ibc Blog

A brief outlook on the COVID-19 pandemic in the U.S.

Küssnacht, June 1st, 2020

We wish we could agree with what appear to be overly optimistic assumptions about the future evolution of the COVID-19 pandemic in the U.S.

According to IHME's projections for the U.S. as per May 30th, there will be 135,109 confirmed deaths by Aug. 4th and 2.2k new estimated infections on the day of Aug. 4th (note: this number refers to estimated total infections, not confirmed infections; IHME's estimate for the ratio of confirmed infections to estimated total infections on May 30th was roughly 40%).

The Three Great Trends in Banking

Küssnacht, January 8th, 2022

At ibc insights, we see three major trends that are shaping today’s banking industry and for which top management needs to adjust existing business models. These are, first, the increasingly onerous rules imposed by supervisory bodies; second, digitalization and the emergence of competition by fintechs; and, finally, concerns for sustainability entering the mainstream.

Increasingly onerous rules imposed by supervisory bodies. Since the financial market crisis in 2008 and the sovereign debt crisis in 2010, banks have had to deal with an increasing number of rules enacted by national and international banking supervisors. Adherence to these regulations results in a higher amount of administrative costs as well as a higher amount of equity. Both effects lead to a reduced return on equity. What’s more, banking authorities appear not to stop intensifying existing or enacting new rules. That’s why banks need a deep understanding of how to manage the banking authority game. Management needs to find strategies to operate with these rules and to optimize the allocation of equity.

Digitalization and the emergence of competition by fintechs. Digitalization changes almost everything in the banking industry. Stronger competitive forces have arisen due to the emergence of new players such as Fintechs. Customer needs and customer behavior have changed. Smartphones have become the new interface between clients and banks. Customers demand apps that help make banking easier. Automation of all working processes in a bank is increasing. Artificial intelligence, e.g. as a part of data sciences or digital technologies, is used in many areas, such as tailoring the customer approach in sales or improving the measurement of risk and return in. Banks need to develop rapidly as technology companies.

Concerns for sustainability entering the mainstream. Nowadays, sustainability is the main topic everywhere. Banks need to define environmental, social, and governance (ESG) rules and implement sustainable work processes. To measure and control sustainability, bank managements have to establish new models and methods such as ESG rating for corporate clients or ESG steering procedures. Clients demand sustainable financial products and they may indeed be ready for less return or higher risk if financial investments are based on sustainability.

Within this challenging landscape, players have to find new ways of safeguarding an acceptable level of return on equity. The best players will see that these changes also provide great opportunities. Stay in touch and please do not hesitate to contact us if you have any questions.

Using Spoken Audio to Build Toward Lean Learning

Küssnacht, December 14th, 2021

One of the biggest challenges faced by today’s knowledge societies is how to make high-quality education accessible to everyone. Unfortunately, unlike sectors such as technology, which tend to improve their productivity over time and experience constantly declining costs, the education sector tends to suffer from persistent cost increases.

An obvious target for educational cost-cutters are line items like staff, real estate, etc. But the biggest cost component in the educational process is actually something much less tangible: namely, the opportunity cost of students’ time.

In Fixing Higher Education, Christian Schierenbeck argued for an approach he dubbed “Lean Learning” as a way for educational institutions to reduce these costs. Lean Learning represents an attempt to avoid waste in students’ learning time, non-learning study-related time, and study-unrelated time. There are all kinds of ways to do this. As part of this blog post, we’d like to focus on one particular opportunity that has arisen with today’s ubiquity of smartphones, advanced text-to-speech technology, and wireless headphones.

If you look at a typical day in a student’s life, you will find many examples of what we may refer to as “downtime”: moments during which a student’s hands and/or eyes are busy, yet her mind is free to absorb information. Examples include exercising, traveling (e.g., commuting in your car, taking a bus or a taxi, riding a train or a plane, etc.), waiting (e.g., in a line at the grocery store), doing housework (cleaning, washing, ironing, gardening, walking the dog, etc.), cooking, eating, and grooming. If you add up these moments, you will be shocked at how much time these moments account for in aggregate. Indeed, we’ve tested it ourselves, and found that it’s easily more than 3 hours per day. For someone who has a long commute, for example, or does a lot of exercise or housework, it can even top 5 hours.

Why not have your students use this time for learning? All it takes is an app which (1) allows you to curate content for your students and which then (2) converts this content into audio for your students to listen to. One such app is Expercast. (Disclaimer: We are affiliated with this app ourselves.)

Not only does Expercast make it highly convenient for you to curate content for your students (all you need to do is submit links to articles or websites you’d like your students to listen to), it also trains your students to listen to the content at increasingly high playback speeds, thus helping them get even more educational impact per hour of study time.

Expercast is currently in private beta. If you would like to get early access, please send an email to support@expercast.com.

A retrospective on our year-end forecast

Küssnacht, January 3rd, 2021

IHME had predicted 371,509 confirmed COVID-19 deaths in the U.S. by the end of 2020, which we believed to be too high. We thought the number was too high based on

research data from the summer months whereby the seasonality of SARS-CoV-2 appeared somewhat less pronounced than for other seasonal respiratory viruses,
treatment improvements, introduced by the time of our forecast as well as expected before year's end,
improved protocols protecting residents of long-term care facilities, as well as
an increased level of immunity among certain pockets of the population with a particularly high infection risk due to external factors and their health behaviors.

Indeed, the number of confirmed deaths did turn out to be significantly lower than IHME's forecast. However it was lower by not nearly as much as we expected (namely 345,737 confirmed deaths as per Johns Hopkins versus our base case of 308,000).

There have been several factors accounting for this delta. For example, data from the summer months which indicated somewhat lesser seasonality than originally expected have by now again been superseded. Also, we had high hopes for Eli Lilly’s bamlanivimab and Regeneron’s casirivimab-and-imdevimab cocktail and they did receive an EUA on November 9th and 21st, respectively. However, a host of factors - from lack of awareness among primary care physicians to a lack of staff to administering them - have severely restrained their impact so far. Yet, what has astonished us the most is the very limited use of countermeasures by federal and local governments even after the COVID-19 burden was already overwhelming. The following graph from IHME shows how hospital beds for COVID-19 patients in the US already reached an all-time high by mid-November, far exceeding the earlier peak from April:

Yet, the level of social distancing barely changed even then - a far cry from the response in March and April (again, chart provided by IHME):

Due to the previously observed trend towards COVID-19 complacency as well as for political reasons, we expected social distancing measures to be somewhat lacking, yet we did have some faith in a more vigorous response in times of such national crisis.

A Perspective on COVID-19 in the U.S. at the end of 2020

Küssnacht, September 30th, 2020

IHME currently predicts 371,509 confirmed COVID-19 deaths in the U.S. by January 1st, 2021. Since the early days of the pandemic, IHME has been rather consistent in underestimating the future evolution of deaths in the U.S., and we predicted one such underestimation in our June 1st blog post. These days, however, we believe IHME’s predictions are erring on the opposite side: our model’s base case expects a much smaller number of deaths than IHME, namely 308,000 by January 1st, 2021.

A retrospective on our forecast

Küssnacht, August 5th, 2020

Around two months ago, on June 1, we warned that IHME’s model (which seemed in line with general public opinion at the time) made what seemed to us like far too rosy predictions of the evolution of COVID.

At the time, IHME predicted 135,109 deaths and roughly 1,000 confirmed new infections per day as of August 4*. By contrast, our own top-down model suggested that, by August 4, there would be 148,092 deaths and just over 10,000 confirmed new infections per day.

Just as we had warned, reality turned out to be far more somber than IHME’s predictions and public opinion - indeed, even more somber than we dared to imagine ourselves. More specifically, the number of deaths reached 160,290 and there were 54,504 confirmed new infections on August 4.

Note, in particular, the delta in the number of confirmed new infections per day: IHME’s predictions were off by a factor of around 50X! Our own predictions on this metric were ten times more pessimistic than those by IHME - which may have seemed eccentric at the time, but actually turned out to have been too conservative still.

As regards the drivers behind our estimates, we correctly identified that the constant decline of deaths and new confirmed infections per day since the end of April at the aggregate national level was misleading. In reality, this aggregate was composed of two opposite trends: on the one hand, a major improvement in the initially heavily affected states (New York, New Jersey, and others), already with more advanced testing capacity, and on the other hand, worrisome unchecked growth in mostly southern states with yet underdeveloped testing infrastructure. (As regards the latter, we cited California, Arizona, and Alabama as examples, which indeed evolved into major outbreaks). Even though this dynamic was discernible at the end of May already, there is a widespread belief even today that this latest surge appeared “out of nothing” in the first half of June.

* IHME did not provide an explicit estimate for confirmed (vs. total) infections. They predicted roughly 2,200 total daily new infections on August 4, as well as estimating, until the present moment, a share of not more than 40-60% of confirmed new infections out of total new infections.

We are concerned that these projections - in the same way as public opinion - miss out on the relevant threat of virus spread of across several US states: in states such as Alabama, Arizona and California, to name a few, not only has there been a worrisome rise in confirmed daily new infections, but the current easing of lockdown measures threatens to accelerate this and to overwhelm insufficient contact tracing capacity. If hotspots turn into outbreaks that need to be contained by renewed lockdowns, it will not only seriously affect the economic recovery, but also cause significant additional morbidity and mortality.

We've created a top-down model which we believe may offer more accurate predictions of the evolution of the pandemic. As of May 30th, our model predicted 148,100 confirmed COVID-related deaths and a total of 2.8 million confirmed infections in the U.S. by Aug. 4th (it implies roughly 10k new confirmed infections on Aug. 4th itself, almost twice the upper end of the 95% CI of IHME's projections even for total estimated infections).

We sincerely hope that we will be proven wrong in favor of the more optimistic projections by the IHME model!

There are many plausible reasons for expecting a surge in U.S. COVID deaths during the upcoming months, such as enhanced spreading of the virus in the cold, an increase in the time people spend indoors, the reopening of schools and university campuses, and a trend towards complacency. However, we believe that IHME does not sufficiently account for a number of factors which seem to limit the extent to which COVID deaths may increase.

Based on experience with influenza viruses and common human coronaviruses, there was widespread underestimation of what SARS-CoV-2 could do in warm climates; however, conversely, one shouldn’t now extrapolate from the summer to the winter based on influenza and common coronaviruses.

Thanks to remdesivir, dexamethasone and improved ICU protocols, there has been a significant reduction in mortality, and it is to be expected that further treatment improvements will be made in the coming months.

Since an estimated 40-50% of global COVID deaths are related to nursing homes, any prediction of COVID deaths needs to specifically predict nursing home deaths. Here, our view is that compared to the early days of the pandemic in the U.S., there has been a trend towards significantly improved protection of residents - even though, sadly, we do expect a continued grim toll in this population.

Finally, we consider it crucial to form a granular understanding of the differential risk profiles in the wider population and to make predictions based on such an analysis. One can divide the population into infection risk segments, based on the external factors surrounding an individual (for example, essential worker status with increased exposure) and based on an individual’s mindsets and behaviors (for example, wearing masks or avoiding eating out at indoor restaurants). Whereas we are very far from herd immunity for the population as a whole, the highest risk pockets have been hit disproportionately hard in the pandemic so far. In terms of predicting the further spread until 2021, one does need to account for the fact that those population segments with favorable external factors and health-conscious mindsets and behaviors will continue to have a relatively smaller infection risk, even in a challenging winter. There will already be some immunity among the highest-risk pockets, and one cannot directly extrapolate from their past exposure to the other segments.

Our pessimistic June 1st forecast concluded on a note of hope that our predictions would be proven wrong. (Unfortunately, reality turned out to be even more bleak than we had feared.) Since, this time, we are taking a more optimistic position, compared to IHME’s predictions, we hope that we will be proven right.