In the modern world, processes are requiring a deeper, faster and more integrated
environment to allow agile and immediate responses to market conditions. It is time
to start using data science to enhance your internal actuarial capabilities.
QED Data Science understands how advanced analytical techniques can be used to enhance current actuarial and data management processes. These insights can be used to augment your current actuarial processes to give deeper insights, improve efficiency and allow actuarial resources to focus on actuarial insights rather than data processing and model development.
Dashboarding and Visualisations
For you to be able to understand the challenges and strengths of your business, it is essential for you, as a decision maker, to be able to analyse your business in a critical way. In today’s fast-paced business world it has become increasingly important for this information to be available in real time in order to make decisions faster than your competitors. And the first step is to generate dashboards and provide this data in a way that can be easily analysed.
Many businesses already have a business intelligence functionality. The modern dashboard, however, does far more than just tell the story of where your business has been. It is vital to know too where the business is going. And it is through parameterisation and predictive analytics, that the modern dashboard allows you to do just that.
Including geospatial information into the current analysis of an insurer can add significant insight into the business from identifying geospatial concentration risks, under-standing mortality experience across different locations or interpreting telematics data for usefulness and integrity. QED looks to incorporate external geospatial data and geospatial modelling techniques to current actuarial applications such as pricing, reinsurance reviews and management information.
Being able to accurately identify customers that are likely to initiate a claim early in the policy lifecycle can have a significant impact on the performance of a product book. QED is working with insurers to implement advanced analytical models including models under-pinned by machine learning algorithms that assist in identifying these policies during underwriting and giving information that can assist in accurately pricing these risks.
Application of data science
The application of Data Science techniques to each component of a financial services business can lead to new and valuable insights as well as identify new opportunities that may exist. QED works with our clients to identify areas where these techniques can be applied in order to identify these opportunities.
- Fraud Framework
- Cross-sell modelling and next best action
- Data Management policy
- Data governance