Insurance Analytics: What is it and how is it used?
Insurance Analytics: What is it and how is it used?
For insurance companies, excelling in the industry and creating trustworthy client services requires careful planning. Historically, these decisions have been informed by manual data research and human judgement, but with next generation insurance analytics on the rise, companies have access to new capabilities.
If you aren’t already familiar with the advancements that have been made in this field and the new tools that are constantly being developed, now is the time to learn more and see how they can be leveraged for your benefit. In the increasingly dynamic and competitive market, every edge you can create to keep you ahead of evolving risks and driving business growth is worthwhile.
What is insurance analytics?
Insurance analytics is the name given to the improved automated processing and advanced data analytic techniques to make fully informed decisions on critical insurance matters, whether that’s designing and pricing policies, improving the underwriting process, resolving claims, or providing real-time management information to better steer the business.
Where you hear the words ‘insurance’ and ‘analytics’, ‘predictive’ and ‘forecasting’ often follow. This is because one of the biggest advantages that comes from understanding your data is the ability to draw upon a wider range of sources to more accurately anticipate risks and forecast future trends. This method of understanding the past to predict is the foundation of insurance models, and insurance analytics will play a key role in the developing the future strategies of the insurance company of tomorrow.
With more and more insurance analytics solutions in the market and being deployed within insurance operations, it's becoming increasingly important to understand how to effectively leverage these techniques effectively.
How do traditional and modern insurance analytics differ?
While the intention behind traditional and modern analytics methods in the insurance industry is the same, the next-gen power of modern analytical tools is so significant that everything from the data input and processing methods to the capabilities and deliverable outcomes, is boosted. We’ve discussed the differences in each of these application stages below:
Data input
Traditional analytics can only handle small volumes of data due to the manual review processes used to analyse it. This data is also usually localised, minimising its potential for implementation across a wider range of decision making due to the limited scope. Analytics may also be limited to certain data structures rather than considering the vast variety of information available to an insurance company.
Modern analytics knows no such limitations and instead can analyse a broad range of current and past data from a wider range of sources. Whether internal data such as policy or finance information, or data from customer portals or contact centres, or external market data, and additional data from industry data sets, the outcomes generated consider a wider view allowing for better-informed decisions.
Processing methods
Traditional analytics relies on manual processing methods, leaving it open to risk of inaccuracies. Even with additional steps in place for manual double-checking, which slows down the pace of the analysis significantly, this risk can’t be eliminated altogether.
Modern analytics though human input is still required, and the valuable experience of experts is still utilised through careful framing of queries into an understandable format by analytics tools, manual involvement is kept to a minimum. The automated review of data and production of condensed information and forecasting improves speed and reliability, with the risk of human error significantly reduced.
Capabilities
Traditional analytics capabilities are as limited as their data and processes are; if the data processed is heavily localised, then the scope of the analytics outcomes will be equally limited. This naturally means that the impact on decision-making and subsequent business growth made by traditional analytics methods won’t be as significant as those that use more modern tools.
Modern analytics capabilities, by the same rules, can be as expansive as its data and processes. If you can input data from relevant sources and frame issues and obstacles appropriately, the insights and solutions that modern tools can generate are invaluable.
How can next-gen insurance analytics be used?
For insurance companies, the possibilities of next-gen analytics are endless. From predictive risk mitigation to improved customer service, every element of designing, servicing and managing an insurance product can be improved. Some of the applications have been detailed below:
- Enhanced risk assessment: Using third-party data, including post code data, risk potential can be more accurately forecasted outside of a customer-by-customer localised frame. This allows insurers to offer more competitive pricing on policies, without being exposed to greater risk.
- Streamlined underwriting: With most of the process digitised within next-gen analytics, including the enhancement of risk assessment, underwriting is faster and more efficient.
- Improved claims processing: Through automated processes such as document processing, AI adjudication and enhanced fraud detection, the claims process is significantly improved. From both the perspective of the insurer and the claimant, submissions are dealt with faster and more efficiently.
- Customer experience and retention: With data leading the way, insurers can get a clearer image of their customers, allowing for the creation of a more personalised service. This opens the door to more appropriate cross and upselling, tailored communications and better retention.
- Business operations and strategy: From the identification of market gaps to the formulation of new insurance products, the insights provided by well-leveraged analysis can completely transform a business strategy, both immediately and in the long-term.
Why choose XPS?
Data analytics developments have been revolutionising the insurance industry but implementing them as part of your business isn’t an instant process. At XPS Group, we have experience helping clients to make the most of leading insurance analytics tools, making sure they can gain new insights, mitigate risk, save resources and remain competitive.
Reach out to our experts to learn more about how we can assist you, or visit our insurance consulting page to discover our wider insurance client offerings.