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Andrew Kuper Introduces Microinsurance
LeapFrog is the world’s first investment fund to focus on the insurance needs of low-income and financially excluded people. Launched by President Clinton and hailed by The Wall Street Journal and Private Equity International, LeapFrog has opened a new frontier for social investment and microfinance. Andy founded LeapFrog in January 2007, inspired by his extensive experience enabling entrepreneurs in emerging markets, and then co-built the firm with a team of former CEOs and pioneers in emerging markets insurance. Andy is a former Managing Director of Ashoka, which has financed and connected 2000 social entrepreneurs in over 60 countries. He worked with both Grameen and BRAC, the world's largest microfinance institutions, to market their social ventures. He also co-founded Kuper Research, which designed The Daily Sun, now sub-Saharan Africa's largest newspaper, with 5 million daily readers. Born and raised in South Africa, Andy is a serial social entrepreneur and author of books including Democracy Beyond Borders (Oxford) and Global Responsibilities (Routledge). He holds a PhD from Cambridge, where he was supervised by Nobel laureate Amartya Sen, who first stimulated Andy’s interest in market-based solutions to poverty.
Andrew Kuper: Andrew Kuper, President and Founder of Leap Frog Investments.
Question: What is microinsurance?
Andrew Kuper: Well, microinsurance is very simple, it’s an insurance policy sold at a low premium to a purpose with a lower payout but that payout matters hugely to them. So a woman might need to go to a hospital but she has no safety net, no resources to fall back on, so she’s forced to either bankrupt the family or spend all their savings or not go to the hospital. And the consequences for her and her family can be profound. Now, what insurance allows her to do is pay a small premium each month, it might be a dollar, it might be $4, it might be $7, but fundamentally that allows that poor woman, if an unexpected event happens, to be able to go to the hospital, to be able to get medication to recover and not bankrupt the whole family or lose all their assets, the same is true of life insurance, people save and save for years scrimping, people earn very few dollars everyday and slowly accumulate assets and then one day as happens to all of us, four years in or two years in, some terrible event happens, the breadwinner dies and they can immediately have all their debts that they have to repay, they can have the funeral cost which can often be significant in parts of Africa and necessary for continued participation in the community and they lose all their assets, everything they’ve been working for and a whole family business that supports say the three kids and all their kids can go down the drain and these are real stories, I’m not making this up.
And what insurance will ask people to do is to recover from that shock so the breadwinner dies within two days there’s a payout, people can pay for the funeral, people can pay off their loans, people can have some money to continue the business and get it to a point where they can run it 6 months later.
This insurance may seem like a small thing because it only costs a few dollars but it provides people with the ability to recover from shock and actually globally studies have shown particularly the work Nobel Laureate [IB] has shown that the poor remain poor often because they have these adverse shocks. They do actually accumulate assets overtime and they may fall back into the poverty line so the importance of this cannot be underestimated, I think it is the one of the most central development interventions in the world and the exciting is that it’s profitable.
Now, just to take a step back, why is it profitable? Well, if you think in pure auctorial hardnosed business terms, insurance is about risk and it’s about predicting what’s going to happen and insurance companies takes money, tries to predict what’s going to happen and promises to make a certain payout at a later date and it takes some money in doing that and for sharing the risk; for organizing a risk pool.
Now, what makes something predictable, well, it has large numbers. You would rather have a million people you’re ensuring at a lower cost than a thousand people you’re ensuring at; for a higher premium that they’re going to pay. So the incredibly exciting thing about microinsurance is you can sell a huge number of policies at low margins to huge numbers of people and your risk pool becomes quite predictable and that makes it much easier to manage so eventhough you’re taking a smaller cut on each policy, you’re actually doing fundamentally in some ways a better business. Now, the important thing is you’ve really got to get your costs low because if you’re selling a policy for $7 adding on 50 cents here or there is going to create real problems.
So one of the really exciting things is the technology and the systems that allow you to do this so microinsurance is now being sold through cellphones, people are working through groups like churches where in South Africa, three million people come the [IB] Church every Sunday and they buy, a lot of the buy microinsurance and it’s a very successful scheme part earned by the largest [insurance] in Africa, microfinance institutions. When people walk in for a loan, you add 2% and suddenly those people have covered so that the load is repaid, so that they’re covered in the event of the death of the breadwinner and so they have a better outlook. Now, the last exciting thing here is it’s not just about protection in terms of social impact, it’s hugely important because it’s enabling. So think of a farmer, I myself have had bad experiences, failed development experiences where I went to India and tried to get farmers to adopt certain drip irrigation technology and others have done this with seeds, trying to give them seeds that really help increase productivity and farmers said no and we couldn’t work it out.
We thought, “Look, this has a 95% change of success, they’re going to triple their income, your family is going to climb out of poverty. Why are these farmers not doing it?”
And the answer is there is a 5% chance of failure and 5% chance of failure of any new business, for these people means that their children starve.
So how many of us are going to undertake a new business when there is 1 and 20 chance that our children starve? Now, what microinsurance can do with things like crop insurance for instance is help people to take worthwhile risks so people know that the assets of their family are protected, that their loans are repaid if they die, that they aren’t going to leave their family destitute. They know that if the crop fails because of something entirely outside of their control, that they’ll be able to get a payout. So they’re able to engage in new forms of economic activity, they’re able to take risks that allow them to dramatically in some cases increase their income. So it’s not only protective microinsurance, it’s enabling and that is what I think makes it one of the world’s most important development interventions.
Recorded on: May 1, 2009
The president of LeapFrog Investments shows how the principles of microfinance can apply to the insurance industry.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
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An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.