The Fourth Industrial Revolution, a term that encompasses technologies such as artificial intelligence (AI), the internet of things, robotics and big data will lead to profound changes within all spheres of underwriting. Since the early days of what is now the modern (re)insurance business, underwriting has been at the very core of the insurance industry.
Traditionally, the analysis of historical data for the purpose of risk assessments has been at the centre of (re)insurance underwriting when evaluating clients’ risk exposures. In this context, tapping into the potential of big data and data analytics promises to be highly relevant for the future of the insurance industry. With a look into the future, technological developments such as the internet of things will enable (re)insurers to collect more fine-grained data and to make better-informed decisions regarding the assessment and management of risks.
Underwriters working in the primary insurance and reinsurance sectors will benefit from increased automation of more mundane day-to-day workflow processes and enhanced analytical capabilities in the wake of technological advancements. An enhanced access to real-time and high-quality data will lead to an acceleration of the underwriting process and an improved degree of accuracy in assessing and pricing risks. The proliferation of quantifiable metrics for more sophisticated risk-profiling will be of crucial importance to facilitate more efficient data-driven decision-making. An increase in analytical and computing capabilities will assist human underwriters to better understand risks.
In the long term, opportunities arising from technological developments such as AI, machine learning and predictive analytics will enable underwriters to analyse patterns in large sets of unstructured data in a more efficient and effective way. In turn, underwriters will be able to dedicate time to more demanding and challenging tasks which require advanced analytical skills and professional expertise.
In particular, the digitisation of (re)insurance underwriting will significantly reduce transaction and information costs and facilitate the ease of doing business. The introduction of straight-through processing facilitated by the automation of workflow will reduce back-office costs and contribute to a lower combined ratio as an indicator of underwriting performance. A reduction of the costs of collecting and gathering information will aid carriers in administrating, assessing and pricing risks more accurately and efficiently. At least, in theory, the digitisation of underwriting should promote the purchase of (re)insurance as companies will be able to pass on cost savings by charging lower premiums to their respective clients. As a result, (re)insurance cover should become more affordable to potential policyholders and cedants.
The current technological revolution will also lead to increasing insurance cover in emerging markets and developing countries. Profound technological changes in the insurance industry will play a crucial role in narrowing the global insurance protection gap. Currently, the vast majority of economic losses remain uninsured. The population in many developing countries and emerging markets suffer from a lack of societal resilience in the wake of natural disasters, climate change and/or pandemics. Technological innovations and the rise of digitisation may indeed turn out to be crucial in fostering the resilience and economic recovery of vulnerable communities in the aftermath of natural disasters.
The digitisation of insurance underwriting has high potential in contributing to the narrowing of the protection gap in developing countries and emerging markets. Insurance penetration should increase in low-income countries as insurance cover becomes more affordable and awareness of the benefits of insurance gradually rises within the local population. The digitisation of underwriting should, therefore, contribute to enhanced resilience and protection of vulnerable communities and businesses exposed to disasters and ensuing economic disruption.
Currently, insurance underwriting requires the collection and analysis of detailed information on a granular level and is, therefore, resource intensive, time-consuming and costly when applied on a grand scale. In combination with the revolution in digitisation, underwriting may be significantly simplified by the use of parametric insurance which is also known as index-based insurance.
In the case of more conventional types of indemnity insurance, the size of the actual full loss determines the monetary amount of the pay-out which requires rather complicated and laborious loss adjustments. By contrast, the pay-out in parametric insurance is determined by an objective metric. The insured purchases a contractually specified amount of cover for a peril and pay-out is triggered by a certain pre-defined event. The premium rate is usually based on the hazard exposure in a delimited geographic area as well as the selected level of coverage.
Furthermore, it is possible to combine the underwriting process in parametric insurance with different kinds of relatively affordable technological innovations such as remote sensing, geographic information systems and mobile technologies to collect data on the ground and facilitate the assessment of risks. As a result, insurance cover should be made more accessible to vulnerable people living in risk-prone areas by saving costs and substantially reducing levels of premium.
The ‘fourth industrial revolution’ has drastically changed the insurance sector, so much so that traditional risk assessment has been “eclipsed” by machine learning and real-time geo-intelligence, according to a new report from Axco.