Tuesday, May 25, 2010

MasterCard Labs Announcement - is this a new era of Open Data?

Following in my recent series on payment technologies and potential disruptions in the marketplace, there was a very interesting announcement from MasterCard about its new MasterCard Labs (NYTimes article: MasterCard Wants Programmers to Use Its Payment Technology) initiative.

In MasterCard's news release of April 15 (MasterCard Launches MasterCard Labs; Names Garry Lyons Group Executive, Research & Development) and accompanying video (http://www.youtube.com/watch?v=wKa1yy1a0fc) MasterCard reveals plans to open up its payment platform for developers.

The NYTimes article only hints at the immense significance of the MasterCard announcement:
So far, MasterCard has identified about 20 of its services that developers will be able to use in their applications. They include payment technology, bill payment systems and data streams like consumer spending patterns, which could be used to send coupons.
This is significant because it's a response to PayPal's November 2009 announcement to open up its platform to developers (PayPal Seeks New Ways to Use Its Payment System),  allowing developers to embed PayPal in their own apps.

Here's the important aspect: Allowing external developers access to its own data on consumer spending patterns, MasterCard is opening up its data outside its own systems.    Leading platform providers such as Facebook and Twitter already allow access to data and functionality through their API's and have cemented their role as infrastructure providers in the new web....they understand the importance of openness and it sounds like MasterCard does now as well.

Other news here (MasterCard Spending $10s of Millions, Hiring Engineers for its New Labs) points to a new development focus.

Looking forward for financial institutions, will having an open platform be a competitive necessity to ward off disruptive payment technologies from the likes of Square (Square Aims to be Credit Card Value Disruptor)?   Even beyond financial institutions, I would argue that every company should be thinking about its information strategy in a new light and asking the question: "Should we be more open with our data and how can that be a competitive advantage to us?"

If you'd like to explore these ideas further with me, please contact me directly. I look forward to connecting with you!

Alan Wunsche

P.S. Have we connected yet on Twitter? You can follow me at www.twitter.com/AlanWunsche

Tuesday, May 18, 2010

Mobile Payments to reach $633B by 2014

As a follow up to my previous post Square Aims to be Credit Card Value Disruptor, thanks to GigaOM for the following information:
The worldwide market for mobile payments will grow to $633.4 billion by 2014, up from $68.7 billion in 2009, according to a new report by Generator Research. Meanwhile, mobile payment users will grow 600 percent, to 490 million in 2014 from 81.3 million last year. Using your phone or your phone number to exchange money is convenient for everyone but especially the “underbanked.” Whether it’s payment dongle Square launching this week, Zong raising $15 million late last month on the strength of its virtual goods business on Facebook, or the fact that my dinner party companions last night settled the bill usingVenmo, mobile payments are finally part of the present rather than the hazy projected future.
Looking at the report details by Generator Research reveals a treasure of details for business leaders developing plans in the mobile payments arena:


Figure 1: Mobile Subscribers – Worldwide (In Million, 2009 – 2014F)
Figure 2: Mobile Payment Users and Penetration – Worldwide (2009 – 2014F)
Figure 3: Mobile Payment Users – Regional (In Million, 2009 & 2014F)
Figure 4: Mobile Payment Volumes – Worldwide (In USD Billion, 2009 – 2014F)
Figure 5: Mobile Payment Volumes – Regional (In USD Billion, 2009 & 2014F)
Figure 6: Mobile Payment Volumes – Growth by Region (In Percent, 2009 – 2014F)
Figure 7: Mobile Payment Opportunities for Key Stakeholders
Figure 8: How NFC Payments work
Figure 9: Subscribers with NFC Capable Handsets — Worldwide (In Million, 2009 – 2014F)
Figure 10: Penetration of NFC Devices — Worldwide (In Percent, 2009 – 2014F)
Figure 11: Mobile Payment Users — Worldwide (In Million, 2009 – 2014F)
Figure 12: Mobile Payment Volume — Worldwide (In USD Billion, 2009 – 2014F)
Figure 13: NFC Payment Volume — Worldwide (In USD Billion, 2009 – 2014F)
Figure 14: NFC Payment Volume as a Percentage of Mobile Payment Volume — Worldwide (In
Percent, 2009 – 2014F)
Figure 15: Contactless Mobile Payments Services in Japan
Figure 16: DCMX Users (In Million, June 2009 – December 2009)
Figure 17: Consumer Spending Behaviour for Contactless Payments – Japan (2008)
Figure 18: Contactless Payment Trials on NoWcard Buses for Over-the-Air Ticket Sales to NFC enabled
Handsets by the UK’s Department for Transport
Figure 19: Mobile Payment Volume — The US (In USD Billion, 2009 – 2014F)
Figure 20: Micro-payment Opportunities in the US (In USD Billion, 2009)
Figure 21: Basic Value Chain of Mobile Payments
Figure 22: Bank-centric Model
Figure 23: Bank-centric Model – Benefits and Drawbacks
Figure 24: Collaboration Model
Figure 25: Collaboration Model – Benefits and Drawbacks
Figure 26: Operator-centric Model
Figure 27: Operator-centric Model – Benefits and Drawbacks
Figure 28: Peer-to-Peer Model
Figure 29: Peer-to-Peer Model – Benefits and Drawbacks
Figure 30: M-PESA Users – Kenya (In Million, March 2008 – September 2009)
Figure 31: Monthly P2P Transactions Value – Kenya (In USD Million, March 2008, March 2009 &
September 2009)
Figure 32: DCMX Users (In Million, June 2009 – December 2009)
Figure 33: GCASH Users (In Million, 2007 – 2009)
Figure 34: Apple App Store In-app Payments Model
Figure 35: Application Downloads from Apple’s App Store – Performance in the eighteen months
since launch
Figure 36: Drivers and Inhibitors – Mobile Ticketing and Coupons
Figure 37: Major Business Deals and Partnerships – Mobiqa
Figure 38: Major Business Deals and Partnerships – NeoMedia Technologies
Figure 39: Major Business Deals and Partnerships – Cellfire
Figure 40: Mobile Ticketing and Coupons Users — Worldwide (In Million, 2009 – 2014F)
Figure 41: Mobile Ticketing and Coupons Volume — Worldwide (In USD Billion, 2009 – 2014F)
Figure 42: Basic Value Chain of Mobile Ticketing
Figure 43: Mobile Ticketing – Business Model I
Figure 44: Mobile Ticketing – Business Model II
Figure 45: Basic Value Chain of Mobile Coupons
Figure 46: Mobile Coupons – Pay per Redemption Business Model
Figure 47: Increase in Revenue of Go North East (In GBP Million, 2006 – 2009)
Figure 48: Go North East’s Contribution to Go-Ahead’s Bus Revenue (In Percent, 2005 – 2009)
Figure 49: Benefits of Planet Funk’s mobile coupons campaign
Figure 50: Mobile Payment Volumes – Regional (In USD Billion, 2009)

LIST OF TABLES

Table 1: Regional Break-out of Mobile Payment Users (In Million, 2009 – 2014F)
Table 2: Regional Break-out of Mobile Payment Volume (In USD Billion, 2009 – 2014F)
Table 3: Regional Drivers – An Overview
Table 4: Challenges for Different Mobile Payment Platforms
Table 5: Assessment of Challenges for Different Mobile Payment Platforms
Table 6: Regional Challenges – An Overview
Table 7: Comparison of Mobile Payments Business Models
Table 8: Top Applications with In-app Payments available from Apple’s App Store (November 2009)
Table 9: Opportunities and Benefits of Mobile Ticketing and Coupons for Stakeholders




If you'd like to explore these ideas further with me and make sure that your company is ready for this next wave of business intelligence, please contact me directly. I look forward to connecting with you!

Alan Wunsche
alan@wunsche.com

P.S. Have we connected yet on Twitter? You can follow me at www.twitter.com/AlanWunsche

Tuesday, May 11, 2010

Square Aims to be Credit Card Value Disruptor



This is an update to my initial blog post (April 7, 2010): Is Square the Bank of the Future?

Today (May 11, 2010), Fast Company has published: "Square Brings Credit Card Swiping to the Mobile Masses, Starting Today"

I highly recommend this article and the accompanying article "Getting Square: A Guide to the New Mobile Credit Card Payment System for iPhone and Android" to better understand Square's business model.

Here are some highlights:

With Square, anyone can accept credit or debit card payments by downloading the app and plugging a little plastic cube into the headphone jack of an iPhone, iPod Touch, iPad, or Android phone. After a quick swipe of the card through the reader, the merchant turns the device over to the customer to sign his or her name on the touchscreen using a finger instead of a pen. The customer can add a tip, either by percentage or a particular amount, and then enters their phone number or email address. In the best case, the receipt message will buzz in the customer's pocket as an email or SMS text message while walking away with their purchase.
Customers are charged as usual by their banks or credit card companies, and Square settles up the net funds with merchants each night instead of at the end of the month. The swiper and application are both free and include access to an online dashboard with analytics that help merchants track exactly what they've been selling.
Square shares very little about you with the merchant, and doesn't even keep your credit card number on file. Although a phone number or email address is needed for the transaction, that is not shared with the merchant, only with Square. [Alan: Square can therefore become a CRM service provider] 
At the same time, Square gives the merchant just enough to recognize repeat customers and offer them incentives. In the dashboard, a merchant can customize a notifier for, say, every tenth visit by the same customer or any time a customer spends more than $100. This notification will appear on screen after the swipe and allow the merchant to offer a discount or giveaway. [Alan: Square can enable loyalty]

Friday, May 7, 2010

Did the Machines Take Over the Stock Market?

Dow Jones Industrial Average (May 7, 2010)
Business analytics as a core process in financials services is quickly being transformed into automated decisioning as the power and ubiquity of computing is increasing.

There are obvious benefits but there are also risks, as we saw in yesterday's stock market plunge.

In today's (May 7, 2010) NYTimes, the article "Surge of Computer Selling After Apparent Glitch Sends Stocks Plunging" states:


"The glitch that sent markets tumbling Thursday was years in the making, driven by the rise of computers that transformed stock trading more in the last 20 years than in the previous 200." 

The old system of floor traders matching buyers and sellers has been replaced by machines that process trades automatically, speeding the flow of buy and sell orders but also sometimes facilitating the kind of unexplained volatility that roiled markets Thursday.
“We have a market that responds in milliseconds, but the humans monitoring respond in minutes, and unfortunately billions of dollars of damage can occur in the meantime” 


 It will be important to get to the root cause of this near disaster but this quote would cause anyone concern:
"The source remained unknown, but that jolt apparently set off trading based on computer algorithms, which in turn rippled across indexes and spiraled out of control."
For a short while, traders started to distrust what they were seeing.
“There was no pricing mechanism,” Mr. Clancy said. “There was nothing. No one knew what anything was worth. You didn’t know where to buy a stock or sell a stock.” 

Did the machines really take over?


Alan Wunsche
alan@wunsche.com

Wednesday, May 5, 2010

Can Google's "Recorded Future" Help Predict the Future?

Timeline view of news about man-made disasters in Thailand
While it's been said that you can't predict the future, there's no denying the holy grail for business is to predict the most likely future scenarios and to provide the business with strategic flexibility that will anticipate a variety of possible outcomes.  Software vendors such as SAS and Cognos provide predictive analytics tools and the explosion of data analytics will fuel demand for these solutions. 

Not content to just knowing everything about the past, Google Ventures recently announced an investment in startup company Recorded Future.

According to Google, "Recorded Future extracts time and event information from the Web. Recorded Future offers customers new ways to analyze the past, present and the predicted future."

The company explains it this way:
"At Recorded Future, we compute a momentum value for each entity and event in our database," one blog post explains. "The momentum value indicates how interesting a certain event or entity is at a particular time, and is continuously updated. In computing the momentum value, we take into account the volume of news around an entity or event, as well as what sources it is mentioned in, what other events and entities it is mentioned together with, and several other factors.
"The momentum measure is used to present the most relevant query results in our web user interface, but it can also be analyzed using statistical methods to predict possible future changes in momentum, which in turn can be valuable, e.g. for trading decisions."


It's too early yet for Recorded Future and any predictions that Google will become the next SAS, but this kind of tool will inevitably make its way to scenario planning for big business.

If you'd like to explore these ideas further with me and make sure that your company is ready for this next wave of business intelligence, please contact me directly. I look forward to connecting with you!


Alan Wunsche
alan@wunsche.com