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A huge increase in data generation, data capture and data storage combined with significantly increased computing power is providing insurers with a unique opportunity to re-evaluate the value that their data can provide.  

Enabling actuaries to embrace modern day technologies and data science tools and to work closely with other experts in these fields are important links that could give strategic advantages to insurers in the further development of insurance. 

For actuaries the rise of data at large is a sign that their role is more crucial than ever. Looking forward, the actuary will continue to evaluate key sources of data and need to find ways to incorporate data science that uses state of the art machine- learning and other technologies together with the actuary’s business insights. 

We need to refresh our methods and make use of emerging technological advances.


The increased presence of data science in financial services will mean that many actuaries will have some level of familiarity with the basic concepts behind machine learning.

However, it remains a challenge for actuaries to integrate these new techniques into their work. This may be as a result of:

Difficulties obtaining and working with large datasets;

Challenges learning the technical skills required.

Challenges to validating and communicating results from models due to their ‘black box’ nature

This article, co-written by Steven Perkins, Hazel Davis and Dupro's Founder Valerie du Preez, aims to address elements of these issues by firstly providing commentary around the key stages of the data science process and the considerations which should be applied by actuaries.


Data & Analytics Webinars

Examples of webinars held recently on the topic (fill in the registration form to gain access to the on-demand content)

Actuaries & Data Science: an introduction 

Actuaries & Data Science: Interpretable Machine Learning

Actuaries & Data Science: Practical tips for computational notebooks i.e. Jupyter

Training Courses

Training events covering, among other:

An overview of the impact of Data science and possible applications within the Insurance Sector.

An understanding of the main techniques of Data Science including data management, machine learning, text mining, scraping and data visualisation.

Initial insight on how to address hot business topics in different fields of the Insurance Sector by leveraging data. 

Actuaries & Data Science Event

Thought Leadership

Ethical guidance on the use of data science released by IFoA (Valerie was on the Task Force with the RSS)

Upholding Standards in Data Science Ethics

Research Papers

Modelling Analytics & Insights from Data (MAID) Working Party Member The Modelling Analytics and Insights from Data Working Party has contributed to research performed by the IFoA’s
Lifelong Learning Initiative related to Data Science. Key contributor and working party member to MAID’s practical application of machine learning workstream co-author of research paper - Practical Application Machine Learning within Actuarial Work

Member of Joint Task Force releasing new ethical framework for their members and practitioners working in the field of data science - Guide for Ethical Data Science

Virtual Data Science Conference

Virtual data Science Conference: Presenter and Panellist

Valerie’s involvement in the virtual data science conference also included:

Data Science: Opportunities for Actuaries. Valerie was one of the panellists, together with John Taylor and Maz Bown, discussing the opportunities for actuaries within data science including a discussion on how actuaries’ roles are changing, the professional and ethical implications and how we can ensure we have the relevant skills available to succeed in this changing world of big data.

Ethics video for Data Science Virtual event: as part of Valerie’s role in the Taskforce between RSS and IFOA (see below) on the professional and ethical implications of data science on our roles she and her co-working party members have developed themes and guidance for members working within data science. The principles developed has been discussed within our recorded filming of the presentation.

The use of predictive analytics within life insurance: via a recorded submission to the IFoA’s virtual data science conference Valerie co-presented a case study: The use of predictive analytics to enhance
life insurance portfolio management. We explained, using practical and easy to follow steps, how leading life insurers are using predictive analytics to: - manage their portfolios; - identify areas for growth; - improve persistence - increase profitability. We demonstrated how the full cycle of actuarial analysis is evolving - from data collection and data enhancement, feature engineering, modelling, verification and ultimately application and communication.

Global Involvement

Over the past year, we have been networking with Actuarial societies across the globe - Israel, South Africa, UK – for example, for the Actuarial Society of South Africa Michael has developed Exam Walkthrough Videos for subject CT4 and CT6 in 2016 and developed and delivered full-day workshops for subject CT8 and ST9 respectively in 2019. The workshops ran for 8 hours and covered the entire syllabus.


Zoning in on Target Operating Model

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