Pricing Teams in a Changing World Report

The actuarial field is experiencing a rapid transformation driven by dynamic trends, including the surge in data volume and diversity facilitated by technological advancements. Actuaries now confront the challenge of extracting insights from diverse data sources, necessitating the integration of cutting-edge technologies like AI and machine learning. While these trends strongly increase the demand for actuaries, there’s a shortage of talent, prompting insurers to embrace alternative pathways like data science to meet their needs. In the meantime, actuarial education is evolving to match industry demands, with an emphasis on machine learning and data science integration. While the rise of data science poses both opportunities and challenges, actuaries remain integral to the industry, sought after for their unique blend of domain knowledge and analytical prowess. As companies vie for actuarial talent, competition intensifies, and retention becomes crucial. Employers are adapting strategies to attract and retain junior actuaries, focusing on reputation, internal rotation opportunities, and actuarial benefits. Continuous learning, particularly in areas like data science, is vital for both junior and senior actuaries. While technical skills are valued, soft skills are also emphasized. The “ideal employer” for pricing professionals prioritizes teamwork, collaboration, learning opportunities, and tools to streamline communication and tasks. Actuarial careers remain a compeling choice for graduates, offering intellectually stimulating roles with a lasting impact on industries like insurance, finance, and beyond.
Cover page of the Report that Akur8 published and named "Pricing teams in a changing world: evolving backgrounds and expectations"
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‍Any judgement on the elements contained in the Paper should be made only after studying the document in its entirety. Any conclusions drawn from one or more sections taken in isolation may be incorrect.The Paper is intended to be used by persons with certain levels of expertise in the areas covered and for the purposes stated. Any reader of the Paper should have a certain level of expertise in the areas related to this analysis, in order to appreciate the significance of the assumptions made and the impact of those assumptions on the results obtained.We recommend that any reader be assisted in reviewing the Paper by a qualified professional to ensure that our findings and recommendations have been understood.The Paper has been commissioned by and prepared for the exclusive use of Akur8, in accordance with the terms of our engagement letter. We make no commitment to third parties and shall not be liable for any use by a third party of an opinion or more generally for the use by such third party of the results included in the Paper. Milliman does not intend to benefit or create any legal obligation to any third-party recipient of its work.‍ 
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TERMS OF USE OF THE PAPER “ANALYSIS OF AKUR8 PRICING SOLUTION AND METHODOLOGY” (“Terms of Use”)

‍In the context of Akur8’s and Milliman’s strategic alliance to provide AI-driven pricing solutions to insurers, Akur8 has engaged Milliman to analyse Akur8’s pricing solution and methodology (“Akur8 Tool”). Milliman’s Paper “Analysis of Akur8 pricing solution and methodology” (the “Paper”) provides a general opinion on the relevance of the modelling choices made by the Akur8 Tool in the context of non-life insurance pricing.Milliman is hereafter referred to as “we” and the readers of the Paper as “you”.

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DistributionYou are not allowed to distribute or disclose all or part of the Paper to any third party whatsoever, without Milliman’s prior written consent, which may be given at their sole discretion.No Use of Milliman nameYou agree not to use and/or refer to Milliman’s name and/or trademarks directly or indirectly in any communication with any third party without Milliman’s prior written consent, which consent shall be required for each use or disclosure and shall be granted only at Milliman’s sole discretion.
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‍Any judgement on the elements contained in the Paper should be made only after studying the document in its entirety. Any conclusions drawn from one or more sections taken in isolation may be incorrect.The Paper is intended to be used by persons with certain levels of expertise in the areas covered and for the purposes stated. Any reader of the Paper should have a certain level of expertise in the areas related to this analysis, in order to appreciate the significance of the assumptions made and the impact of those assumptions on the results obtained.We recommend that any reader be assisted in reviewing the Paper by a qualified professional to ensure that our findings and recommendations have been understood.The Paper has been commissioned by and prepared for the exclusive use of Akur8, in accordance with the terms of our engagement letter. We make no commitment to third parties and shall not be liable for any use by a third party of an opinion or more generally for the use by such third party of the results included in the Paper. Milliman does not intend to benefit or create any legal obligation to any third-party recipient of its work.‍ 
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