Stretching the bounds of Actuarial Science: PART 1 – Anesu Shuro

Traditionally, actuarial skills have been used in insurance for the purpose of valuations, capital modelling and pricing. The kind of statistical skills that actuaries learn in training can; however, be used very efficiently in a lot of fields. One of these skills being is that of predictive modelling using tools like multivariate analysis. These skills, your generic statistician would possess which would make one wonder why someone would pay expensive actuarial fees instead of using data analysts and other statisticians that might prove cheaper.

One thing that makes actuaries more suited to answering some of the questions that companies face is their ability to structure the way they approach problems. One of the many tools Actuaries learn in training and exams is that of the actuarial control cycle (ACC). The ACC is sets out a framework for solving problems including understanding the problem; how to choose an appropriate technique to solving the problem, how to monitor and update assumption and consideration of external factors i.e. the environment and professional issues. This and other tools ensure a structure is maintained in solving problems and creates better clarity for clients and reviewers on the work done.

Actuaries are also trained in communicating uncertainty and highly technical concepts to a non-technical audience. This ensures that companies understand the results, limitations and implications of the results. Actuaries also have a board that ensures structured reporting, communication and ethics are practiced during actuarial work

Here I have highlighted some of the applications of predictive modelling including some that Dynamo has been involved in.


Modelling can be done around customer relationship management (CRM) in order to optimise marketing and operations. This included projecting customer receptiveness to different market offers; propensity to repay debt; identifying opportunities of cross-selling and up-selling and retention offerings to deliver to specific customers at given times; churn and risk management; and, using decision methods like declarative rules and decision tables.


Modelling can be done on usage data, network performance and device sales.  Again predictive modelling in churn management can be used.


There is extensive data that can be used in healthcare which can be used in predictive modelling in order to reduce costs and provide better healthcare. This includes claims and costs data, pharmaceutical and R&D, clinical data (from medical reports) and patient behaviour and sentiment data from stores. This data can be used in clinical analysis, financial analysis, supply chain analysis and fraud and HR analysis


In any subscription market CRM is a big area especially if companies have “big data” that is of good quality, Churn is one of the biggest areas of modelling in subscription markets.

These are just but a few of the applications of predictive modelling and predictive modelling is just one of the many applications of actuarial skills. In the next parts of my blog I will highlight some of the wider fields that actuaries are involved in and that we at Dynamo are quite passionate about.