements, and has lower costs or more advanced technology for customer acquisition, underwriting, origination and servicing.
  • Bank’s intermediation cost for credit cards is 16.99%.  LC’s range is 7.9%-127% with average intermediation cost of 4.83%.
  • A lower lending rate means a higher return to investors.
  • Have consistently controlled LC’s growth.  Now have 550 employees; hire 100 people every 6 mos.
  • Use data for marketing, credit, fraud and collections – receive about 9,000 loan applications a day.  Less than 10 are fraudulent, so that fraud becomes a needle in a haystack.
  • Fraud predictors:  time of day, frequency, etc.  New data sources:  device, online footprints, application use.  Look at consistency of the information provided, behavior online footprint, machine/device and location signal.
  • LC uses machine learning to assess risk and predict fraud based on more than a thousand attributes
  • Fraud attempts have declined from 5% to 2%.
  • Just formed a partnership with Union Bank in San Francisco, which overcomes the challenge of complying with 49 sets of state regulations for Lending Club and opens the way for a traditional bank to offer products it could not otherwise offer.  (Probably an indicator of a future trend.)

James Gutierrez, Founder & former CEO, Progreso Financiero

  • James was a 2005 MBA from Stanford
  • Micro finance gave him the idea for Progreso Financiero – unsecured micro loans and debit cards – delivered from a table in the supermarket – to help immigrants with no FICO scores
  • Typical loan size was $1,000 for 12 months.  Had to make 10,000 loans to get $1,000 back.
  • Immigrants with no FICO scores are a challenging population to underwrite
  • What he did:

o   Took an eHarmony approach with a robust application with extremely detailed personal data.  Detailed data turned out to be valuable.

 o   Booked some bad loans – a learning experience – the most valuable data is performance data – having a huge amount of data helps build a model – data science is no help

 o   Aggregated and analyzed alternative data:

      • 300 attributes on the application
      • Separate borrowers into nodes
      • Later 2,500 attributes from multiple sources
      • Over 120 segments
    •  Data helped simplify the process & determine the score
    •  Merged alternate data with bureau data
  • Fair equal Opportunity Act – the jury is out on what data you can use to deny credit, the actual underwriting decision
  •  Made more than 500,000 loans with single digit loses
  • Partnered with Prosper, the first peer-to-peer lending marketplace, with more than 2 million members and over $1 billion in funded loans.
    •  Risk model design
    • Loan valuation framework
    • Valuation stress testing.

Today James’s focus is on Insikt Inc., a financial data analytics company that uses data for risk models to apply to consumer markets.  He and his team are working on how to originate loans in the subprime market and how to create a more curated market for securitization – concerned with both bond performance & loan performance.

Panel Discussion, Moderated by Matt Turck, Organizer

  • Banks are encumbered by regulation
  • Alternative lending is only 5% of consumer finance

o   In 5 years we’ll see a lot of new entrants

o   More partnering with banks

  • Transforming the bank system to be more transparent and customer friendly
  • There are four different segments with lending opportunities

o   SMB

o   Consumers

o   US

o   Emerging markets

  • Top ten global institutions will be big players in financial services
  • Rates for consumers can be as low as 6.5%, average 12.5%; for business, 5.9%
  • Rate risk is better through the use of data and marketplace dynamics drive interest rates down
  • A virtuous circle continues to make credit more affordable and drives interest rates down
  • Most credit cards are priced at prime plus
  • Alternative lenders return a higher return to investor
  • Rates rise in a better performing economy and defaults come down so we expect our proceeds to be stable.

How Fred Wilson Sees the Next Ten Years

By Eleanor Haas

Just yesterday, at the LeWeb conference in Paris, VC, blogger and thought leader Fred Wilson identified three megatrends that his VC firm uses as a framework for investing and four areas they’re watching. Things like mobile and big data are technologies that represent too small a lens when it comes to envisioning the big opportunities to come, he said. For him and his colleagues, it’s about adopting a behavioral and societal point of view.
The three trends are networks, unbundling and smartphones, and the four areas are Bitcoin, wellness, data leakage and trust/identity.

1. Networks
We’re very early in the transition from slow bureaucratic hierarchies to technology-driven networks. The hierarchies were solutions of the industrial world, but today they’re obsolete – just plain inefficient. Examples? Twitter replaces the slow-moving bureaucratic news organization that sits behind every newspaper. With Twitter, the crowd determines what’s news, and we get it instantly. YouTube replaces traditional video production. Again, the crowd determines what’s important – and quality rises to the top. SoundCloud disintermediates the music industry by enabling music creators to upload, record, promote and share their sounds to be found by the crowd.
We saw this happen first in media and entertainment, but now it’s happening with hotels (Airbnb), creative services (Kickstarter) and learning (Codecademy).

2. Unbundling.
Cost factors made it desirable to package and deliver products and services in bundles. Now technology makes it cost-effective to deliver focused services a la carte. Examples? Getting sports news from a different source than business news or classified ads. Finding free-standing services once bundled by banks – Lending Club and Funding Circle – asset management, education – where online classes are disrupting the traditional four-year university model – research – where technology enables researchers to collaborate freely as a network – and entertainment – where Netflix, YouTube, Hulu and VHX let us buy shows a la carte instead of having to subscribe to cable.

3. Smartphones
By carrying smartphone, we become always-on nodes in a network. Examples? Uber and Halo are disrupting taxi and limo services, rental cars and delivery businesses. Payment platforms, such as Venmo, Dwalla and Square are phone apps. Tinder is a dating app that leverages location as well as the phone.

Four Areas to Watch

Bitcoin, says Fred, is important as the transactional protocol for the Internet, not as currency. It provides a global peer-to-peer ledger and a technology-based architecture that entrepreneurs can and will build on so that payments, in time, will flow on the Internet like content and images, not controlled by any company.

Health and wellness platforms and tools, not healthcare, will be increasingly important ways to help people avoid the need for healthcare. Examples? Wearing devices that report physical activity and vital signs, a phone device that provides fertility information for women, gamified weight loss initiatives.

Data leakage is Fred’s term for how we allow our own personal data to be open for spying by Google, Facebook and the government while we ourselves have no control over it.

Trust/identity, both of which are closely allied to the data leakage area are currently managed by Google, Facebook, Amazon, Twitter. We give them access to all that we do online. In time, he predicts, there will be a protocol, just like http, that allows us to control our identity, trust and data.

So what areas are you watching? What mega trends seem to you to be significant indicators of what lies ahead?
(You can see the video of Fred’s keynote here. http://bit.ly/1cByjEg )