Category: Digital Disruption

It’s not every day that I feel the need to fight with Martin Wolf. The Financial Times commentator is an eminently respectable analyst and most of the time makes good sense. However, last week he sort of lost the plot.

Mr Wolf has written that technology will do to finance what it has done to media, taxi companies and hotel rooms. The financial version of Twitter, Uber and Airbnb will soon emerge, taking on banks which are – his words – inefficient, costly, unethical, untrustworthy and prone to threaten global economic stability to boot.

At the end of the day, said Mr Wolf, finance is an information business. All information industries have been transformed by the internet of everything. Ergo, so too will finance.

The vision is enticing, holding forth the promise of a day when money will be democratised and flow without friction through the system. A day when bank scandals no longer make headlines, because banks themselves will be automated platforms owned by their users and not corporations owned by their shareholders.

But this vision is also unrealistic. To understand why, we need to remind ourselves what the financial sector is, and what it is not.

Contrary to Mr Wolf’s assessment, finance is not an information business. Information is important in the industry, but not its core offering. Rather, we can think of finance as a warehousing business. Bank warehouses hold mainly deposits and loans. Fund managers hold assets such as shares and bonds. Insurance companies warehouse assets against the insurance liabilities they underwrite.

It is often the case that financial firms are required to warehouse their products for a very long time. They need to ensure that they do so properly, and that their customers are aware of the risks the products entail. If the job is done correctly – and clearly that is not always the case – then financial firms collectively support economic activity by transforming savings into capital (and loans), providing liquidity to the market and helping households and firms mitigate their financial risks.

In Australia, this is huge business. The Big 4 banks together hold over A$2 trillion of financial products on their balance sheets. There is more than A$2 trillion of assets in the superannuation system (some of which is also held by banks). The three largest general insurers in Australia hold nearly A$200 billion on their balance sheets, and the list goes on.

Around this core set of financial products, financial companies offer a whole lot of services. These include the things we use every day such as PayPass, international money transfers, account verification, share trading and automatic billing. They also include activities we don’t like to think about so much, such as disputed credit card transactions, property damage payouts, security against cyber hacking and a 30-year guarantee of a payout upon death.

When fintech startups first entered the system, they focused on offering new financial services rather than products. Examples include companies like PayPal – no longer thought of as a start up – which introduced a better, cheaper and more convenient payment platform to the United States that allowed individuals and businesses to transfer payments to each other nearly anonymously.

PayPal still relies, however, on the credit cards and bank accounts of its customers. That very traditional financial system – guaranteed by highly regulated bank balance sheets – provides confidence that the buyer has an account with funds that can be received and then held by the seller’s account.

More recent examples of new fintech entrants in Australia include the many firms deploying blockchain technology in a distributed ledger system (CoinTree, CoinLoft) or using big data sets and algorithms to shorten loan approval times from days or weeks to less than 10 minutes (Kikka, Nimble). These are welcome innovations in the financial ecosystem, and are disrupting the way in which banks engage and interact with their customers in terms of the services they provide.

But at either end of this transaction, more often than not, there will be a bank sitting with a balance sheet to warehouse the payment or the loan in a way that the customer can be certain that their money will be safe over time.

Consider this against the model of Uber or Airbnb. These are outstandingly successful companies in the “sharing” economy, where individuals with something small and personal to sell are able to make that offer via a safe and secure platform and where customers can feel confident that the product will meet their requirements. Uber and Airbnb have successfully disrupted the old warehousing businesses model of taxi companies and hotels.

So why couldn’t the same be true in finance – a sharing platform that renders the financial warehouse obsolete? The main reason is in the nature of the product itself. First, financial products – money – can lose value if stored for a long period of time. That can be risky, particularly for people with low levels of financial skills or literacy. Booking a single Uber ride where the transaction will be completed in 30 minutes is low risk, even if the driver is bad or doesn’t turn up. Paying $1,000 now to book that specific driver for 20 rides scheduled to take place in 2025 is a different kettle of fish. Will the $1,000 still buy the same number of rides and will the driver accept the currency on offer?

Second, money is fungible. It is much easier to steal than, say, a hotel room. To reduce the risk of fraud and misappropriation of funds, financial regulators impose huge requirements on financial firms to verify that transactions are legitimate. This creates friction in our financial system – eg, slows down the pace at which we might otherwise undertake financial transactions. Humans have been experimenting with the “right” level of friction in the financial system ever since the time of the Medicis, and arguably we have yet get the balance right. One thing we know, however, is that a frictionless financial system would carry huge risks. In fact, it would be downright scary.

The closest concept to a frictionless, shared, Uber-like company in the world of banking is peer-to-peer and crowdfunding lending platforms. This is a credit-sharing model, where individual lenders can make their household savings available and attract higher rates of return on a platform that pools their funds into loans for people who are willing to borrow off that platform. One benefit of borrowing off a platform can be the potential for lower interest rates based upon a wider set of information (such as mobile phone payment history for example) that may allow borrowers to access more favourable interest rates.

This is a welcome development, albeit with limitations. There are commercial banks in the US and UK that now utilise peer-to-peer providers to find customers in much the same way that professional real estate firms have invaded the online shared property rental market. More worryingly, predatory lending and usurious interest rates are not the sole domain of established players, and commentators are suggesting that some elements of the PtoP market in the United States may be starting to resemble the subprime market of the noughties.

The potential emergence of high-risk lending in the PtoP space – and, for that matter, evidence of unsavoury actors exploiting the anonymity of digital currency – is a reminder as to why the financial sector remains one of the most heavily regulated in world.

Rather than “replacing” banks or other traditional financial firms, fintech start-ups seem to be developing a symbiotic relationship, utilising the balance sheets of established players while disrupting and in many ways improving the customer interface – the ways in which people and businesses engage with their money.

Last week, the headline from ANZ that it was poaching Maile Carnegie from Google to run its digital banking service captured the zeitgeist. Are banks now tech companies? The answer is no, not really. But they are looking to technology to better serve their customers. And that is something we can all agree is a good thing.

Author: Amy Auster, Executive Director, Australian Centre for Financial Studies

Last year Deloitte Access Economics reported the sharing economy contributes about A$504 million a year to the New South Wales economy, with about 45,000 people earning an income from the different platforms like Lyft and Uber for ride sharing, and Airbnb for accommodation.

In the initial phases of their introduction, these platforms provided good money for providers, much to the annoyance of heavily protected suppliers such as the “official” taxi industry. Some taxi drivers actually switched to Uber in the hope of greater incomes.

Though not as widespread as in the United States, activities in the sharing economy in Australia include many services such as house-sitting, car sharing, bike sharing and IT services.

But for those in the “gig economy” there is evidence emerging that markets for services like Uber and Airbnb are becoming saturated. Expectations on income prospects are being lowered.

Recently in Brisbane and on the Gold Coast, some Uber drivers have complained of making less than $A10 an hour after deducting GST, personal income tax, car and phone expenses and Uber fees from their fares. This compares to the minimum wage of A$17.29 which, although subject to income tax, is greater than the drivers claim they are getting from Uber. The company also announced it was scrapping guaranteed hours) for drivers after their first four weeks in the service.

As the profitability of activities falls we will likely see a drop in people working through these platforms or offering services. For us economists these developments are hardly surprising. As we say in Essentials of Economics: “If everyone can do it, you can’t make money at it.” By this we mean that in markets which are competitive with relatively easy entry and exit, suppliers can’t expect to make above the average return for long. In this case that means earning above the average wage, or for the less skilled, the minimum wage or even unemployment benefits. If activities are profitable then people will enter the market and drive down prices.

Everyone can do it

There are few markets that have easier entry and exit than those in the sharing economy. Anyone with a car (which is most people) can become an Uber driver. Anyone with a spare room can offer it on Airbnb. The same goes for house-sitting, car sharing and most of the other services now available in the sharing economy.

Also, the price which suppliers are willing to accept will be determined by the value of the alternative uses of their time, room or other asset they are “sharing”. So a person who has a regular job and finds it convenient to spend an hour or two of otherwise idle time, might be content with a relatively low payment from Uber. But such an hourly rate for a driver relying on Uber for a living might not.

A person who has an empty room in their house might find even a relatively low payment is better than nothing at all. But if you relied on income from the room to make a sizeable contribution to the household budget you might find Airbnb a rather unattractive proposition.

The lesson in all this is that markets will adjust to a price where people are just deciding whether to undertake the activity or not and many will be unwilling to take part at this price. The big profits to be made are in the firms which bring buyers and sellers together, usually through app-based methods. But even here these profits are subject to serious competitors not being able to enter the market.

All of these factors explain why the sharing economy has really taken off in the United States where minimum wages are low and social security payments (both the level of payment and accessibility) are relatively poor. In a country such as Australia which has relatively high wages in “mainstream” employment (even at the minimum wage) and relatively generous social security it is doubtful if for most, the sharing economy will ever compete with a full-time job as an attractive proposition. But then again, the very point of the sharing economy is that it is a part-time, somewhat casual activity compared to the “mainstream” economy.

Author: Phil Lewis, Professor of Economics, University of Canberra

“22 of the Cutest Baby Animals,” the headline said. “You won’t believe number 11!”

Despite an impending deadline – not to mention my skepticism (how cute could they possibly be?) – I clicked on the story. I’m only human, after all. Yet this failure in self-regulation cost me at least half an hour of good work time – as have other clickbait headlines, bizarre images on my Twitter feed or arguments on Facebook.

The insidious, distracting suck of the Internet has become seemingly inescapable. Calling us from our pockets, lurking behind work documents, it’s merely a click away. Studies have shown that each day we spend, on average, five and a half hours on digital media, and glance at our phones 221 times.

Meanwhile, the developers of websites and phone apps all exploit human behavioral tendencies, designing their products and sites in ways that attract our gaze – and retain it. Writing for Aeon, Michael Schulson points out:

Developers have staked their futures on methods to cultivate habits in users, in order to win as much of that attention as possible.

Given the Internet’s omnipresence and its various trappings, is it even possible to rein in our growing Internet consumption, which often comes at the expense of work, family or relationships?

Psychological research on persuasion and self-control suggests some possible strategies.

Tricks for clicks

It’s important to realize some of the tricks that Internet writers and web developers use to grab our attention.

The strange number 22 in the headline is an example of the “pique” technique. Lists are usually round numbers (think of Letterman’s Top 10 lists or the Fortune 500). Unusual numbers draw our attention because they break this pattern. In a classic study, the social psychologist Anthony Pratkanis and colleagues found that passersby were almost 60 percent more likely to give money to panhandlers asking for US$0.37 compared to those who were asking for a quarter.

People in the study also asked more questions of the panhandlers who requested strange amounts, compared to those who begged for a quarter. The same thing happened when I saw the headline. In this case, the skepticism that caused me to ask the question “How cute could they possibly be?” backfired: it made me more likely to click the link.

An attention pique (such as asking for $0.37 or calling out photo #11) triggers us to halt whatever we’re doing and reorient to the puzzle. Questions demand answers. This tendency has been dubbed by psychologists as the rhetorical question effect, or the tendency for rhetorical questions to prompt us to dig deeper into an issue.

These tricks exploit built-in features of our minds that otherwise serve us well. It’s clearly advantageous that unexpected stimuli capture our attention and engage us in a search for explanation: it might stop us from getting hit by a car, or alert us to sudden and suspicious changes to the balance in our bank account.

So it wouldn’t make sense to turn off that kind of vigilance system or teach ourselves to ignore it when it sounds an alarm.

Binding ourselves to the mast

Content on the net isn’t only designed to grab our attention; some of it is specifically built to keep us coming back for more: notifications when someone replies to a posts, or power rankings based on up-votes. These cues trigger the reward system in our brains because they’ve become associated with the potent reinforcer of social approval.

Not surprisingly, Internet use is often framed in the language of addiction. Psychologists have even identified Problematic Internet Use as a growing concern.

So what can we do?

Like Odysseus’ strategy for resisting the temptation of the sirens, perhaps the best trick is to commit ourselves to a different course of action in advance – with force, if necessary.

Odysseus had his men tie him to the mast of their ship until they were out of the sirens’ range. This is an example of “precommitment,” a self-control strategy that involves imposing a condition on some aspect of your behavior in advance. For example, an MIT study showed that paid proofreaders made fewer errors and turned in their work earlier when they chose to space out their deadlines (e.g., complete one assignment per week for a month), compared to when they had the same amount of time to work, but had only one deadline at the end of a month.

The modern-day equivalent of what Odysseus did is to use technology to figuratively bind oneself to the mast. Software packages such as Cold Turkey or the appropriately named SelfControl allow you to block yourself out from certain websites, or prevent yourself from signing onto your email account for a prespecified period of time.

Researchsupports the reasoning behind these programs: the idea that we often know what’s best for our future selves – at least, when it comes to getting work done and staying free of distraction.

Coming out with your commitment

If you really must win a game of chicken, the best way is to accelerate to top speed, remove the steering wheel and brake from your car, and throw them out the window – all in view of your opponent.

In a less dramatic fashion, precommitments can be much more effective when they’re announced in public. Researchers have found that people who publicly commit to a desired course of action such as recycling or being sociable are more likely to follow through than people who keep their intentions private. We are deeply social creatures with a fundamental need to belong, and publicly declaring a plan puts one’s reputation at stake. Between the social pressure to live up to expectations and any internal sanctions we self-impose, public precommitment can be a powerful two-pronged attack against self-control failure.

More and more, scientists who study self-control are starting to see tools such as precommitment and software that blocks out websites not as “hacks” that circumvent the system but instead as integral pieces in the self-control puzzle.

For example, a recent study tracked the everyday lives of a large sample of people on a moment-by-moment basis, asking them questions about their goals, temptations and abilities to resist them.

Contrary to expectations, the people who were generally good at self-control (measured with a reliable questionnaire) were not the best at resisting temptations when the temptation presented itself. In fact, they were generally pretty bad at it.

The key is that self-control and resisting temptation are not the same thing. Odysseus had one, but not the other.

Instead, good self-control was characterized by the ability to avoid temptations in the first place. We often think of self-control as the ability to white-knuckle our way through temptation, but studies such as this one indicate that self-control can also be as simple as planning ahead to avoid those traps.

The next time you need to get something done, consider precommitting to avoiding the Internet altogether. Like Odysseus, realize that if you find yourself facing temptation directly, the battle may already be lost.

Author: Elliot Berkman, Assistant Professor, Psychology, University of Oregon