Most GCC insurers have successfully adopted IFRS 17 with the transition having a negligible impact on the overall equity in the industry, although there are variations at an entity level. However, key challenges remain, with solvency deficits emerging as a prominent concern, leading to credit rating downgrades and the need for remedial plans.

For companies wishing to adopt IAS 19 for the first time or considering a transition to a new IAS 19 provider, there are certain measures that can be taken to ensure the valuation process runs efficiently and smoothly.

Lux Actuaries is excited to announce our participation in the 5th Insurance Data Science Conference, taking place on 15-16 June 2023 at Bayes Business School, City University of London. The conference brings together academics and practitioners in areas including data science, analytics, machine learning, artificial intelligence, computational statistics and software, as applied in the insurance industry.

Outsource Chief Investment Officer (OCIO) represents today’s evolution of best practice in investment for institutional investors. OCIO provides a complete investment function, similar to in-house investment management functions of yesteryear. However, in-house solution is no longer commercially viable except for the very largest institutional investors, which is why outsourced solutions like OCIO have become mainstream.

Lux Actuaries & Consultants is delighted to announce its participation at the Arab Actuarial Conference 2023, being held at the Four Seasons Hotel Cairo, Egypt on 9th-11th May 2023.

Lux Actuaries has developed the Lux Conflict, War and Strife (CWS) Predictive Model which has been designed to assess the risk of future armed conflicts globally, considering a multitude of indicators that cover all areas of development, governance and overall socio-economic strength of countries across time. This blog post discusses feature importance analysis - a key strength of the Lux CWS model - which helps to elucidate some of the black-box workings typical of most machine learning models.