Diagram - ongoing down and upspikes in perception of the topic of Fraud for various banks
No sooner do we do some research on the problems of retail banks managing perception (using our own DataSwarm analytics suite
, natch) and find that the Challenger Banks/Fintechs will not be immune, than the proof comes down thick and fast on one Challenger's head (Revolut).
In a few short days they have suffered bad publicity over parts of their system's issues re money laundering tracking
, their uber-culture
, and their App not working.
Our research had shown that overall, the "Challenger banks" like Revolut had better customer perception overall, for a number of reasons (seehere for the relevant blog post
). At that point it was only the Traditional retail banks that were being hit by negative stories, due to ongoing complex operations and old bad news continually resurfacing - a factor we call "perception drag
". You can see this on the diagram at the top of the page, its those big downspikes. However, we also wrote (to quote the report):
These types of issues do not yet impact the Challenger banks, but we would suggest that this is currently because they haven’t been around long enough. It is yet to be proven that they will not fall into these sorts of policy errors and PR gaffes over time.
No sooner had we finished the report and turned the trackers off than Revolut fell into one mess a few weeks ago
, and now all this.
Fortunately, not all is bad news. If you look back up the diagram, there is an interesting effect if a bank chooses to try and adress these issues - again from the report, look at two of the spikes:
• October 27th – Lloyds faces probe alongside KPMG over HBOS possible fraud a decade ago
• November 14th - Lloyds shortlisted for an award for anti fraud detection system
Being seen to try and fix he things that go wrong is a good antidote to the downspikes. What we also know' from our work experience with cients is that not only the devil, but salvation, is in the details - the report again:
Digging down to the next levels [in the perception data] reveals which specific factors are causing positive and negative impressions, when, and why, for each issue. At that point it becomes possible to attempt to optimise perception from an informed base.
Our experience is that the impact of perception on sales and service can change market structure over time, but is not well understood, especially the effect of service on future sales. It is an opportunity for most companies to improve on significantly.
And one last crumb of comfort - in matters of publicity, to quote Wilde, "the only thing worse than being talked about is not being talked about...."
The DataSwarm report "Retail Banking in the Fintech Age" is available here
An ode to the digital comminications technologies of our times, and the wannabe influencers who infest them:
Go with rage into the noise and haste, and remember there is no value in silence. As far as possible never surrender the mike, get your opinions out to all other persons.
Speak your truth loud and often, to all the others, they are mostly dull and ignorant and they need to know they are wrong.
Override quiet and thoughtful people, they are impediments. Compare yourself with others frequently, ignore those lesser than you as they are a waste of effort, and suck up to those still better than yourself.
Trumpet your achievements, and broadcast your plans. Focus on your own career, don’t be humble, this is your way to make your fortune.
Exercise duplicity in all your business affairs, there is one born every minute. Do not be blind to virtue, idealism or quiet heroism, there is always a way to use those suckers.
Be You, but feign whatever you must to get what you want. Especially feign affection, the losers always fall for it as they are continually seeking love, and anyway they are used to falling on their arse.
Resist the counsel of the years and try and look as young as you can. Nurture a feeling of self-worth to get you over misfortunes, and ignore any dark imaginings, fear is for wimps.
Have a good workout discipline, and always forgive yourself anything. You are a master of the universe, much more than the trees and the stars, it needs you to be here.
Labour and aspire to create noise and bustle in life, peace is for the meek souls. It’s a beautiful world despite all the drudges and dreamers, so don’t worry about anyone else, be happy.
Note to self. Take 2 frog pills, eschew social media, and see if someone will sell you one of those devices that splats mobile phones on trains....
(With grovelling apologies to Desiderata)
To say that blockchain is overhyped is to put it mildly - not a day goes by without some pundit proclaiming that industry X will be transformed by it. Most of this is speculation, based - as far as I can see - on little understanding of the technology or the viable alternatives. For most proposals, somewhere between the hype and heuristics is a major disconnect.
This post is not going to go into the ins and outs of blockchains, but will just point out the basics of what defines whether it will transform Industry X (this post summarises a more detailed article I wrote
last year - go there for the more tech stuff - in our preparation for the blockchain work last year for helping to run the London part of Global Legal Hackathon.
In short, its all about ROI on the transaction costs..... in essence blockchain technology (as designed today) is great if you want transactions that are:
secure (ish - the overall flowchain of a blockhain system has shown itself to be prone to all the standard hacking problems),
no trusted 3rd party (TTP).
But, owing to the high calculation load to be secure/resilient/not require a TTP, for blockchain to work it also needs transactions to be:
relatively low volume (c 6 a second for Bitcoin for eg)
not particularly time sensitive (hours, or even days to complete the agreement between nodes)
relatively high transaction value - as these calculation loads massively increase the blockchain transaction cost.
This is captured in the 2 x 2 matrix above - there is only one "sweet spot" square for blockchain, that where the value and rate of transaction flow makes blockchain a useful solution. So for applications that are:
High volume, Low value - blockchain is a lousy solution in every single way unless the need for the secure/resilient/TTP overrides everything.
High Volume, High Value - the value means blockchain transactions cost in, but the high volume and resulting time lags will probably break the system or render it useless for most cases
Low volume, Low value - can cope with the volume, but unless the need for the secure/resilient/TTP overrides every consideration, or one is prepared to fund the transaction in another way (VC stump money, subsidies, indirect gains) there are far better approaches around today.
Low Volume, High Value - this is the sweet spot - transaction values make it economic to use, volumes don't break it.
Worryingly, for a lot of mooted applications there is not a hope in hell that Blockchains (in their current forms), will be fast enough or cheap enough to work. To be fair, there are now more and more blockchain approaches entering the market, but there is always a trade-off of speed and/or secure processing. Here is what is more likely to happen in most cases:
1. For most non "sweet spot" blockchain applications there are existing, cheaper, faster “Good Enoughs” today. There will nearly always be an alternative case to employ more scalable/lower cost/faster performance blockchain system designs with:
Less distributed architecture to scale it for speed and cost
Less complex security in the blockchain to reduce the processing load time and cost
2. This will probably be done by implementing them as “private and much less distributed” systems behind IT datacentre security walls, ie “Walled Garden” blockchains will very probably put themselves in the position of the TTP supplier. (This is what is in fact happening today, I first saw this predicted in 2015 by Dinis Garda looking at IoT outcomes).
Which of course negates a lot of the theoretical benefit of the Blockchain idea itself.....
For the last day or so Revolut Bank (or more accurately, non-bank) has been in trouble
with data privacy advocates, singletons, vegans, users and now possible even the regulators
For the new "Challenger banks" this is a very bad idea.
We have been researching perceptions of Challenger Banks vs Traditional Banks from October 2018 to January 2019, but in a nutshell, perception matters for capturing and retaining customers, especially in an age when 90%+ of people go online for recommendations.It also matters more for the Challenger banks, who don't have large service portfolios - so they need to be seen to be really, really excellent at what they do. Implying they spy on their users to the extent the regulator is interested (never mind the rest of the fallout) is a bad idea.
Revolut have not done as well in the perception stakes as their main competotor, Monzo - another Challenger bank - as the chart above shows (the faster the rise in the line, the better), their perception is lagging and is not much better than the Traditional banks, with all their history dogging their steps. This latest episode is not going to help (and may well point to deeper issues)....
More analysis on the DataSwarm site over here
This is a summary of a more detailed post over here
on our DataSwarm company site:
We have been tracking Brexit (the British Exit of the EU) for about a year now using our DataSwarm systems, as a side project to test our system’s predictive analytical capabilities (we predicted the Brexit referendum correctly all those years ago, as well as quite a few other “surprise result” elections since – see here for more details
One of the more interesting features of Brexit has been the fate over the last 9 months or so of the one of the most high profile and flamboyant politicians in the Pro Brexit camp (the "Brexiteers"), one Alexander Boris de Pfeffel Johnson, better known as Boris Johnson, or just “Boris”.
To recap for our non-UK readers, Boris was one of the main personalities in the Leave Europe campaign leading up to the Brexit referendum vote, but - after David Cameron (the Prime Minister at the time) resigned the morning after the unexpected result to Leave came in. Boris exited the ensuing tussle for Prime Minister, and Theresa May won the internal Tory Party election and then scraped back in as Prime Minister after (just) winning a General Election.
At any rate, post these elections Boris again threw himself into the task of championing the Leave cause, and from the get-go captured a very large amount of the UK mindshare around the Brexit arena. Chart 1 shows his prominence in March this year.
Chart 1 – Zeitgeist Chart for Brexit, March 2018
But a week is a long time in politics, and 9 months is an eternity, and when we look at the same chart of the memetic heavens now, his blob is not nearly as prominent.
Chart 2 – Zeitgeist Chart for Brexit, December 2018
So what has happened? An examination of the opinion and idea sub-streams underlying Brexit overall over the intervening months points to 3 main causes:
The actual process of the negotiation has risen in the overall mindshare as March 29th 2019 approaches
Others have actively started to make more running as That Day draws near
The “Boris Camp” has been changing tack over recent months, and going for Gravitas. The shift has been to adopt a more serious, thoughtful, dare one say Leader-like approach
So, watch this space. Or better still, come back and watch us watching this space.
A short note on what the DataSwarm system does
The DataSwarm Analytic Engine tracks opinions and ideas from social and other media. It registers their rise and fall in the mindshare of groups of people (this change over at any time what we call the Zeitgeist), whether of large groups like the British population, or smaller subgroups (for example cosmetics users, whisky drinkers, online TV consumers, bitcoin buyers and various other client projects). Just to make it more interesting (i.e. complicated), large groups comprise of smaller groups each with varyingly different idea and opinions sets. We also track how these varying idea sets combine, split, recombine and generate new Zeitgeists in different subgroups. It’s fairly complex analytics, but very powerful – hence our ability to predict elections that surprise all the pollsters, pundits and politicians. See here for more
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