South Africa is still reeling from the significant loss of life, and housing and infrastructural devastation, of the floods that rocked KwaZulu-Natal in April. The harsh reality is, this will happen again. Floods, wildfires, tropical cyclones and other climate change-related events have been increasing and will continue to increase in the future. Which begs the question - can risk modelling play a greater role in preparing communities for what’s to come?
The short answer is yes. The insurance market relies on predictive models to calculate risk and therefore, insurance premiums. Understanding and being able to quantify the risk underlying different perils allows clients and underwriters to better prepare for devastating events due to these perils.
A difficult-to-predict peril
By all accounts, flood is a challenging risk to model. The various types of floods differ based on the nature, location and severity of the associated storms. Added to this, models must accommodate differentiating perils, vulnerabilities and defence information of the specific risk location.
Insights from MS Amlin in 2017 following the devastation of Hurricane Harvey in Texas, USA, noted that flood is such a localised peril, that it is notoriously difficult to model.
It referred to the fact that in the UK, severe winter storms in recent years had caused billions of pounds’ worth of damage, some of which was not recoverable. This was as a result of claimants being under-insured or having no cover at all, as a significant number of claims came from areas previously modelled to be low risk. In other cases, risk models failed because above average rainfall conditions were quickly compounded by a lack of adequate runoff and burst rivers, which hindered the models’ ability to accurately predict the flood outcomes.
Flood has become such a significant risk in the UK that the UK Foresight report estimates that the increasing risk of urban flooding could cost anything from 1 to10 billion pounds a year by 2080.
Using technology to better predict risk
That being said, it is not impossible to model flood risk. JBA, a leader in computational flood modelling, offers probabilistic flood modelling on a global scale. It models at 30m resolution for river and surface water flooding for every country around the world, using cutting-edge flood maps. This enables both the insurance and non-insurance sectors to better understand and manage flood exposure and risk at any location worldwide.
Ground-breaking technology like this, combined with increasingly available data on the impact of flood waters on infrastructure and vulnerabilities in the urban infrastructural system during flooding, are powerful tools in helping insurers prepare their clients for flood events, mitigating damages and losses.
At RSIS, we have access to these state-of-the-art probabilistic models, and working with JBA, we are able to communicate to our clients their exposure to flood risk critical to risk mitigation, underwriting and preparation.
Looking back at the floods in KwaZulu-Natal, there was a definitive opportunity for re/insurers with clients in the affected areas to draw on the data available to them and advise their clients of the severe weather and potential for destructive flooding that remain exposed to. Gauging from the devastation that occurred, it seems communities and businesses were ill-prepared for the events of that fateful day.
From an insurance perspective, the risk could have been largely mitigated and better managed if advanced flood risk modelling had been used and the data correctly applied.
Where to now?
It’s clear that the first thing insurers with clients in the high-risk flood areas of KwaZulu-Natal need to do is improve their access to accurate flood modelling, based on their clients’ exact geographical locations.
Then, using that data, these clients’ risk for flood should be re-evaluated, and well-informed, strategic decisions taken about how the business is covered.
Based on this, insurers can either load premiums or share the risk with an experienced reinsurer, which would reduce their risk exposure and significantly reduce the potential for losses.
KwaZulu-Natal has experienced three devastating extreme weather events in recent years: a tropical cyclone in 1984, the floods of 1987, and severe coastal erosion as a result of a storm swell in 2007. Flood-based events in this province will happen again, it is only a matter of when. The difference is next time, there’s no reason for businesses and communities not to be better prepared.
Thato Raboroko is Head of Analytics for Reinsurance Solutions Intermediary Services (RSIS), a niche, agile reinsurance broker providing focused, trusted reinsurance solutions to insurance clients across Southern Africa.
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