InsuranceERM's Technology Guide 2018-19 is now live

Published in: Risk, Risk management, Risk Models, Cat risk, Capital Models, Solvency II, RBC Worldwide, Accounting - tax, Investment risk - strategy, Software - IT, IFRS 17

Christopher Cundy introduces this year's guide to risk, capital and asset management software

The 2018-19 edition of InsuranceERM’s Technology Guide marks the seventh year we have put together this listing of software that re/insurers use in their risk, capital and asset management.

In the Technology Guide microsite we provide details of more than 90 products from almost 60 vendors.

The guide also includes 10 corporate statements from leading vendors, describing how risk and capital management is evolving and how they are developing their tools in response.

The market and the products never stand still, so here are some of my thoughts on the trends we are currently seeing in the market.

IFRS 17 becomes the biggest driver for investment in actuarial transformation projects

The insurance contracts accounting standard, coming into force in 2021, will force some insurers – particularly life underwriters – to invest heavily in data management, in order to deliver the level of granularity required by the accounting regulation.

The standard will not have as broad an influence as Solvency II – roughly 500 insurers will be expected to implementing IFRS 17, compared with the 3,500 entities subject to Solvency II.

However, for those that do have to adopt IFRS 17, the costs are significant. According to a survey of European CFO Forum members, the average spend will be €160m ($185m) per insurer.

Most insurers will have to be ready from 2020 to do a parallel run of their accounts on their existing and IFRS 17 basis, leaving two scant years to implement any changes.

According to a KPMG survey from May this year, around two-thirds of large firms are still in the preparation phase, and only 6% have started implementation. Among smaller firms, just 4% are implementing and one-third are assessing.

Getting the most out of Solvency II

With almost three years past since the implementation deadline, it is understandable how Solvency II is no longer the biggest prompt for investment. But while most firms have satisfactory systems of calculating capital and delivering reports, there is room for improvement.

This is especially true on the reporting side, where it’s still a labour-intensive process for some. Firms remain focused on getting the most out of their Solvency II investments, particularly in providing information to management. Dashboards and advanced analytics remain an attractive area for development.

Fears over the security of cloud computing have dissipated

Worries over the security of cloud computing were a major barrier to adoption of these technologies. But the tables have turned, with some firms even demanding cloud solutions instead of hosting it themselves. So almost all vendors are now offering – or plan to offer – cloud solutions.

Software-as-a-service (SaaS) is also becoming a more widespread option as the general IT landscape shifts to this kind of approach.

The influence of insurtech

Almost every new insurance technology company boasts of some skill in big data, artificial intelligence or machine learning.

In the risk and capital management space, such technologies are not being ignored, but most of the systems used by re/insurers are well established and deeply embedded, so change is necessarily a little slower.

Christopher Cundy, InsuranceERMThat’s not to say there is no disruption in the market. RPC’s Tyche modelling system has gone from nothing five years ago to gaining some big-name clients, including Lloyd’s of London, Hiscox and Guy Carpenter, who have been keen to take advantage of its speed and user friendliness.

In the catastrophe modelling space, the open-source Oasis Loss Modelling Framework is making strong in-roads.

Actuaries and risk modellers have been keen to highlight the huge potential for AI and machine learning to help model complex problems and improve how decisions are made.

Modelling solutions such as Agena are emphasising how its modelling software takes advantage of Bayesian networks. This trend can only be set to continue

Christopher Cundy