“My voice is my password” and similar phrases have begun to be used for secure voice authentication for banks and health insurers and other critical services that require security and privacy.
It’s likely that several of your own service providers will roll this out in the next couple of years. Progress, right?
The problem is that in the short time since voice identification models have become mainstream and slick enough to be used in call centers, voice spoofing technology has exploded. It is now trivial to create voice tracks saying whatever you want them to say without human ears being able to tell any difference, and increasingly, fooling the voice authentication models too.
Worse, we are probably only a few years from trivial video spoofing with the same qualities.
I support the idea of moving away from passwords and improving security, but I struggle to understand how voice authentication is anything other than a tiny blip in the timeline before it becomes the easiest vector for fraud yet.
Setting discount rates is a crucial and subjective exercise. This is true for life insurance embedded values too.
Many researchers are comfortable with a range for Equity Risk Premiums of between 3% and 5%. Many corporate finance practitioners use a range from 5% to 8% or even higher. My nearly eight year old blog post on mis-estimating the ERP covered these differences in detail.
This post is a little different. Forget about what theory says, what are the implications of using a high risk discount rate (RDR) when calculating embedded values and then trying to maximise value.
Solvency II and SAM suggest a 6% (excess over risk free) cost of non hedgeable capital. Most South African insurers calculating real world embedded values use risk-free + 3.5% as their RDR.
Some insurers want to use an RDR closer to 15% or even 20%. The problem here is one of convictions. If the cost of capital was truly felt to be 20%, then capital optimisation, value optimistion and therefore reinsurance decisions should be made with this in mind.
It will almost always be the case that reinsurance will have an implied cost of less than 20%. Thus, the consistent action would be to grab as much reinsurance as possible, at least up the point where the reinsurer was concerned about skin in the game.
I don’t see this happening in practice.
Some insurer will argue that they don’t want to give away all their profits to a reinsurer. This fundamentally misunderstands how reinsurance is priced and the impact of return and profit commissions to facilitate reasonable commercial terms.
Similarly, the pursuit of greater investment returns usually results in more risk and more capital required. At a 20% return on capital requirement, pretty much no avoidable market risk should be retained.Yet I still see insurers opting to take on more credit risk (even at current depressed credit spreads) in pursuit of a little extra yield.
We can have a debate about the range of reasonable RDRs to use. But there is a credibility problem if this rate isn’t also used to decide on reinsurance and investment strategies.
I have never owned Steinhoff shares. I was surprised then, when going through some old blog uploads (dealing with a separate copyright issue that I may touch on in another post) to find this share price graph of Steinhoff from 2007
Am I going to invest in Steinhoff? Well, no, not yet, not until I have actually done some proper research into the fundamentals of the company. And also not until I have understood the reasons for the decline in price over the last year properly. If the market thinks they are worth less, I had better know why the market thinks so before I disagree too strongly.
Having said that, I pay careful attention to knowledgeable insiders when they put their money where there collective mouths are and vote with their personal wealth and risk appetites that a company is a good bet.
I never sufficiently understood the fundamentals of the business and how it related to their accounts and valuation. Score one for then not investing.
However, I was also saying that I saw value in following directors’ dealing and possible positives from directors investing in their own stock. In the case of Steinhoff, it’s hard to separate out:
true belief in their business;
attempts to demonstrate confidence in the shares (whether or not the confidence was actually held); from
artificial attempts to prop up the share price
I have less time for fundamental analysis these days so low cost trackers is more my flavour. Given my mixed success in the past, perhaps that’s just as well.
I walk my daughter to school many mornings. On the way up the hill, we play a game. I tell three stories and she has to tell me which is untrue.
So far it’s clearly been too easy as she gets them every time. That’s okay, I still plan to beat her at carcassonne some day. It turns out it’s quite a fun way to tell her slightly unbelievable stories about my life as well as teaching her to think about whether what she’s told is true or not.
Expectations of future UK life expectancy have declined for several years now. This is not to say that current life expectancy has decreased, but rather than estimates of future mortality improvements are being lowered, pushing down future estimated life expectancy.
The thing is, it’s no utterly crazy to think about extreme life extension for currently living people. We don’t need to solve ageing in the next 40 years for a 40 year old to live to 200 or 1,000. In the next 40 years, we need to extend life by enough time to allow the research for the next 40 year extension and so on.
I’m feeling a little old myself with a milestone birthday coming up in a couple of days. For now, 50 years still feels like a long time, although Asimov’s The Foundation series and the Long Now crowd would likely shame me into thinking I am a super myopic actuary.
Life expectancy is one of those funny measures with a cavernous gap between those who think they understand it and those who do.
The latest controversy arose a few days ago a year ago (this post has been in draft for a long time…) because Russia is planning to increase the normal retirement age from 60 to 65 for men by 2028 and 55 to 63 for women by 2034.
“Life expectancy at birth” is a well defined term estimate the mean age at death of someone just born.
“Life expectancy” without a modifier generally implies this as well, but can be misunderstood
“Life expectancy given survival to age x” or “life expectancy by age x” is how long one is expected to live, given your current age x.
Problematically, terms to differentiate “remaining life expectancy” (the number of years remaining) and “total life expectancy” or “expected lifetime” (the total number of years expected to live including those already survived) are not used consistently.
Every day that you dodge death, your total life expectancy goes up. An 18 year old, with newly conferred adult status, will have a total life expectancy somewhere between 0 and 18 years higher than their life expectancy at birth, depending on how dangerous childhood was expected to have been in the calculation of the original life expectancy (at birth) calculation.
Progression of Life Expectancy at birth for almost all countries remains on an upwards trajectory
The World Bank has a useful interactive tool for plotting useful figures. Here is the progression of life expectancy at birth for a subset of countries.
There have been gains even in recent years (opposed to over hundreds of years, where the massive gains are widely accepted). The gains are not without interruption.
South Africa, in particular, was hit by HIV/AIDS for many years. HIV/AIDS affects the mortality of babies and young children through mother to child transmission. This has a particularly potent impact on life expectancy at birth.
Mortality improvements in the UK have slowed down dramatically in the last few years.
Life expectancy in the US has actually gone backwards in recent years, partly linked to opioid abuse and suicide.
One of the reasons this blog post took ages to come out is after a bit of rambling I wasn’t sure what the conclusion is. This would need to be a much longer post to really cover any amount of the detail. However, perhaps this provide a tiny taste of the complexities involved with the terminology (ab)use and the actual numbers and drivers.
I’ve been using snopes.com to fact check dubious stories since before fake news was a term. I still recommend it to everyone.
I also teach elements of critical thinking in some of the actuarial normative skills workshops I run. By the time students get to me there, they are often already pessimistic and cynical when it comes to core areas of work (to be clear, this is a criticism of the profession, with a silver lining of critical thinking). However, there are plenty of other areas where their minds still seem susceptible to fakenews.
This re-energised my interest in this area. I’ll blog on this topic more in future. One area I discovered in my research is the Illusory Truth Effective.
The Illusory Truth Effect is a really disappointing insight into how poorly our brains do at identifying truth. At its core, it says that when subjects are exposed to facts multiple times, even if the facts are highlighted as being false, still increases the probability that those subjects will view the facts as true. So whether it is on a Sunday morning surrounded by friends and family, or on the couch on your own infinitely browsing social media, what you see and hear and read becomes true in some proportion of minds.
It also applies to election campaigns and political rhetoric.
I’m going to test this with my actuarial students next chance I get.