In my previous post, I suggested that it was possible to provide a road map that would help with the introduction of artificial intelligence, advanced analytics and machine learning into insurance companies. This post outlines the process. Start at the beginning The first area to address is applications where the
Recently, as a result of the EU’s General Data Protection Regulation (GDPR) and other regulations, new governance requirements for data management have emerged. These have had some interesting effects on the data preparation process. This post is the third in a series on data preparation (Data preparation in the Analytics
This post is the second in a series on data preparation based on a webinar about its role in the analytical life cycle. The first discussed how data preparation fit into the analytical life cycle. This post considers some trends in data preparation and some of the structures and processes
The increased availability of data is opening up a new world of analytics to insurance companies. There are both new sources of data and also increased volumes of information, and together, these are being used to generate insights and influence decision making. This post, the second in a series on
Data preparation is often seen by companies as a difficult and dangerous job, one best left to IT. However, business departments often do not want to wait for their data, so thick SQL books and spreadsheet applications are booming in most offices. This does not really make sense, however you
Data may be expanding exponentially, but this expansion in itself is not the be-all and end-all. Data is very important, but only because it enables organisations to learn more about their customers and offer them a better service. Therefore – and this is crucial – data allows organisations to make
Instant insurance, insurance on demand and real-time customer engagement are the buzzwords of the moment. These concepts are also, however, a real breakthrough in the insurance business. They describe new products and services that are strongly oriented to customer needs and follow their evolution throughout the life cycle. These changes
So much debate still rages about Artificial Intelligence (AI) and what it means for the future of society and humanity. While this continues, governments around the world are actively embracing the prospect of transforming their departments into smart digital governments that are able to deliver improved services to organisations and
Fashion and analytics are not obvious partners. However, fashion is a business like any other, and like other businesses, it can benefit from understanding its customers better. Recent experience with one particular high-end fashion retailer suggests that good use of analytics, including predictive modelling, drawing on an end-to-end analytics platform,
Until recently the approach to accounting for insurance contracts was considerably simple. Most of the existing accounting standards do not require any special processing after estimations are made by actuaries and before they are posted in the general ledger. However, with the arrival of IFRS 17, this will definitely change.
