This session looks at how MGAs can experiment with their data in a low-cost and compliant manner to test and pilot data-driven concepts to improve the quality and speed of decision-making and optimise performance.
Learning objectives
By the end of the session, delegates will be able to:
- Understand and describe the differences between Management Information (MI), Business Intelligence (BI), Augmented Intelligence (IA) and Artificial Intelligence (AI) and understand the practical applications of each of these data disciplines.
- Understand the importance of the involvement of insurance domain expertise in exploring data analytics concepts.
- Understand the importance of targeting data analytics projects at solving specific business challenges for MGAs.
- Describe the steps involved in the data analytics journey from concept to operationalisation.
- Describe several different types of data analytics techniques and understand how to apply the right technique to the right problem.
- Understand the basic theory of predictive analytics techniques and why they work.
- Understand the importance of both creative thinking and failing fast as applied to data analytics experimentation.
