‘Tipping points’ are events that push a system over the edge into a new attractor state (see also ‘attractor states’). They are the final straw, giving a pattern that last bit of energy needed to leap into a new “normal”. Think about boiling water for example. Every second more and more energy is transferred into the water, making its molecule move faster and faster. At some point, some last bit of injected energy will finally enable them to leap into the air, transferring the water from a liquid into a gas state. That bit of extra energy is not the cause of the transformation, rather it charts the point in which the system reaches a certain critical mass of destabilising energy.
And this is the significance of tipping points – they are not causes but rather random occurrences that help systems cross certain thresholds. Thus, while the fall of Lehman Brothers in 2008 is rightly associated with the financial crash and the world recession that followed, it was not the cause of the crisis. Rather it provided a tipping point that pushed the system into a new reality. Lehman’s announced bankruptcy on the 15th of September 2008, sent new signals into the market crushing any last held assumptions about the US property market, global finance, and investment banks. Yet, the systemic tensions undermining the old economic structures and the behavioural patterns they have informed had been building up for years.
All systemic patterns whether deemed good or bad, harbour their own demise. This demise is fuelled by the gradual yet inevitable emergence of contradicting trends from within, overtime creating unsustainable tensions that allow certain random events to finally tip them over. We cannot predict exactly what the tipping points will be, but we can learn to expect them. In the case of the subprime financial crisis for example, systemic contradictions had been slowly building up for over a decade.
As the mortgage market was deregulated to allow more mortgage lenders to help more ordinary people get on the property ladder, the US housing market boomed. Small mortgage landers could then also sell on their mortgage contracts to bigger financial investors such as banks. For them it was a way of getting rid of their initial risk and raising more capital to help new home buyers; for the investors that bought them, it was a “low risk” way of getting into the property market. Even if a small number of people would not be able to pay back their loans, as they were bundled with so many others, the risk for the whole group – the bundle failing, seemed minimal. Furthermore, the steady rise in house prices meant that the actual assets backing such loans could be sold off without a loss. So far so simple.
However, the possibility to trade these new Asset Based Securities (ABSs) allowed further financial innovations to take off. As players across networks naturally do, those who bought these securitized bundles thought up further ways to recombine them into new financial products they could sell onwards. After all evolution in innovation is all about the recombination of existing elements. Overtime however, as in the old game of “Chinese whispers”, an ever growing information gap began to emerge between the inherent risks of the initial loans, and that of the overall processed financial products they had become part of. Most importantly, the new trading patterns altered incentives and constraints for local players thereby gradually reshaping the market itself.
With ever growing demand for their mortgage contracts, the risk element within lending seemed to have disappeared, incentivising mortgage providers to simply maximise mortgages sales. Their local business model was simply turned on its head. Instead of selling mortgages to home buyers, they were actually selling approved mortgages into the emerging ABSs financial processing machines. All they needed was to find new potential home buyers, and when those ran out, find literally anyone, including those nobody ever thought of giving money to before – enter the subprime lenders. From their own local system perspectives, the risk thresholds, i.e. the likelihood their customers might stop paying those mortgage payments became almost irrelevant. Moreover, once bundled together the collected pools were again “de-risked”, surly not everyone would default on their loans. Thus from their end, giving out NINJA loans - to people with no income, no job, and no assets, made “complete sense”. Of course, like any complex ecology, each player was operating locally, constrained by his or her own immediate knowledge and cognitive biases. Thousands of bankers were independently looking to bundle mortgages sold by tens of thousands of independently operating mortgage providers, handing out millions of mortgages to independent home buyers. All were driven by a self-organized construction binge catalysed by cheap money channelled through an endless flow of new mortgages. None could see the emerging unsustainable bubble as none had the full picture. After all, no player ever operates at the systemic level.
Still as Michael Lewis brilliantly captured in ‘The Big Short’ some very few players did start to get suspicious and became what can be referred to as ‘avalanche hunters’ – players seeking out tipping points. As complex patterns tip over they release huge amounts of energy. Harnessed in the right way, they can make the players who brave them very powerful, or in this case very rich. All that is required is more thorough research into the unsustainable tensions building up in a system and the strategic means to position oneself to take advantage of its imminent collapse.
Michael Burry for example, an ex-neurologist with Asperger syndrome who set up an investment fund, actually found the patience to read through the thousands of mortgages bundled in one securitized bundle. Some lenders income and background just did not add up with the amounts of money that they have been given. Steve Eisman, another outspoken fund manager, took a field trip to see for himself the kind of assets that were backed up, finding half-finished new neighbourhoods built in the most unlikely of places, with home owners seemingly in over their heads.
Both Burry and Eisman, independently and against the judgement or support of all their peers, (Burry almost had to close his fund due to investors revolt), reached the same conclusion. An unsustainable tension dominated the system. As financial players, they did the only thing they could do – short the housing market. Their weapon of choice was the credit default swap (CDSs) basically an insurance taken out against the fall in price of those securitized bundles of mortgages. Once the system tipped over, their bets paid out, making them hundreds of millions of dollars in the process.
SO WHAT does that mean in terms of pattern analysis?
Tipping points are not causes but signals of change. They thus provide players with invaluable information about the tensions and contradictions that naturally build up even in the most seemingly stable of systems. Whether system changers or avalanche hunters, players must be able to identify unsustainable tensions, and consider alternatives paths to systemic collapse. Given that systems can continue to exist in contradiction for quite a long time, creatively thinking up potential tipping points at different intersections, can provide the basis for designing early monitoring systems. But more on that in Building Blocks.