Risk Modelling in Insurance: The use of ‘R’ in data science
Leading insurers are harnessing the analytical and intelligence capabilities of Microsoft R Server, SQL Server 2016 and Microsoft Azure to deliver faster results from increasing volumes of data.
Insurers today operate in an increasingly connected, data rich environment in which they face demands for faster, more accurate results. The amount of available data has grown rapidly in the past 12 months, and it will continue to grow in volume and variety. All of that information can enable insurers to create an increasingly accurate picture of risk and make informed, timely business decisions – but only if the business can turn that data quickly into actionable insight.
Microsoft Azure services, with Microsoft R Server and SQL Server 2016, are empowering insurers through intelligent apps using advanced analytics, machine learning, emerging cloud development models and the internet of things.
Take property and casualty insurance as an example. Weather predictions have been used for many years to identify the risk, severity and location of events, enabling insurers to alert customers and prepare themselves for the resulting claims. Those predictions are ever more sophisticated and, combined with data from a growing range of sources, from telematics to self-driving cars, they open up a world of potential for risk management, profiling and customer care. Customer segmentation can be based on a far more granular image of the insured, enabling efficient responses to the risk or profitability that each customer represents. Leading insurance organizations like State Farm and Progressive Corporation are using telematics to help them understand individual driving behaviors, so they can lower the premium for a good driver or raise it for one who presents more of a risk.
Exposing that data from a front office and back office perspective enables a more granular picture of the risk profile and faster, responsive decision-making to manage risk. Intelligent applications optimize the use of data to analyse regulatory exposures and improvement areas, or to profile customers in order to prevent fraud and make sure the organization is attracting and retaining the customers it wants.
Microsoft works with insurers to enable them to adapt and improve their data analytics so they can do what is best for their business. By adding the speed and agility of Microsoft R Server to the power of SQL Server, and combining that with the global connectivity of Microsoft Azure, we are delivering intelligent cloud and on-premise solutions that enable insurers to run any number of models, analyse information, identify trends and make the results available to those who need them, without having to worry about where their data is stored or where claims adjusters are located. Quite simply, it’s a game-changer.
Customers in our testing group have found that SQL Server 2016 with built-in Microsoft R Server capability enables dramatic reductions in the time it takes to run complex analytics. For example, one customer found that an analytics routine that had taken days using their old techniques now takes only 30 minutes using SQL 2016 with Microsoft R Server.
Business or regulatory requirements might mean that insurers want to store their data in a specific place – but in terms of technology, the location of data is much less relevant. Insurers no longer have to make the choice between moving to the cloud or handling their data analysis on-premise – they can do both. The speed, accuracy and analytic capability they need is available through SQL Server with Microsoft R Server on-premise, or in the Microsoft Azure cloud. Wherever an insurer’s data is stored, the pervasive, open-source nature of Microsoft R Server means they can now run it anywhere. If an insurer has SQL Server database and Microsoft R Server on-premise but decides later on that they want to move all or some of that infrastructure into the cloud, there is a migration path that makes it relatively easy for them to do that.
The combination of Microsoft R Server, SQL Server and Microsoft Azure means that whatever choice insurers make about on-premise, cloud or hybrid infrastructure, there is no wrong answer. The important choice faced by insurers today is whether to embrace the increasing volumes of data now, in order to ensure faster, more accurate data analysis to support the business.
In our increasingly connected world, the volume of data will continue to grow and demands for rapid, incisive risk management – whether for regulatory reporting or day-to-day operations – are only going to intensify. Insurers who embrace that volume of data now are going to win. By applying advanced analytics, leading insurers are already enabling intelligent processing that empowers the business to gauge any number of factors – from identifying the right customers to building the right portfolio, adjusting premiums or responding to risk events – more accurately. In doing so, they are enabling fast, intelligent decisions that deliver value for the business and its customers.
Find out more by downloading Microsoft’s Perspectives on Insurance Risk Modelling
