Disaster capitalism - How financial markets benefit from the climate problem | DW Documentary

DW Documentary
24 Feb 202451:56

Summary

TLDRThe transcript discusses the emerging market for catastrophe bonds which allow investors to bet on potential disasters. It explores how former Wall Street bankers like John Seo create complex financial products to cover damages from events like hurricanes, using advanced statistical models. However, these products are inaccessible to most disaster-prone communities. The transcript criticizes how global capital exploits catastrophe risk for profit rather than focusing on prevention and community resilience. It highlights the limitations of algorithms in capturing unpredictable human behavior during crises when lives are at stake.

Takeaways

  • πŸ’° Excess capital is a global issue, with an estimated 10 to 20 trillion dollars seeking profitable investments.
  • 🌎 'Planet Finance' symbolizes a complex and fast-paced world where financial opportunities, especially risky ones, are pursued aggressively.
  • πŸ”₯ Catastrophe bonds (cat bonds) are financial instruments that speculate on the occurrence of disasters, transferring risk from insurance companies to investors.
  • 🚨 The shift from traditional insurance to cat bonds reflects increasing costs and risks associated with natural disasters, leading entities like New York's Transportation Authority to seek alternative coverage methods.
  • 🌧️ Cat bonds provide a unique investment opportunity, offering high returns but with the risk of total loss if the specified catastrophe occurs.
  • πŸ“ˆ The demand for cat bonds is growing, driven by their non-correlation with traditional financial markets and the increasing frequency and severity of natural disasters.
  • πŸ” Cat bond pricing and risk assessment heavily rely on data modeling and predictions about future disasters' likelihood and impact.
  • 🏘️ The personal stories from Bonny Dune illustrate the harsh realities and limitations of relying on public services during natural disasters, highlighting the importance of individual preparedness and community action.
  • πŸ’‘ There is a clear divide between those who can afford to protect their assets through instruments like cat bonds and those who must fend for themselves.
  • 🌐 The global nature of 'Planet Finance' shows that while financial markets can provide mechanisms for risk management, they also reflect broader disparities in access and vulnerability.

Q & A

  • What is the main issue caused by excess capital roaming the world?

    -Excess capital has no useful place to be invested, so it creates its own opportunities and allows crazy financial schemes to arise just to be put to work.

  • How did catastrophe bonds first come about?

    -They arose after Hurricane Sandy when the New York City transportation system realized its insurance was not enough to cover damages, so it worked with Wall Street to create catastrophe bonds to raise additional funds.

  • Who buys catastrophe bonds and why?

    -Big investors like pension funds, hedge funds and others buy them because they provide high returns uncorrelated to other markets and diversify risk across different disaster types and geographies.

  • How do the catastrophe bond triggers work?

    -The bonds have precise triggers based on disaster model predictions of minimum damage thresholds. If those triggers are hit, investors lose their money, which then pays for damages.

  • How did the residents of Bonny Doon fight the wildfires?

    -When the fires approached and firefighters would not come, the residents fought the fires themselves, using bulldozers to create a fire break to protect their homes.

  • How did John Seo's firm assist with the wildfires?

    -They used satellite imagery and modeling to predict property damage and losses, helping investors understand if their catastrophe bonds were at risk of being triggered.

  • What criticisms were raised about traditional disaster risk models?

    -That they rely too much on historical data when risks are changing with climate change, so AI and machine learning approaches do more simulations to better predict future risk.

  • Why are catastrophe bonds appealing to investors?

    -They provide returns uncorrelated to financial markets, so even if markets crash, the bonds continue paying high interest unrelated to market conditions.

  • How did residents of places like Bonny Doon feel they were viewed by officials?

    -They felt labeled as insignificant and disposable, realizing for the first time that the fire department and wider society did not value them or their homes.

  • What preparations did the Bonny Doon elder make for future fires?

    -He created a protective bunker stocked with air, water, and firefighting gear to shelter in and have the means to defend his property during future fires.

Outlines

00:00

😱 Capital chasing opportunities leads to crazy financial instruments.

Excess capital is desperately looking for places to invest, creating niche markets like catastrophe bonds that pay out when disasters happen. This allows capital to chase speculative opportunities just to be put to work.

05:00

πŸŒͺ️ Sandy wreaks havoc, but creates opportunity.

Hurricane Sandy caused massive damage to New York's infrastructure. Since traditional insurance didn't fully cover the losses, the city issued catastrophe bonds to raise money, paying high interest rates to investors who take on the risk of losing principal if another storm hits.

10:04

πŸ’° Wall Street finds appetite for oddball risks.

Investing in catastrophe bonds became popular on Wall Street because they provide high returns uncorrelated to other markets. They are complex instruments that pay off under highly specific disaster scenarios, but hedge funds enjoy modeling the risks.

15:04

🌊 New York adapts to climate change threats.

After Sandy, New York installed flood barriers and improved infrastructure. The catastrophe bond arrangement provides funds for repairs if flooding triggers are met, encouraging proper planning by setting measurable risk thresholds.

20:06

πŸ”₯ Taking on tail risks beyond the bell curve.

Traditional finance dislikes unpredictable disasters and uses normal distribution curves. But by developing models for severe events like 9/11, new firms like John's hedge fund tap into profitable "tail risks" that scare big institutions.

25:06

😒 Locals fend for themselves as wildfire encroaches.

When a massive wildfire threatened their California community, residents stayed behind to fight it themselves as firefighters were overwhelmed by the scale of simultaneous blazes sparked by lightning.

30:10

πŸ’» Wall Street models don't capture human behavior.

John's firm models wildfire risks to price related catastrophe bonds, predicting likely property damage. But unpredictable human actions in crisis like stubborn residents staying to defend homes defy simplified calculations.

35:11

πŸ˜• AI judges areas uninsurable based on models.

A startup uses machine learning to model wildfire probability, considering factors like weather, terrain and emergency resources. But model outputs may determine remote communities are too risky for affordable insurance.

40:14

😒 After the smoke clears, there is only loss.

In the wake of the devastating wildfire, the isolated rural community was largely written off by officials and received little aid. For them no financial instruments cushions the blow, only loss of lives and property.

45:16

🌑️ Climate change fuels growing catastrophe market.

Increasing disaster severity from climate change drives more demand for catastrophe bonds. Firms Make big money modeling amplified risks while promoting these instruments as diversification for investors.

50:19

πŸ’° Ultimately insuring yourself may be the only option.

Those in vulnerable, underserved areas cannot rely on Wall Street innovations to manage risk. Instead locals build their own "insurance" by preparing for disasters, from bunkers to community defense like fire breaks.

Mindmap

Keywords

πŸ’‘Capital

Capital refers to money and assets invested by companies or individuals for financial return. The video says there is 10-20 trillion dollars in excess capital globally that is desperately looking for investment opportunities and returns. This drives capital to fund risky ventures like catastrophe bonds.

πŸ’‘Catastrophe Bonds

Also called cat bonds, these are a type of insurance-linked security that transfers catastrophe risk to investors. They pay high interest rates but investors lose principal if a triggering event like a hurricane or earthquake occurs. Cat bonds provide insurance companies with reinsurance so they can cover large-scale disasters.

πŸ’‘Planet Finance

This metaphorically refers to the world of high finance focused on complex financial mechanisms, investments, and speculation. Things like derivatives, hedge funds, and cat bonds exist on Planet Finance. The video explores how this planet operates.

πŸ’‘Risk

A major theme is how risk is calculated, commodified, traded, and profited from within Planet Finance. This includes tail risks from catastrophes as well as systemic risks from climate change which traditional finance is unequipped to handle.

πŸ’‘Mathematics

Advanced mathematics and algorithms are used to build models that try to predict the likelihood and losses from various disasters and extreme events. However, the video questions whether human behavior can be captured fully in such models.

πŸ’‘Opportunities

For those with capital and computing resources, disasters also represent profit-making opportunities as clients urgently seek to offload cat bonds and related securities when catastrophe seems imminent.

πŸ’‘Triggers

Cat bonds have triggers which specify conditions like minimum hurricane intensity or flood water levels. If those triggers are activated by a subsequent disaster event then investors lose all or part of their principal.

πŸ’‘Bunkers

Both the village elder in the video and the Planet Finance system create bunkers as protection against disaster - physical bunkers in the case of people, financial bunkers in the case of cat bonds.

πŸ’‘Significance

The village residents realize they are not "significant" to the wider system governing disaster response and are essentially disposable. In contrast, financial centers like New York are significant which is why cat bonds exist to protect their infrastructure.

πŸ’‘Vulnerability

Both the physical/geographic vulnerability to disasters and the financial vulnerability of companies and municipalities are calculated and translated into cat bond mechanisms and premiums.

Highlights

There is roughly $10-20 trillion in excess capital globally that is struggling to find useful investments

Catastrophes like hurricanes, floods and fires cause breakdowns of systems and create uncertainty, which financial markets struggle to deal with

Catastrophe bonds allow investors to invest in the risk of potential disasters, providing high returns but with the risk of losing everything if a disaster occurs

John's hedge fund makes money by precisely calculating risks of disasters using complex data sets and algorithms to price catastrophe bonds

Human behavior in crises is hard to capture in algorithms and models. Individuals react unpredictably compared to large groups

When disaster strikes, most people freeze or flee but some stubbornly stay to defend their property, a behavior that is accounted for in pricing models

AI models run billions of simulations with granular data like tree types and distance to fire trucks to calculate wildfire risks for insurance

Investors are attracted to catastrophe bonds because returns are uncorrelated to regular markets - bonds still pay out if stock markets crash

When a potential trigger event happens, investors race to re-price and trade the affected bonds, providing profit opportunities

John's team continuously stress tests climate projections against their models to estimate rising risks and potential damage over time

After disasters like wildfires, there is often nothing left of value except the catastrophe bonds before damage is clear

Though risks are rising, investor demand grows for catastrophe bonds which now exceed the expected disasters

Sophisticated algorithms judge areas like Bonny Doon too risky to insure though locals feel neglected and disposable to official emergency services

Locals realize they must rely on themselves in disasters, not governments, as they are deemed insignificant and disposable

The village elder has his own insurance policy - an underground bunker stocked for survival in case of being trapped by wildfires

Transcripts

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in the old days say uh pre1 1990s uh

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Capital was king or

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queen you called the

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shots now capital is a

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burden I estimate that globally there's

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roughly 10 to 20 trillion in excess

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Capital that has no useful

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home no place to

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go it's it's just roaming the world

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searching for a a

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use for those who possess that Capital

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uh it's it's a little bit of a

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nightmare so it can kind of make up its

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own opportunities or it can allow crazy

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Financial opportunities to arise solely

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to put that money to

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[Music]

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work there is a world made up of

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numbers a world where you have to be the

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smartest or the

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fastest a world connected by radio waves

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and Fiber Optic

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[Music]

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Cables a world where you can make money

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if you think you know what the future

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holds a world of fear and

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[Music]

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desire where you can win or

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lose I call this

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world Planet

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Finance wandering around Planet Finance

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I arrive at a place where they really

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love risk here they speculate on the

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chance of a wildfire flood or other

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catastrophe

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happening you want to try go from there

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come on boys let's go this man lives of

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disasters I married while I was in

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college and I started my family while I

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was doing my

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PhD my my first child he cost the

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insurance company half a million dollars

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uh being born

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prematurely and so the person at the

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insurance company told me your next

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child won't be

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covered oh so good someone whispered to

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me and they said hey go to Wall Street

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um you know a lot of math they'll give

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you health care just for solving one

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equation okay so in the first interview

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the person comes in he said John uh does

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money motivate

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you and he went on and on a 10 or 15

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minute speech that culminated almost do

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you worship at the altar of money does

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money mean more to you than anything

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else on this planet Etc so I was like

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wow this is a very long speech so waited

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for him to finish and I said

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no now see then why are you here I said

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oh I just need health insurance and I'll

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do anything that you ask me to

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do that was my start and that led

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directly and eventually to my getting a

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phone call from Leeman Brothers one day

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for catastrophe

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bonds I said oh wow I go okay so I have

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no experience in that and he said that's

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the great thing nobody

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does on planet Finance there is a market

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for nearly

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everything even for a future

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disaster a disaster that hasn't happened

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yet a disaster that might never

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happen

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there are people who spend all their

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time calculating the minimum chance of

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such a disaster happening and above all

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the extent of the

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[Music]

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damage what is a crisis or a catastrophe

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or a hurricane what happens is it Causes

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Chaos and chaos is the breakdown of

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typical

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[Music]

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systems

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and it's this feeling of you normally

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walk around you're like I know the

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subway is going to come at this time I

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know that I have to go to work at 9:00 I

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have to leave by five and to go to the

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grocery store and then a crisis hits and

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none of that is known anymore suddenly

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it's all in the world of unknown to show

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you how such a chaotic situation can

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give rise to a market I will take you

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back to a dark Autumn

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night

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come here

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sh Hurricane Sandy reaches the shores of

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New York a state of emergency is

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declared and all traffic comes to a

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standstill the South part of Manhattan

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is

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flooded and power goes

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out the next morning the extent of the

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damage becomes clear and even Wall

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Street is forced to close trading for

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two days a rarity the last time that

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happened was after to

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911 the aftermath is a process of how do

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you go from chaos back to understanding

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or back

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to some sort of stability it's not going

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to be the same as it was before but

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hopefully a little bit more stable than

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than uh than that moment of

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Chaos

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the storm leaves New York with 43 dead

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and billions of dollars of

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damage the flooded tunnels are the

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greatest disaster to ever happen to the

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city's public transportation

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system be careful CU you want to have

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some grease in it so might be a little

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sppy so how do you make a business out

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of that what what is the business well

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the business is

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being able to predict that risk and

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price it how can anyone make money out

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of a disaster a disaster that only seems

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to leave losers in its

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wake the tunnel filled with water for

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about 2/3 of its length we estimate

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there were about 60 million gallons of

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salt water entered the tunnel

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I think it was about a week of solid

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pumping just to just to pump the water

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out of the tunnel that was before we

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started doing any repairs or cleaning or

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anything like

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that I don't think anybody anybody knew

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what the intensity of it was going to be

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when it actually came and you know we

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weren't weren't really prepared for it I

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guess today New York is prepared to be

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able to pay for the damage when the next

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hurricane happens a former Banker has

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found the solution she spent years on

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Wall Street and now works for the

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Transportation Authority of New York for

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the uninsurable damage she goes to

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Planet Finance for help we're all here

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about hurricanes in the Caribbean we

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know about damage in Florida

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occasionally and we never thought that

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it would come here but it

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did

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of course our system was devastated the

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inside of our tunnels um have a lot of

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electrical um equipment that was all um

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[Music]

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ruined our um damages were like in about

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$800 million range I

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think we were only able to get about 500

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million give or take in coverage and the

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premium doubled actually more than than

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doubled so we were concerned that we

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were not able to get enough coverage

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that's when we started working on our

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first cat Bond transaction let's explain

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that one first cat bond is short for

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catastrophe

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Bond a bond is nothing more than a loan

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that has to be paid back before a

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specified

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date I lend you a sum of money you pay

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me interest and at the end of the term

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you pay me back the borrowed amount but

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a cat Bond goes further than that if a

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disaster occurs before the end of the

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loan's term the money lender loses the

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entire sum which is then used to

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compensate for the damage and save New

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York it's it's exactly like insurance

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right Insurance collects your premium

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while everything's okay it's supposed to

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pay you when you have been and

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loss so now New York pays interest on a

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cat Bond instead of an insurance

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premium and if you want to buy a cat

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Bond you go to John so I described the

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deal and I fairly quickly got to the

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size it's say oh nothing just 500

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million you know years ago Jon couldn't

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get health insurance when his wife was

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expecting a second baby now he owns a

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hedge fund specialized in cat bonds the

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hedge fund there is losing leaving 400

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basis points on the table right that's

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why it's like cuz we're not cat bonds

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that should cover the damage of future

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disasters reasoning is that there are

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all these opportunities and you just

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have to give examples like I gave right

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but as I say to get in on the game you

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need at least € 100 million hold on a

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second this is a billion and a half

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commercial mortgage that's backed by the

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collateral of the building itself the

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complex and the the complex itself is

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not insured against earthquake or flood

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even or all these cat there are even cat

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bonds to cover the damage of solar

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storms and meteorite

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impacts so this is uh our main room

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we're 31 people and uh we invest in

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bonds now bonds are usually very simple

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uh these bonds are called catastrophe

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bonds meaning earthquakes hurricanes

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floods we lose money when they occur so

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uh we're not profiting off a destruction

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we're ensuring uh destruction uh that is

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otherwise too large for traditional

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insurance companies to handle

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comfortably so there's a a lot of

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computation that's involved in

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this this server room is the heart of

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the company the computers link the

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widest range of data sets together and

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continuously calculate the probability

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of a future disaster

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happening plus the damage it might

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because um it's set up so that my older

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brother who used to sit right over there

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can actually see all the status lights

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from his

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desk so it turns out running a server

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room is very complex because you have

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software to see if software is broken

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but then you need software to look at

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that software to see if it's broken and

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usually the the the whole chain doesn't

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work all the time so the best uh

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indicator of failure is actually a red

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light so you want to be able to stand up

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and see the red light

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[Music]

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investors uh around the world are

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looking for something new to invest

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their money in uh and then they find us

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once they find us and allow us to invest

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uh their money then then the really the

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rest is relatively easy I up my hey

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hello right are we on that 10 to 20

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trillion dollar of capital roaming the

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world is urgently looking for returns

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our clients are wonderful they they come

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from every continent from every investor

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class uh in in the world uh so it's

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everything from uh giant National

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Pension funds corporate Pension funds

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Sovereign wealth funds uh insurance

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companies Banks endowments charities

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uh and and Wealthy individuals what

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would happen if normal the traditional

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bonds witness higher

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yields how would it affect the cat bonds

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you know our our Market is if the

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interest rates on other bonds go up as

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they do today the interest rates on cat

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bonds automatically go up as well so the

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returns remain high you know in a sense

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catastrophe bonds are the only thing

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left over to absorb that extra risk the

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the demand for cyber risk coverage is

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going to explode over the next

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year Jon so's clients invest millions in

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his hedge fund and throughout the term

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of the cat Bond they receive an

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attractive interest rate in return but

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first the conditions under which they

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can lose their money are precisely

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defined there are so-called triggers for

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that what the minimum damage should be

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after a wildfire or what the the minimum

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water level should be during a

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flood the trigger was created

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specifically for our area basically the

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modeling firm did the analysis where

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potential storms can come from and they

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analyze about 100 Years of data they

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model 100,000 storms based on all this

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data available

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historically and basically they're

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continuously measuring water levels the

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triggers are in if in area a the trigger

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level the water hits

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7.75 ft or in area B it hits 12.75 ft

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above nava8 then transaction triggers

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another condition for the transaction to

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trigger is that there's got to be an

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aimed

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storm every new hurricane season the

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first tropical storm gets a name

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starting with the letter A until the end

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of the alphabet is reached Anna Bill

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claudet Dany many named storms have

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swept across New York since but the

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water never reached as high as it did

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during

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[Music]

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Sandy it it actually never triggered so

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so far investors didn't lose any money

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on us we hope it is going to happen at

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some point I'm I'm joking but um yeah so

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so far so good um um so far it hasn't

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triggered we we didn't have another

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Sandy so this cat bond is not only a

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solution for New York but Planet Finance

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is happy as well a typical winwin

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situation a catastrophe Bond it's

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brilliant because it's so simple uh

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there was no complexity for the

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investors you know when you when you set

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a high uh water mark there and you tell

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very clearly to the organization if the

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water comes to 8 ft not 8 and 1/2 ft

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then we have no insurance then the

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engineers know how high to make the

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sandbags to design all the flood

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barriers for all the entrances

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to

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so one of the the mitigation measures

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that we put into place after Sandy was

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these floodgates right here these are

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steel hinged flood gate each of these

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Gates weighs approximately um more than

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40,000 lb so approximately 20,000

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kg this Floodgate seemed to be the the

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best combination of cost strength as

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long as we maintain them and replace the

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gaskets these should last for 7,500

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years John's job is to make sure that

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even if there is a big storm there is no

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damage to his tunnel our tunnel I should

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say

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right so my job is to make sure that if

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there is damage we have money to fix it

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right investors who invest in CAD bonds

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they just used to investing in this kind

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of risk that's what they do and to be

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honest because it's such a risky asset

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right um they enjoy much higher interest

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rates that are currently available on

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other assets you know they will invest a

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little little bit in MTA CAD Bond and

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then unless a little bit in the

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earthquake in Mexico cat Bond and a

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little bit in Japanese typhoon CAD Bond

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and this is how they diversify their

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portfolio so things don't hit all at

play18:09

once and they don't lose everything

play18:13

but so there is a market for disasters

play18:16

all around the world each with its own

play18:18

risk and therefore its own

play18:23

price managing catastrophe risk is is

play18:26

very very particular

play18:28

and this was originally what drove my

play18:31

perception of the opportunity here the

play18:34

opportunity not just for profit but

play18:36

actually create a whole another industry

play18:38

that never existed before it was driven

play18:41

by the fact that traditional Finance

play18:43

actually uh is very uncomfortable

play18:45

dealing with catastrophe risk and

play18:48

effectively sweeps it under the rug

play18:50

right they want to think about the

play18:52

opposite which is you know uh the

play18:54

winning lottery ticket hitting it big

play18:56

you know big upside who wants to think

play18:59

about downside so the very first task I

play19:02

set myself to even before I went to

play19:05

Leman Brothers to manage a catastrophe

play19:08

uh Trading Group was to actually

play19:10

redevelop all the mathematics outside of

play19:13

the bell curve right so there it is the

play19:16

bell curve a graph in the shape of a

play19:19

church bell traditional Banks and

play19:22

insurance companies use the bell curve

play19:25

to calculate their

play19:27

risk in the middle you see what is most

play19:30

likely to happen for instance the chance

play19:32

of people paying off their mortgage the

play19:35

sides of the curve show you the chance

play19:37

of what is less likely to happen like

play19:40

mortgages that aren't paid off due to

play19:42

unemployment or

play19:45

illness the business model of Planet

play19:47

Finance is built on the most likely

play19:50

risks not on the so-called tail risk

play19:53

that's where it becomes much harder to

play19:56

make precise predictions because because

play19:58

what are the chances of an airplane

play20:00

flying into the World Trade Center or of

play20:03

a tsunami crashing straight into a

play20:05

nuclear power plant these are the

play20:08

unexpected events the traditional part

play20:10

of Planet Finance isn't prepared for but

play20:13

John so lives off these fickle chances

play20:17

the reason why they're stuck on that

play20:19

framework is because they don't have

play20:20

anything

play20:21

else and it terrifies them because if

play20:24

you can't rely on that uh there is

play20:27

actually no academic framework for

play20:29

dealing with systemic uh catastrophe

play20:31

risks CU if you don't have that

play20:33

framework then you can only deal with

play20:36

emotion or relying on old-fashioned

play20:39

techniques that are that are known not

play20:41

to work and and you need to break with

play20:43

that if you're going to survive uh in

play20:46

the catastrophe Bond

play20:49

[Music]

play20:50

Arena so Jon so's algorithms can be used

play20:54

to calculate the chance of a disaster

play20:56

happening but to me human behavior seems

play21:00

much harder to capture in an algorithm

play21:03

because uh individuals are too wild and

play21:06

wet and

play21:08

non-uniform uh to be conquered with

play21:10

simple

play21:13

mathematics to show you how those Planet

play21:16

Finance algorithms affect planet

play21:20

Earth I travel to the Village of Bonny

play21:25

Dune a close-knit community on the

play21:28

American West

play21:30

Coast a place where the threat of

play21:32

wildfires looms every long dry summer

play21:36

there's Josh hey hey I he you are you

play21:39

going to be there for a few minutes all

play21:42

right I'll be around the community has a

play21:45

village Elder who lives off the wood

play21:47

from the

play21:48

forest Johnny did you see there's three

play21:50

deer in the

play21:52

orchard his wife who grows flowers for

play21:55

weddings and celebrations the St deer

play21:57

might go up over the road we have to Sho

play22:02

some deer out of the garden uh

play22:08

okay and this man who makes his living

play22:11

drilling water wells I think we're set

play22:13

okay oh you want to get fuel you already

play22:15

got

play22:17

it and a teacher who gives lessons to

play22:23

convicts when one fateful August Night a

play22:26

wildfire came St stra at them they

play22:29

decided to fight it

play22:31

themselves it was the night that marked

play22:33

the beginning of the Santa Cruz

play22:35

lightning complex fires which started

play22:38

with as many as 11,000 bolts of

play22:42

lightning in all the 50 years or more

play22:45

that we've been here we have never seen

play22:46

so much lightning and we thought what is

play22:49

going on but we still uh the fire hadn't

play22:53

really become a reality well it wasn't

play22:56

reality it hadn't started started yet

play22:59

and there happens to

play23:01

be some lightning chain

play23:04

Lightning by the mon

play23:07

B got to check this

play23:21

out we looked out our bedroom window and

play23:25

we had never seen anything like it well

play23:27

it was lighting up the sky everywhere

play23:29

wasn't even in one

play23:33

spot there's the wall of clouds coming

play23:36

towards

play23:37

us

play23:39

Uh something's coming something

play23:43

big something's

play23:46

going thunder clouds humid

play23:55

huge I mean it was behind as it was up

play23:58

north of us it was everywhere there were

play24:01

big lightning bolts going off all over

play24:03

the place and that's why there were nine

play24:05

different fires started you know and the

play24:08

Thunder claps were loud they weren't

play24:11

just you know all way off in the

play24:13

distance they were right on top right

play24:15

around

play24:20

us the fire

play24:23

department well we didn't ever see them

play24:25

to be truthful because they were all

play24:27

going going to these different fire

play24:36

locations I took

play24:39

Nancy our daughter and all the kids and

play24:42

everyone up here

play24:46

vacated and then fire was

play24:50

hitting it was hitting the upper part of

play24:52

BU who was coming up that SWAT there and

play24:56

starting down this way he get a chunk

play24:59

here it'll drop every human being is

play25:01

constantly making his own personal

play25:04

assessments how to deal with the risks

play25:06

of

play25:09

Life John was up on the mountain by

play25:12

himself his son had left his daughter

play25:14

had

play25:16

left everybody was gone except for John

play25:18

all the neighbors left John was the only

play25:20

one who stayed there was one night when

play25:22

John was the only one up

play25:24

there he's also kind of this uh

play25:27

patriarch of community and and a really

play25:29

well-respected Elder I would call him

play25:31

and so I felt the need that I needed to

play25:34

go up just to help John if help was

play25:39

needed and when disaster suddenly

play25:42

strikes you can freeze flee or fight

play25:47

most of us even though we're Hermits

play25:49

just kind of were like okay the

play25:50

government's going to handle it let's

play25:52

get out of the way and then when um John

play25:56

Laman decided to stay uh and you know he

play26:01

let us all know that nobody was here you

play26:04

know it's kind of like that uh age-old

play26:07

story like no one's coming to save

play26:12

you ooh cop don't know what he's doing

play26:21

here maybe we're all in

play26:26

trouble but we kept getting uh refused

play26:29

by the police um and uh so we ended up

play26:34

sneaking up

play26:36

here I'm so curious about that sheriff

play26:39

we rarely rarely get cops up here just

play26:41

because you know why

play26:45

Patrol we're not super

play26:48

interesting um yeah to to start we'll be

play26:51

uh revisiting some notable wild many

play26:53

miles away John so and his team are

play26:55

trying to calculate bu the possible

play26:58

damage of the wildfires to see if any

play27:01

triggers could be activated the the tubs

play27:04

fire from 2017 campire from 2018 Wy from

play27:07

2018 and the Santa Cruz Landing fire

play27:10

from 2020 so then let me see here where

play27:11

the where the property counts there the

play27:13

actual property counts are there in line

play27:16

six right you obviously see in green the

play27:19

fire perimeter for the Santa Cruz Fire

play27:21

the CCU fire what what's in green that's

play27:24

the the green is the it's not Forest

play27:26

it's actually the buyer per that's the

play27:28

that's the fire perimeter which I'm I'm

play27:29

going to turn on and off toggle on and

play27:31

off okay and um could you create a

play27:33

different color for that make it

play27:36

red you know what you see is a bunch of

play27:38

yellow dots and each of those dots

play27:40

represents properties in and around this

play27:43

case the Santa Cruz County we know what

play27:47

resources are we at the very beginning

play27:49

of that event we tested a uh a new

play27:52

satellite imagery processing technique

play27:56

to try to predict what the the losses of

play27:59

that fire would be but would you say the

play28:01

burn ratio in those areas total number

play28:04

of structures versus you know it will be

play28:06

quite High it'll be high yes yeah so

play28:09

that's what it would be interesting to

play28:10

find out because now you're basically

play28:12

coming up with a a

play28:14

resource kind of uh dependent view on

play28:16

what the burn ratio is going to be yeah

play28:18

which I like wildfires are very common

play28:21

and they are relatively straightforward

play28:23

events you have ignition you have burn

play28:26

and then you have damage Dage so where

play28:29

most people actually think that the

play28:31

greatest uncertainty lies is in the

play28:34

damage itself right if you if you burn a

play28:37

certain area then how many of the homes

play28:39

are destroyed and there is some

play28:41

uncertainty in there but there's

play28:43

surprising patterns in

play28:45

that maybe those patterns can be

play28:49

recognized in the data but I wonder what

play28:51

good those calculations are to you when

play28:54

the fire is coming your

play28:56

way

play29:00

no one knew how bad it would

play29:02

get all night long I would go up to the

play29:05

top of our property and during the night

play29:08

I kept hearing these explosions that I

play29:11

thought were the propane tanks I mean it

play29:13

was a boom you

play29:15

know Ash was falling on me but it was

play29:19

still tiny breeze on the back of my neck

play29:22

the the little breeze was actually

play29:24

blowing the fire slightly away from us

play29:30

in the morning it came over the

play29:33

Ridge and then I could see trees flaring

play29:41

up

play29:44

um I was walking

play29:47

around

play29:50

and I

play29:55

guess partially because my daughter

play30:00

was

play30:02

emotionally

play30:05

um I guess she was tweeting and calling

play30:10

people telling them to get me out of

play30:16

here it was a very surreal

play30:20

experience rodents uh mice and rats

play30:23

literally like running through your legs

play30:25

just fleeing the fire

play30:28

and then the um butterflies a lot of

play30:31

Monarch butterflies were just they were

play30:32

just landing on me in the woods and they

play30:34

didn't

play30:35

seem I mean how can you read a

play30:38

butterfly's uh personality but they

play30:40

didn't seem panicked you know the way a

play30:41

butterfly is just so light in the way

play30:44

they live it seems like and so they're

play30:46

just kind of cruising along and they

play30:47

would land and then they would move on

play30:49

but there was a lot more than I have

play30:51

ever seen in the woods and obviously

play30:53

they were just moving away from the

play30:56

danger

play30:57

they don't have necessarily decent roads

play31:00

coming in going out calfire won't be

play31:02

able to reach there so the burn ratio is

play31:05

going to be 60% should yeah

play31:07

[Music]

play31:08

[Applause]

play31:11

right the fire was finally starting to

play31:14

come around and approach

play31:17

[Music]

play31:19

us anybody that knows how to go towards

play31:23

the

play31:25

Empire no I don't

play31:27

no I think I realized probably on the

play31:30

second day of fighting the fire that we

play31:33

were going to control it as long as the

play31:36

weather didn't

play31:38

change the information was so poor from

play31:40

social media under their iPhones they

play31:43

were seeing pictures

play31:46

of that very aggressive

play31:56

fire

play31:57

and so from social media there was these

play32:00

satellite images that showed what they

play32:02

said were hot spots of where it was

play32:04

burning and where it wasn't so you would

play32:05

you was kind of an overlay of the

play32:07

Topography of the land and it just had a

play32:09

bunch of dots the red dots where it was

play32:12

really hot orange wasn't as hot yellow

play32:14

maybe it had already burned and then

play32:15

green was okay and when you looked at it

play32:17

it showed red dots all over our house

play32:20

and all over our

play32:22

neighborhood people were hyperfocused on

play32:24

this image and they're just like it's

play32:25

burning right here and then we would get

play32:27

texts from them say from people in town

play32:29

saying it's burning on back Ranch Road

play32:31

you need to go check it out you need to

play32:33

get out that's your only way out and we

play32:34

go out to back Ranch Road there was no

play32:36

fire and we say there's no way it's

play32:38

burning on background so we can see the

play32:40

fire it's right here you know and then

play32:41

we would tell them and then no it's

play32:43

burning on Warren Drive you need to go

play32:45

get out and then we'd go look and be

play32:47

like no it's not burning there

play32:50

either and it wasn't until I think

play32:53

probably 3 or 4 days in we realized that

play32:55

the satellite damage was transposed

play32:57

improperly it needed to shift East by

play33:01

about a mile or

play33:03

[Music]

play33:09

so the fire went around I came up the

play33:13

backside and all of a sudden we got a de

play33:16

A

play33:17

desperate hollering there was a draw

play33:20

there it had come up and it caught one

play33:23

of his out buildings on

play33:25

fire

play33:28

by the time I got up

play33:32

there it had taken off it was really

play33:35

burning we were going to stop

play33:38

and it literally sounded like some Jeet

play33:42

plane preparing to take

play33:49

off and that's when I

play33:55

decided you know this is ridiculous

play33:58

let's get the bulldozers and we push

play34:01

this fire break

play34:06

through and with those bulldozers the

play34:08

Bonny Dune residents create a wall a

play34:11

fire break between themselves and the

play34:14

approaching

play34:16

Flames it almost looks like that upper

play34:18

left lobe yeah like it go to the left

play34:21

there yeah that lobe right there that

play34:23

looks like they were the ones that

play34:25

actually successfully built a perimeter

play34:29

so I'm going to I'm going to zoom in on

play34:31

that and actually see if I can see uh

play34:33

the and then the human behavior is a

play34:35

fundamental part of the modeling it's

play34:38

actually already taking into account

play34:40

that there's millions of sometimes very

play34:43

stubborn and independent especially here

play34:45

in the US uh homeowners who are defying

play34:49

orders to leave and evacuate are running

play34:52

around you know putting up boards over

play34:54

their windows and defending their homes

play34:57

if it weren't for that behavior uh then

play35:00

the losses would easily be double or

play35:02

triple what we're observing so it's

play35:06

actually in a sense priced in this human

play35:10

behavior right so John so has already

play35:13

factored in this behavior of large

play35:16

groups of people but what about the

play35:18

behavior of a single

play35:21

individual because whether our village

play35:23

Elder can be insured against wildfires

play35:26

is De decided today by

play35:32

algorithms in New York a finch startup

play35:35

is confident that it can calculate the

play35:38

risk of a wildfire down to the smallest

play35:40

detail and therefore determine whether

play35:43

something is insurable or not and the

play35:45

first version of our model didn't really

play35:47

take into account the randomness of

play35:49

lightning so it didn't really consider

play35:51

lightning as as a as a major variable um

play35:56

so the

play35:57

reason we exist is

play36:01

because the old way of doing things is

play36:03

isn't really working anymore that's the

play36:06

traditional way of understanding risk is

play36:10

let's look at this spot on the map this

play36:12

ZIP code and we look and say okay over

play36:15

the last uh 500 years this has burned

play36:18

five times so it has a one inone 100

play36:21

chance of

play36:22

burning and then you price it

play36:24

accordingly the problem is

play36:28

it's right there in the word climate

play36:30

changed see right here negative4 is

play36:34

Extreme drought right negative3 is a so

play36:37

you can't really use the last 500 years

play36:40

and expect to be able to predict the

play36:42

next 10 years off of that you have to do

play36:45

a much

play36:46

more bottomup physical model uh using

play36:50

machine learning looking at the reality

play36:53

of that place now this is what the trees

play36:56

look like this is this is what the

play36:57

weather looks like this is uh where the

play36:59

fire brakes are this is how close the

play37:01

closest fire engines are and all that's

play37:04

being done by the the model the AI model

play37:07

so it's to give you an idea the

play37:09

traditional way of doing it they might

play37:11

run a 100,000 simulations to get to that

play37:14

one and 100 number they might say run

play37:18

100,000 different simulations and say

play37:20

okay I I think that this has a one in

play37:22

100 chance of burning we're our machine

play37:25

learning models our mod models they're

play37:28

running

play37:29

682 billion

play37:32

simulations to build a well functioning

play37:35

AI model out of

play37:37

682 billion simulations you need all

play37:40

kinds of things I'm losing money I don't

play37:42

know how to model this anymore the

play37:44

models aren't working I'm going to leave

play37:45

I'm just I'm not going to do this

play37:47

anymore first of all you need

play37:48

investors's money where else can you go

play37:50

with but also brains with a background

play37:53

on Wall Street and I started my career

play37:55

at Comm Sachs and and I'm a doctor as

play37:57

well a climate

play38:00

scientist a mathematician a probability

play38:03

that the fire will spread to a greed in

play38:05

California and the founders who

play38:07

zealously promote their AI model there

play38:10

is significant Alpha that we could find

play38:13

in the industry as we've seen as they

play38:15

all pull back because they say all right

play38:17

we have no idea what the future's going

play38:19

to look like there's a far more measured

play38:21

and datadriven approach that that we

play38:23

could really take towards it yeah a lot

play38:26

of the traditional finances so places

play38:28

like Pension funds and hedge funds and

play38:31

and family offices looked over and said

play38:34

well here's this whole world that that's

play38:36

writing insurance policies it's not

play38:38

focused at all on the stock market or or

play38:40

you know in Commodities or something

play38:42

like that they're just focused on

play38:43

whether or not a hurricane happens an

play38:45

earthquake happens or you know Wildfire

play38:47

happens and why that's so valuable is

play38:50

because it's a non-correlated asset and

play38:52

what I mean by that is the stock market

play38:54

can be doing whatever it is today that's

play38:57

almost completely unrelated to whether

play38:59

or not the wind is blowing in Florida

play39:00

and there's a hurricane happening and

play39:02

one of the best things you can have it

play39:04

is an investor is something that's

play39:05

non-correlated because even if you think

play39:07

you're Diversified in your portfolio but

play39:09

it's all in the stock market well if the

play39:11

stock market blows up tomorrow then

play39:13

everything's going to go

play39:15

down so the appeal of a cat bond is that

play39:19

it's a completely different type of

play39:22

risk even if Wall Street crashes

play39:25

tomorrow the cat Bond will still bear

play39:28

High interest

play39:33

rates we're headed out to last chance

play39:35

road to to get people water um we work

play39:39

on work on water wells and uh repairing

play39:42

water wells virtually every water well

play39:44

out here

play39:47

melted fire came through

play39:50

there uh very fast and very hot very

play39:54

different than the than the fire that we

play39:56

did dealt with at our

play40:01

home sorry for the dirty

play40:03

windshield it's only going to get

play40:04

dirtier

play40:06

today it used to be you couldn't see any

play40:09

of this this this was all

play40:14

trees that was a house there there was a

play40:16

house right

play40:19

here that one

play40:25

survived

play40:28

[Music]

play40:32

one gentleman died out

play40:38

[Music]

play40:42

here he was an elderly guy who went back

play40:45

in to get stuff from what I heard and he

play40:47

didn't make it out he tried to hike out

play40:50

through the state park and he didn't

play40:52

make

play40:54

it they found him some some of the

play40:56

neighbors found

play40:57

[Music]

play41:25

him

play41:39

after the disaster there is nothing of

play41:42

value left but when lightning strikes a

play41:45

bone dry forest or when a hurricane is

play41:48

on its way to the coast and the extent

play41:51

of the insured damage isn't clear yet

play41:54

that's when Jon so swings into

play41:58

action whether it's a a hurricane

play42:01

wildfires or an earthquake that just

play42:03

happens in the middle of the night I get

play42:05

a phone call and I'm woken up we have

play42:07

software and tools in which we bring up

play42:09

our portfolio and immediately access the

play42:13

impact to the portfolio from the event

play42:16

so um if I zoom in if it looks like a

play42:18

trigger is activated and as an investor

play42:21

you could lose all your money then you

play42:23

naturally want to get rid of your cat

play42:25

Bond as soon as possible by putting it

play42:27

up for sale that's when interesting

play42:30

opportunities arise if you're not able

play42:32

to estimate the the losses of of a live

play42:35

event like this then you have to

play42:37

question your ability to estimate the

play42:40

risks hypothetical risks to this Bond

play42:42

and pricing it so it's a it's a little

play42:45

bit like a Formula One

play42:47

race worldwide very few players have the

play42:51

knowledge computing power and reaction

play42:53

speed necessary to play the game LEL

play42:57

just before the fire and then as soon as

play42:59

possible I wonder whether that would be

play43:00

it a typical uh catastrophe bomb

play43:03

portfolio will have roughly 200

play43:05

positions in it what do you mean uh

play43:08

we'll have 200 different catastrophe

play43:10

Bonds in it these data and so in a major

play43:14

event um roughly 80 to those are

play43:17

potentially exposed to the event that

play43:21

narrows it down from 200 to

play43:24

80 and then um are immediately

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estimating what the intensity of the

play43:29

event is going to be and and therefore

play43:31

what the financial losses will

play43:33

be and then from that next cut the 80

play43:37

bonds that are at risk suddenly Narrows

play43:39

down to 10 so that final list of bonds

play43:42

that are potentially at risk the seller

play43:45

really just wants to sell lot of media

play43:47

attention we saw a lot of like a hot

play43:49

potato no one wants to burn their

play43:50

fingers on these cat bonds are now being

play43:53

resold for less and less

play43:56

money the uh the market maker will call

play43:59

us and say I've got an offer on 5

play44:03

million of this Bond at 60 cents on the

play44:06

dollar so normally if the bond was not

play44:08

in trouble it would trade at full value

play44:11

uh 100 cents on the dollar but it's

play44:13

offered at 60 cents on the dollar so if

play44:16

JN so thinks he is better informed than

play44:19

the rest of the market and he is sure

play44:21

that the trigger won't be activated and

play44:23

he won't lose Millions then he can seize

play44:26

his opportunity and buy a cat bond for a

play44:29

bargain

play44:30

[Music]

play44:40

price it's a it's a tricky business

play44:42

because roughly every other year you

play44:44

have a catastrophe bond that loses money

play44:48

and I've been doing this for over 20

play44:50

years so we've lost um a lot of money on

play44:54

on on those cumulatively

play44:58

we've made more than we've lost on net

play45:00

but we've had significant loss

play45:02

experiences for

play45:04

sure so if a cat bond is really

play45:07

triggered you lose a lot of money as an

play45:11

investor therefore Jon has to constantly

play45:13

test the most recent climate projections

play45:16

against his own data and calculate the

play45:19

extent of the potential damage of those

play45:21

projections so here are the different

play45:25

end of century temperature projections

play45:27

so obviously the 8.5 scenario is the

play45:29

highest okay so 2Β° by 2050 45 40 Etc and

play45:34

we tweaked those the historical storms

play45:36

and ran it through their model and on

play45:38

average that increases by 3 1.34 so 34%

play45:42

you were so it's a 3 no it's a 35% 34 in

play45:46

what I okay 34% increase in in damage

play45:50

right in damage and what' you do did you

play45:52

oh that's annualized and you an

play45:54

annualize it from today or from 2020 oh

play45:59

okay the world is getting riskier for

play46:03

sure so that is driving growth in our

play46:07

Marketplace by our

play46:10

estimation uh the the world needs

play46:13

roughly 500 billion of catastrophe of on

play46:19

finance largely it's for the time being

play46:22

uh a US centered Market but the

play46:25

potential worldwide is is immense you

play46:28

know whether it's a flooding in Germany

play46:31

uh flooding in Asia particularly in

play46:34

China you can calculate what the

play46:36

exposure is because in the end it's

play46:38

physical so really you you need

play46:41

effectively Google Earth and to look at

play46:44

all the property around the world and

play46:46

understand its vulnerability to

play46:48

earthquakes hurricanes and floods and

play46:51

you can do the

play46:53

calculation right

play46:56

but what is the bottom line for the

play46:58

people of Bonny

play47:02

Dune for a lot of people up here it was

play47:05

a huge surprise to them that the firemen

play47:08

didn't

play47:09

come I think it really is a numbers game

play47:12

on people and then the amount of wealth

play47:15

within an entire community so you know

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we might have some affluent community

play47:19

members but it's not the Silicon Valley

play47:23

or you know it's not all affluent Comm

play47:26

so it's not worth it for them I think it

play47:28

must

play47:29

be uh how close it is to a city that you

play47:32

know that they care about for most of my

play47:35

community it was the first time that

play47:38

they realized that they were not

play47:41

significant um and uh that that they

play47:45

were deemed easily

play47:48

disposable not significant disposable

play47:52

the fire department wasn't willing or

play47:54

able to save many of the houses so cat

play47:57

bonss at Bonny Dune no one noticed their

play48:01

existence they only work for you if you

play48:03

own insurable property this is bunny

play48:06

Doom yes uh yes

play48:08

T Last Chance

play48:13

Road last

play48:17

chance Last

play48:20

Chance

play48:24

no yes this still shows us like a

play48:26

extremely high risk we see that

play48:29

historically this place has burned in

play48:31

the

play48:32

past so actual model shows that this uh

play48:38

Bon do location uh is like

play48:41

1.18% chance of burning so that's

play48:44

actually within 95 percentile in terms

play48:46

of the risk yeah so 95% of the

play48:50

California has lower risk than this

play48:52

particular location the distance to um

play48:56

Wildland and Uber interface is to to

play49:00

close and then the Palmer jot uh

play49:04

severity index is too low and those are

play49:07

the reason behind um we think this

play49:11

location is actually too dangerous for

play49:13

to

play49:24

Ure

play49:26

[Music]

play49:29

so this is my little

play49:35

bunker I've got four compressed air

play49:38

bottles there that are full of

play49:42

air I'm never going to if I stay in here

play49:45

I could stay in here hours with those

play49:47

tanks with no outside air but my house

play49:49

would be burnt down and I've got to come

play49:52

out of this as soon as that big wave

play49:56

Burns over I've got to be out there

play49:58

putting out the fires but anyway this is

play50:01

just a little there a little insurance

play50:04

policy is what it is you know I

play50:06

doubt 90% of the time I'm never going to

play50:09

use this but if if that one two five% of

play50:13

the time I need it it could save my life

play50:16

so that's why I got the compressed air

play50:18

tanks and the water and and it also

play50:21

gives our loved ones the Assurance or

play50:23

the feeling that oh yeah Grandpa's got

play50:26

it together he'll get in his little

play50:28

pizza oven and sit there and eat pizza

play50:31

you know so yeah and I've got a hoses

play50:36

and I've got a little can of gas there

play50:38

so I'm I'm Ready the people of Bonny dun

play50:41

ensure their own

play50:44

lives and rebuild them if they need

play50:48

to because if you live in Bonny dun or

play50:52

by the mass River or in Pakistan you

play50:55

you'd better build your own bunker or

play50:58

[Music]

play51:03

Levy if there's anything I've learned is

play51:06

that it is hard to calculate the risk of

play51:08

a war a pandemic or climate change yet

play51:12

on planet Finance even this kind of risk

play51:15

is a good business model because the

play51:17

capital that's roaming the world is

play51:20

always looking for a way creating new

play51:22

arenas for profit

play51:28

you could call it perverse but for a few

play51:31

years now the demand for cat bonss

play51:34

actually exceeds the expected

play51:37

[Music]

play51:54

catastrophes