Tobias Baer shares an article that questions the current, popular credit strategy of instant gratification with delayed payments.
Buy-Now-Pay-Later (BNPL) is hot – and that makes it increasingly controversial, as it was made clear by Monday’s article in the Financial Times. Retailers love it as a way to increase sales, FinTechs as a way to build new, appealing lending propositions. But from a consumer’s perspective, is it good or evil?
The question whether BNPL is good or evil obviously would inform the regulatory stance as to what extent it should be regulated and even curtailed. Nevertheless, I believe that it is the wrong question. Very often, not least when it comes to regulating the financial industry, we pretend that the product is the problem. What if the problem is the consumer – or more precisely, the consumer choosing the wrong product? In the following, I will briefly argue the good and bad sides of BNPL before suggesting a better approach for regulating financial products.
Good arguments exist to let BNPL prosper
In the ideal case, BNPL creates a clear and positive effect for consumers. For some, BNPL allows to get the benefits of a certain acquisition earlier (e.g., the earlier you upgrade to a safer motorbike helmet, the lower is the risk of a debilitating injury). There even can be a good business case to use BNPL for certain groceries (e.g., it can enable a cash-strapped family to save money by buying certain items in bulk even though the family needs 100% of its current income to feed itself).
Key points include:
- Regulations curtailing access to BNPL
- Four reasons why some view BNPL critically
- A better approach to regulating consumer finance
Read the full article, Is Buy-Now-Pay-Later Good or Evil?, on LinkedIn.
Tobias Baer takes on the role credit bureaus play and misguided government prescriptions in this post.
Credit bureaus are both feared and loathed – feared because their revealing of “sins” of the distant past can dash many a dream such as buying a house or a car, renting a flat, or even just getting a postpaid mobile plan, and loathed because their verdict on an applicant sometimes appears unfair or even incomprehensible – e.g., when sensibly taking up an interest-free “Buy Now, Pay Later” offer from the likes of Karna causes the credit score to fall rather precipitously.
On the upside, there is therefore much to be improved (in the US and many other markets) – ranging from the trivial (such as better protection from plainly wrong data and identity theft) to the visionary (such as eliminating racial and gender-based discrimination perpetuated by credit scores). On the downside, the role credit bureaus play with regard to these problems is poorly understood, and hence many prescriptions discussed by politicians and the media are misguided and at times outright dangerous. Beware the unintended consequences! Recent years have seen a lot of innovation and movement in the credit reporting agency industry. Across the globe, credit bureaus have been adding additional, non-traditional data sources and sought to provide scores also for unbanked customers and new applications (such as predicting likelihood of returns for online shoppers). The IPO of Credit Bureau Asia Ltd in Singapore last year (up 46% since) and FinTech start-ups such as Nova Credit and Credit Kudos remind us of the growing potential for profits to be made in the space.
Key points include:
- How to ensure high data quality
- Reporting positive or only negative data
- Fighting racial and other discrimination
Read the full article, Joe Biden could improve credit bureaus for real – here’s how, on LinkedIn.
Tobias Baer draws attention to the danger of selective perception becoming the norm as the use of AI in online information and marketing limits the amount of information delivered.
There is a famous psychological experiment where participants intently watch a basketball game – but when asked afterwards about the gorilla that had danced around amidst the players, nobody has seen it. It’s the literal textbook example of selective perception – in this experiment, participants were tasked with counting the number of passes between the players and as they focused all their attention on the ball, their minds completely disregarded everything else going on on the court.
If you think of selective perception as a curtain that is partially drawn on our minds, thus narrowing our window into the world, AI is pulling more curtains from every side, leaving only a dwindling beam of light. If we don’t actively manage this and make sure we get enough exposure to mental sunlight, we risk making increasingly poor decisions and falling prey to manipulation by marketers. In the following, I will quickly describe how selective perception affects our beliefs and actions before reviewing some of the recent innovations in how AI is used that worry me for what they could do to our perception.
Our own selective perception is technically necessary but also a key way how our personality manifests itself. You all will have met anxious people who seem to always only see the risks of a proposal, or helpless optimists who seem to be blissfully blind to any risks or downsides.
Key points include:
- Facebook’s acquisition of Kustomer
- GPT-3, a language prediction model
- Side-tracked cognitive processes
Read the full article, How AI closes the curtain on human perception, on LinkedIn.
Tobias Baer shares an article on the latest Google news and the regulation of Big Tech. He explores the impact of Google’s algorithms on e-commerce and the commercialization of the internet.
In spite of its limited scope, the DOJ’s antitrust complaint against Google already highlights three fundamental issues of e-commerce and the commercialization of the internet. The first is about industrial organization – how to create a digital market structure that isn’t monopolized through natural network and scale effects? The second issue is the bundling of services especially in areas where due to information asymmetry, consumers don’t see the true cost of their decisions (as they pay with their data) and hence are highly vulnerable to exploitation. The third issue is the important role of design as a key trigger of human behavior – an aspect where governments still are playing catch-up with the latest insights of psychology and behavioral economics.
Before offering two specific solutions to the problem, I want to briefly explain these three issues.
Monopolization of e-commerce
The DOJ’s allegations of anticompetitive behavior is the latest evidence that the internet, rather than democratizing seller and buyer relationships and giving more power to consumers by getting rid of the “middle man”, has enabled the creation of powerful new quasi-monopolies. Such creation of dominating platforms is driven not only by network effects (e.g., just as we benefit from everyone speaking the same language, it also benefits us to communicate through the same channel or app) but also because of an inherent need for risk management, as I’ve argued in an earlier article. I learned already in Industrial Organization 101 that in such situations regulations need to create a market structure protecting a balance of forces between sellers and buyers – sadly my teacher did not explain exactly how to do this for the internet (which back then was in its infancy)!
Key points include:
- The high cost of bundling
- The psychology of design
- A regulated code of conduct
Read the full article, What Google’s antitrust lawsuit means, on LinkedIn.
Tobias Baer tackles the issue of payment fraud, credit fraud, and money laundering and explains how the universal payee ID can reduce losses. He identifies how fraud schemes are enabled by and benefit from weaknesses in most banking and payment schemes around the world.
One of the most amazing aspects of working in many different countries is the realization that a few countries have the perfect solution for a problem that costs most other countries literally billions of dollars. One of these things is the universal payee ID. It could massively reduce payment fraud and credit fraud losses and seriously hinder money laundering.
As I’ve discussed in the past, today we face the problem that banks are very much left to their own devices in confirming the purported identity of a customer or counter party. This causes three big problems.
The problems and solutions identified in this article include:
- Payment systems
- Unique IDs
- Biometric data collection
Read the full article, Why Covid-19 has shown that we need a universal payee ID now to combat fraud, on LinkedIn.
As we become increasingly aware of the prevalence of the conscious or unconscious racial bias, Tobais Baer provides a timely article that may help address and overcome sneaky biases that affect decisions, opinions, and actions.
The tragic death of George Floyd has triggered a global push to fight racial discrimination. There are many ways how each of us can contribute to this fight; one important way is to fight our own subconscious biases that can heavily influence our decisions – be it major ones like hiring or evaluating staff or making verdicts as a judge or jury member, or be it minor ones like deciding what we do or say when dealing with a sales clerk or customer.
The typical reader of my blog is intelligent, sophisticated, open-minded, and most likely already very supportive of equality and fighting discrimination. The snag: As Sheryl Sandberg powerfully confessed in a private talk I had the privilege of attending, even she, author of “Lean In” and an ardent fighter of gender discrimination, had caught herself espousing gender bias in evaluating her own female staff members.
Points covered in this article:
- Licensing and outgroup bias
- Monitoring body reactions
- Anchoring and signaling
Read the full article, How can you fight your own racial bias?, on LinkedIn.
As both people and businesses begin to feel the economic impacts of the Coronavirus, Tobias Baer provides clear steps that can help your business deal with delinquent accounts.
Many of my clients so far have experienced less delinquencies on consumer debt than I had feared. Unfortunately I don’t think that I can claim that this is only because I’ve helped them draw up extraordinarily effective credit policies and scoring systems – instead, this time around delinquencies themselves might be delayed, and lower balances today may be the receding water levels we observe before a tsunami. A welcome side-effect of lockdown measures across the world was that many consumers had a lot less opportunity to spend – discretionary spending has nose-dived by 30-60% in many markets and card portfolios. And those who were robbed of their income sources by Covid-19 often had some buffers (cash and credit lines) that they could draw upon.
Advice included in this article:
- How to segment delinquent accounts
- Build an economic model
- Reassign accounts to dedicated team
Read the full article, Three Tools You Need to Stem the coming Tsunami of Bad Debt, on LinkedIn.
Take a look back to the beginning of the COVID-19 pandemic with Tobias Baer where he asks us to imagine the positive impact to both the individual and the economy.
Amidst all the gloom and panic, I saw a light today. Grounded in Germany, I made a long bicycle ride through mostly empty countryside. All my worries about my family, clients, and own affairs notwithstanding, I couldn’t help feeling bliss and happiness, and it dawned on me that also this crisis won’t be the end of the world – and that we might be able to soften the blow and use it for something good. With a pause button.
As we look at especially elderly patients dying because of a shortage of hospitals and ICU machinery, shutting down the world makes sense. And spending one, two months at home with our families actually could be a boon in disguise – if it wasn’t for the world economy, our livelihood, fighting for its survival. And as I was gliding through the fields, I wondered if we could simply hit the pause button on the economy – if we, the ‘normal’ world (those lucky enough not to be fighting death in the world’s health systems), collectively could go on a 2-month vacation, like a meditation retreat, while the real world, our businesses and financial pressures, are frozen in time. And it dawned on me that in a world where already normality has disappeared and many businesses are shut down, such a utopia might not be far fetched at all.
Read the full article, Could a Pause Button Save the World Economy, on LinkedIn
Tobias Baer explains why the lack of randomized testing hampers businesses and raises the costs of the COVID-19 pandemic.
The lack of randomized testing again and again hampers businesses because it means executives need to make decisions half blind – and Covid-19 is no different, only that in the case of Covid-19, the cost of not doing randomized testing literally might run into the trillions of dollars.
Randomized testing is nothing new – and widely considered best practice in the business world:
- Marketing executives should run A/B tests to make sure that ads and other marketing outlays actually influence purchasing decisions and isn’t wasted on customers who would have bought the product anyhow (or worse, even discourage buyers);
- Banks and insurers randomly approve a small sample of credit or insurance applications rejected by their policy rules because otherwise they cannot know how many errors these rules make and if they lose any profitable business;
- Online sellers use randomized pricing experiments to test how much more or less revenue and profit they would make by raising or lowering prices a bit.
Read the full article, Why Covid-19 illustrates once more the need for randomized testing: Paying the price for biased information, on LinkedIn.
Tobias Baer explains why the second-order effects of the disruption caused by the Coronavirus are what should concern risk managers the most.
For risk managers, Covid-19 is both scary and a real-life test of our approach to risk management. As we are grappling with the virus and its fall-out, there are three sets of issues: the threat of the virus itself; the panic that it has caused; and lessons for operational risk management.
The risk of the virus itself is still hazy. I myself haven’t lost my cool yet considering facts such as that the total number of deaths from Covid-19 (less than 5,000 people globally as I write this) is dwarfed by the number of people who die in car accidents every year (more than 1 million in the US alone) and that while Covid-19’s overall mortality rate is estimated at 2%, it is less for the strong and healthy. In fact, as the WSJ points out, while Covid-19’s mortality rate of 2% seems to be 12.5 times higher than the ordinary flu with a mortality rate of 0.16%, the 2% may be greatly overestimated if many benign Covid-19 infections have gone undetected.
Points covered in this article include:
- Supply chain shortages
- Operational risk mitigation
- Mandatory equity buffers
Read the full article, Covid-19 and Risk Management, on LinkedIn.
Tobias Baer provides clear and concise examples of how Google uses the acquisition of select data to create bias, which leads to the dissemination of inaccurate information.
I’m an avid user of the navigation function of Google Maps. Every time I reach my destination, Google asks me for feedback on the navigation instructions. What could possibly be wrong with that? Well, I bet that the data and any analytics derived from that feedback often – and, vastly! – overestimates users’ satisfaction. Why is that?
The app is a perfect illustration of availability bias. I only am given this opportunity to provide feedback when I reach my destination. Which means that if I reach a river only to find that the ferry supposed to take me and my car to the other riverside has stopped operations an hour ago, or if after a few hours of cycling I find that the path indicated by the app leads straight into a gigantic military infrastructure that is fenced by barbed wires with large red signs threatening any trespasser to be shot (both has actually happened to me), and hence my only option is to abolish my route, exit the navigation, and go back to where I come from, no feedback is collected.
Points covered in this article include:
- The problem with creating algorithms quickly
- The lack of sufficient communication
- The challenge of creating objective, systematic assessment procedures
Read the full article, A Little Example How Google Creates Biases, on LinkedIn.
Data scientist and psychologist Tobias Baer (who recently published a book on algorithmic bias) is giving a talk on how to prevent algorithmic bias in the U.K. on Tuesday, 11 February 2020.
Algorithmic bias can affect us everywhere, from minor trivia such as our social media feeds to critical decisions where bias can wreak havoc with a person’s life dream or a company’s survival. Sources of algrorithmic bias are manifold – some, such as biased data and overfitting, sit squarely in the domain of data scientists themselves, while others only can be tackled by the business users and government agencies who use algorithms, be it through carefully crafted experiments that generate truly unbiased data or through deliberate tweaks of the decision-making process.
The discussion will include:
- The psychological and statistical sources of bias
- What business users and data scientists can do respectively to manage and prevent algorithmic bias.
- How regulators should think about algorithmic bias
To learn more about the event, visit: https://www.eventbrite.co.uk/e/how-to-prevent-algorithmic-bias-tickets-86670021367