Laws of large numbers: Use of big data in Asian Insurance Markets

15 Aug 2016

Asia comes from a somewhat different starting point to other developed insurance markets. Insurance penetration has historically lagged Western economies – meaning that the industry is less encumbered by legacy systems. This provides both room for growth and innovation. This report analyses the latest developments in data analysis and application in Asia and explores potential risks and opportunities for the insurance industry.

Swiss Re and external experts have analysed how big data is changing the risk landscape in agriculture insurance, healthcare, occupational accidents and diseases. We also discuss data protection and privacy in Asia as compared with Europe and the Americas. We further investigate experiments being undertaken by Chinese insurers trying to make up for data shortfalls through innovative partnerships with other industries.

Given the fast growth of IT infrastructure and technologies in Asia, this report also provides a good reference for other markets around the world.

Key content of this report includes:

  • Data protection and privacy

    Data on individuals may be physically collected in one jurisdiction, stored temporarily in another one and processed in yet a different one. Personal data-protection and privacy laws differ across different countries. These distinct legislations and different compliance postures make the realisation of potential benefits from big data into a serious challenge for global companies. The European Union and the United States, for instance, have very different and sometimes irreconcilable positions in terms of information privacy rights and related regulatory practices. Will these differences in information privacy open up unexpected opportunities for Asian countries to attract new business from the other two giant regions in the world?

    Big asymmetries in the era of big data
  • Big data and crop insurance in Asia

    Administering crop insurance in Asian countries with small fragmented agricultural land holdings is an expensive affair, but costs can be substantially lowered through the introduction of index-based or parametric insurance schemes. These are managed, however, by means of relatively generic data measurements that do not always capture the experience of individual farmers. The introduction of new data technology services into agriculture, in the form of increased sensor data volume, refined data processing, and far greater mapping accuracy, can provide a much more detailed picture of risk at the farm level. Technology can provide a rich source of underwriting and loss-assessment data for insurers to improve their index as well as indemnity products. Initiatives across a variety of players are, however, necessary to ensure that data reains accessible in order to reap the full benefits.


    Big data in China
     
    Crop insurance
  • Interesting experiments on big data in China

    The potential of big data in the Chinese insurance industry is clearly considerable; although it is currently hampered by the significant hurdle of the relative lack of existing data in the market. The data shortage is a direct result of the short history of the insurance industry; and as a result of the hitherto limited capabilities of insurers in data management, analysis and processing. Nevertheless, Chinese insurers are now approaching big data with enthusiasm. The cross-industry use of data sources is seen as one of the most promising experiments currently being undertaken in the sector. By utilising the strength inherent in underwriting and risk control, insurance companies may unlock the untapped demand for insurance by collaborating with companies in other industries who have high-quality data.
  • From personalised medicine to personalised prevention

    Personalised prevention is a new, data-driven approach to health care, providing advice at an individual level to best achieve desirable health outcomes. Using big-data and predictive algorithms, prevention measures can be based on their unique set of characteristics of the individual, with specific recommended real time actions to improve their individual prognoses and prospects. DEMOS, Demographic and Epidemiological Model of Singapore, simulated the population of Singapore at an individual level, taking in probability of possible future scenarios, as well as evaluating the effect of various interventions.
  • Big-data analytics and evidence-based healthcare

    The healthcare industry is moving towards an evidence-centric healthcare ecosystem, which is key to shifting healthcare towards lower costs and better outcomes. Enabling the vision of truly evidence-based healthcare will require critical investments to turn structured and unstructured healthcare data into care insights that will support evidence-based practice. Big-data analytics technology is the core of healthcare transformation, and impacts the evidence-centric healthcare ecosystem. The adoption of big-data analytics is the key component to enable this evolution.
  • Affordance analysis for individual analytics ecosystems

    Big data in Asia and elsewhere can be effectively used in the management and prevention of occupational accidents or work-related diseases. Employees' work behaviour and health-related data can be integrated to detect correlations and patterns and to recognise core drivers of human behaviour at the individual or organisational level. This allows the analytics focus to shift from understanding aggregates to understanding actions and behaviours of individuals. The success of using big data for individual behaviour change and awareness creation is, however, dependent on mutual value creation for both individuals and enterprises – a big difference from traditional use of big data. Big-data infrastructures as an “eco-system” may only function properly if the individual and organisational values are aligned and compromised.By looking into the application of big data techniques in Asia, this report provides a vivid picture of where the market is going and how the insurance industry could readjust itself to fully benefit from the emerging technology.

    Using affordance analysis to design individual analytics ecosystems

New developments are taking place whilst this report is being printed. We will keep a close watch on market developments and provide updates in our coming conferences and publications.

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