Archive for the ‘Uncategorized’ Category
It seems to be that time again where we are on the cusp of a shift in internet behaviours and platforms.
I have been noting themes in my reading over the past few months, and two recent pieces in particular solidified them for me. Mary Meeker report, State of the Internet that I referred to a few days ago, and several recent articles by Ben Thompson.
The broad themes are:
1. Chat (as in texting) as an interface.
2. Natural Language Processing (NLP) (as in speaking) as an interface.
If we think about it, these directions are entirely rational especially #1. Over the last 10 years mobile has grown and grown with certain obvious characteristics.
– connectivity by mobile is not always perfect
– web on mobile is spotty especially with ads taking 10% of the screen
– everyone has a phone
– not everyone has a laptop or at least not handy
– the single largest use of mobile is chat – it is low bandwidth, fast, easy and simple.
So if we take the single most used method on mobile, why not make it the interface for other things such as search, shopping and banking. Here is a well explained piece on ChatUI for Banking. Watch for Apple maybe opening up iMessage to Android later today.
Siri has been around for 5 years, and not exactly getting many excited so far. Google/ Android are pressing on this UI now. However Apple have recently purchased a new company which has made express improvements in NLP with better understanding of accents (something I value) and picking out sounds despite background noise.
Enter Amazon Echo and they may have caught everyone by surprise with the Echo. Integrated hardware, speaker, powerful NLP and which has the power of Amazon.com suggests they are on to a winner. It may be a stretch to suggest that Echo killed the Google Nest strategy, but it has to be fair to say the Nest strategy has now been refined to the “Home” strategy, and Amazon Echo success must take some significant credit here. Echo makes a point of differentiating between voices in the home and learning over time. The power of Amazon cloud comes to bear here; once Echo is in the home, that home is now part of the Amazon cloud and both can learn from that. Something that held up Siri is that vehicle use is the only practical one so far. Introduction of Home as a user platform takes voice to a whole new level.
Lastly the drive by large tech towards AI will support both these interfaces, and in fact is a requirement for complete success.
Relevance to Bankwatch:
Watch for Chat and Natural Voice Processing as a user interface that will become prevalent and I would predict will overtake web browsing as the primary access to internet over next 2 – 3 years.
The Mary Meeker annual report is always fascinating and full of facts for the wonks amongst us.
This particular slide pasted below from the 2016 report is one of the better I have seen at quickly summarizing the large generations and their value differences; in particular the financial view of the world which is very different between Boomers and Millennials.
I watch and listed to Google I/O today. The stuff about the new communications app Allo and new emojis was a bit underwhelming but I sensed a deliberate shift under the guidance of SEO Pinchai towards commercialization with the likes of Google Home coming this year. This is going right after the Amazon Echo market, no doubt with a view to address and expand upon the earlier narrow view exemplified by the Nest purchase.
But one comment from Pinchai on “Move 37” came closer towards the end of I/O struck me as prescient with regard to Artificial Intelligence (AI) and that hooked me.
If you want to now more about the status and implication of AI, I recommend this two piece analysis at waitbutwhy. Tim Urban explains very clearly AI using a three level model. If you have any interest in AI, this is a must read. It is neither scary nor technical. It simply and carefully (for our human brains) explains the inevitability and implication of AI:
Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.
AI Caliber 2) Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board—a machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it.
AI Caliber 3) Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board.
Let us return to Pinchai’s reference to
I had followed the AlphaGo vs Lee Sedol Go match series in which AlphaGo won 3 of 4 games. Go is generally accepted as the most complex board game with so many alternative moves as to be almost unlimited. Unlike chess it is not possible to program a series of moves and responses.
During Game 2, AlphaGo made a move at Move 37, that left all the observing experts aghast. So much so that Lee spent 15 minutes considering how to respond.
Move 37 was a move that no human would have considered. It turns out in this analysis at Wired, that AlphaGo had uncovered a move that no human would have considered because it had a 1/ 10,000 likelihood of being deployed, yet AlphaGo realized Move 37 had a high change of success.
It seems to me that in the Urban model AlphaGo may have jumped right over Level 2 AGI (which is yet to be created) and straight to level 3 ASI.
Here is an extract from the Wired Article which I recommend to all.
A One in Ten Thousand Probability
Following the game, in the control room, Silver could revisit the precise calculations AlphaGo made in choosing Move 37. Drawing on its extensive training with millions upon millions of human moves, the machine actually calculates the probability that a human will make a particular play in the midst of a game. “That’s how it guides the moves it considers,” Silver says. For Move 37, the probability was one in ten thousand. In other words, AlphaGo knew this was not a move that a professional Go player would make.
But, drawing on all its other training with millions of moves generated by games with itself, it came to view Move 37 in a different way. It came to realize that, although no professional would play it, the move would likely prove quite successful. “It discovered this for itself,” Silver says, “through its own process of introspection and analysis.”
Is introspection the right word? You can be the judge. But Fan Hui was right. The move was inhuman. But it was also beautiful.
I just made my first Apple Pay transaction at Tim Hortons in Toronto. Very smooth – double press the home button on your locked phone. This has the double effect of unlocking the iPhone, and activating Passbook. Then simply hold over the merchant device to pay.
Despite the naysayers, it is actually easier than debit card tap to pay, because the phone is usually more accessible than debit card, and the activation levers the finger print authentication.
Now we just need more merchants in Canada to accept Apple Pay.
I was pleasantly surprised after a long wait to see RBC add debit and credit card functionality to Apply Pay today. I had lost touch with the Big 5 Canadian Banks efforts to develop a co-ordinated front on Apple Pay but I see now that they must have agreed on something. They are deploying on their own schedules with RBC and CIBC out first.
Here is the RBC page.
And here is my Apple Wallet that I had almost given up on for Canada. Now I have to go and buy a Tim Hortons coffee tomorrow. Hopefully the merchant sign up will get into a different gear now.
P2P Lending held out as a great opportunity to disrupt banking … back in 2006. I was with CommunityLend then, and the opportunity seemed endless. Since then the Canadian regulation stopped P2P lending in Canada.
Meanwhile in the rest of the world the market moved from P2P to “Institutional Lender”2P. Now the Institutional Lender market seems to have dried up. The fact that Lending Club, the most successful P2P lender is increasing their rates in order to attract lenders has a sense of desparation.
This from Finextra.
Prosper slashes workforce as online lenders feel the heat
With Citi recently deciding to stop buying debt from Prosper, the online lender is cutting its workforce by 28%, shutting its office in Utah and slashing jobs in San Francisco and Phoenix, affecting 171 people, according to Bloomberg.
The firm’s CEO, Aaron Vermut, who is reportedly not taking his salary this year, told Bloomberg: “Over the past year we invested for growth, but with the recent tightening of the capital markets we are refocusing on our core consumer loans business and building more resiliency into the company.”
Rival OnDeck Capital is having similar problems. This week it reported that first quarter losses have more than doubled to $13.14 million, sending its stock price plummeting by a third.
The poor numbers are related to an inability to sell off the loans it makes to third parties. In Q1, just 26% of loans were sold to investors, down from 40% in the previous quarter, while the price received for loans also fell.
Next up is Lending Club, which reports first quarter results next week. The firm has seen its share price fall by more than a third so far this year, taking another hit this week as news of its rivals’ travails made the news. Last month it said that it would raise rates on loans in an effort to attract investors – the third time it has done this in six months.
Their annual report is out now. Some useful country specific information regarding customers experience level and feelings about their banks.
Capgemini and Efma today released the findings of their annual World Retail Banking Report (WRBR) 2016. The report reveals that fintech providers are making increasingly significant inroads with customers – two thirds of customers are now using fintech products or services – yet banks are struggling to keep pace, with the vast majority admitting they are not adequately prepared to manage this threat.
Key findings include:
* Not only are a majority of customers now using FinTech products or services, they are also much more likely to refer friends and family to their FinTech provider (55 percent) than to their bank (38 percent)
* 96 percent of banking executives agree that the industry is evolving toward a digital banking ecosystem, where Fintech providers play a much bigger role, but only 13 percent say they have the systems in place to support it
* Fintech providers are perceived among consumers as easy to use (82 percent), offering fast service (81 percent), and providing a good user experience (80 percent)
* While banks improved their customer experience performance, this did not translate into tangible results in profitable customer behavior, with only 16 percent of customers, saying they are likely to purchase an additional product from their bank
* Bank executives favor partnership with fintech firms through collaboration (46 percent) and investment (44 percent) as they look for ways to respond to the threat posed by these emerging competitors
The full report, here: https://www.worldretailbankingreport.com/