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Digital ecosystems and AI: The enablers for Asian insurers’ future growth

Mobile interaction data can unlock untapped markets in Asia

Today more than two thirds of the world’s 7.6 billion population have a mobile device, and well over half of the world’s population is online and connected to internet.1

As technology becomes more deeply embedded in people’s lives, we are also observing a vast amount of new data sources being gathered. The amount of data generated automatically, inexpensively and non-intrusively is growing exponentially, so too are new tools to analyse and extract insights from these data. This creates new opportunities for insurers and their digital partners to engage more effectively with customers.

Swiss Re’s recent Asia Health Protection Gap research findings also shows that 83% of the respondents are willing to share their data generated from wearables and fitness apps with insurers. Further, 88% of the next billion middle class will emerge from Asia, and most of these Asian unbanked/uninsured population will already be using their mobile devices to transact.2 Therefore, companies that are able to  transform their mobile/digital ecosystems data into risk insights quickly, while tailoring products and services for quick launch in the market will be the ones driving the future growth of insurance.

AI predictive models maximise the value of data

It is fascinating to see how fast financial services leverage the initial personalised scores built by big tech giants in China to onboard their new customers and enhance their more traditional risk models. Some insurers in China are also using technology to offer services outside the boundaries of traditional insurance through digital ecosystem partnerships. This process has enabled them to leverage new customer interactions and gain deeper risk insights to further personalise their product and services proposition to improve the insurance customer journey. Often times the personalisation of products also requires dynamic risk management features where a strong reinsurance partner is proven to be valuable.

Building stronger partnerships with digital partners, accessing more customer data and digital interaction while leveraging developments on artificial intelligence and cognitive systems will enable insurers to activate dynamic risk management. Artificial intelligence, machine learning in particular, is already being used by insurers across the value chain to optimise processes and customer services. There are already many examples globally of how AI is bringing value to insurers across the value chain, from targeted sales with micro-segmentation (proposing particular products to the hyper-targeted audience), lapse prediction, claims triage/automation, to fraud prediction. However, with new technology comes also new challenges and risks that need to be well managed for adoption at scale, such as algorithmic malpractice, data bias, cyber risk, decision process transparency and auditability, just to name a few.

Current AI-enabled predictive models solutions across the value chain – Transforming customer touchpoints/data into (risk) insights

While the industry is only starting to leverage AI to enhance the existing risk models to build more personalised products and services across Asia, Swiss Re have already implemented some pioneering predictive models to help insurers leverage data from their digital partners and improve risk management.

Case study – Parametric products, predictive underwriting and claims analytics

Last year, Swiss Re together with our clients and digital partners across the region launched many tech-enabled innovative solutions. Just to name a few: the first wellness product in India, the first dynamic pricing product for diabetes in Thailand, the first ‘parametric health’ product in Singapore for gestational diabetes, and parametric products for flight delay and typhoon.

Amongst these solutions many were AI-driven projects, with our business experts and data scientist teams working closely with insurers. For example, we have implemented the predictive underwriting models to help improve customer segmentation based on their current and future risk to simplify the onboarding journey for 30 per cent of their end-customers, while not increasing the price of their premium. We also helped create more accurate prediction of claims costs to 95 per cent to ease the impact of raising medical expenses. We have also created AI prediction models on multiple risks such as flights delay, typhoon/hurricanes, earthquakes, etc. that forms the basis of our parametric platform offers and enriches our risk knowledge day by day.

These are just some examples, where our data science and smart analytics capabilities, alongside our risk understanding have provided our clients with new perspectives when analysing data, and ultimately improving their risk management. We are also doing research and pilots in new technology, such as distributed ledgers and federated learning that will accelerate opportunities for collaboration by providing secure platforms to build models, while not having to directly own or access the data. Find out more about our collaboration with We Bank on federated learning.

As insurers gain more access to new data from their customers through their digital partners and offer better tailored products and services to the Asian customers, we are expecting more insurers onboarded to fine-tune these AI-enabled risk models. This is enabling the industry to gain more risk insights and provide more personalised product and service to the new generation of Asian customers. Hence, we look forward to working more closely with insurers and our partners to close the protection gap.

1We Are Social, Digital in 2018 Report
2Source: World Bank, Kharas H 28. 02.2017 The unprecedented expansion of the global middle class