data analytics

Kirsten de Vries new CEO Triple A – Risk Finance

Consultancy firm Triple A – Risk Finance (Triple A), specialized in risk and actuarial issues, has a new CEO as

Triple A – Risk Finance to open German branch, bolstering its growth in Europe

Triple A – Risk Finance is setting up an insurance and financial services consulting team based in Cologne, Germany. Andreas

Sustainability & ORSA

The presentation slides “Sustainability: Explanation of EIOPA’s latest advice and practical guide to integrating transition risks into ORSA and investment decision-making” are not only of interest to our Luxembourg colleagues. Download them here!

SDG Integrated Investing

Stakeholders of financial institutions demand that the objectives of SDG are an integral part of the product. Triple A – Risk Finance, Innorbis and LINKS Analytics developed a model to apply SDG integrally in the investment cycle.

Chaining in Python and R

Chaining is a powerful construct supported both by Python and R. Feel free to try it yourself, code and data can be found here.

What makes a good model?

What do we consider a good model? A model that runs fast and can run via cloud? A model with a lot of features and few (known?) bugs? Do particular programming languages or software packages make a good solution? Read the opinion of Robert Poos.

Alternative CSM approach for IFRS 17

The retrospective CSM is the source of some major IFRS 17 implementation challenges. Carlo Jonk offers the solution by using prospective valuation.

Triple A opens office in Spain!

Triple A – Risk Finance is growing. And now that Triple A is working for a growing number of clients in Spain, such as VidaCaixa, Medvida and Zurich, it’s time to open an office here.

Contractual Service Margin – calculate this also at the policy level!

The implementation of IFRS 17 and determining the Contractual Service Margin (CSM) for existing insurance contracts presents insurers with major challenges.

autoML: is this the Holy Grail for the insurance industry?

The primary objective of data science is adding value to the business, using data. This is where a well selected AutoML platform can make a difference.

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