Data Science For Insurance Companies
Data Science as a knowledge (or technique) becomes more and more popular, expanding its borders to different fields that were not previously involved in this discipline. These fields include, for example, financial markets, startups or commercial sector. All of them have already benefited from hidden opportunities that Data Science revealed and its importance continues to grow. Now, data scientists are even more popular than economists or SEO specialists. Obviously, having such an influential impact, many businesses want to improve their internal activities and processes in order to boost their sales or share rates. Insurance companies here are not an exception.
From the first glance, both fields are closely connected with different mathematical approaches in their routine and from this point of view, it is strange a bit why Data Science was not so popular here.
However, now, insurance uses one of the most versatile and reliable way of prediction and forecasting.
Data Science Benefits
Insurance not only connected with mathematics, but also involves some kind of risk management and assessment. For example, insurance payments, assessment and calculation of potential and inflicted damage, switching to another insurance products, etc.
Data Science not only helps you to find some pain points in your sales or payment strategies, but also gives suggestions on how to improve them. For example, if you found that one or more your insurance policy products are not as attractive as they are expected to be, uncertainty may exist here. So, making things clear with Data Science, you will be able to improve pricing accuracy, create more successful and profitable insurance products, and define loss-prevention strategies. This will also help to build stronger customer relationships.
Furthermore according to the report by the Ordnance Survey and the Chartered Insurance Institute, The Big Data Rush: How Data Analytics Can Yield Underwriting Gold, 9 out of 10 respondents feel that having real-time claims data in place helps price risk more accurately.
Data Science can be useful in the following areas:
- Personalized Risk Pricing
- Life and Health Insurance
- Property Insurance
- Auto Insurance
- 360-degree Customer Profile
We will describe all these areas and some approaches that are used in each particular case in our next article. Stay tuned!
Feel free to browse through the latest insights and hints on the DevOps, Big Data, Machine Learning and Blockchain from IT Svit!