been temporarily taken off the ball in terms of other risks such as underwriting risk, reputational risk and political risk but that position is relatively easily and quickly remedied.
1.1.4 Between the Data and the Analytics
Big Data in either its structured or unstructured forms does not naturally flow into analytic outcomes, which usually takes the form of reports, predictions or recommended actions, but relies on intermediate processes which exist ‘between the data and the analytics.’
How this is done in practice is a matter for the technical experts but in simple terms the raw data needs to be captured, then brought into the system where it is filtered, cleansed and usually stored. Massive volumes of data lend themselves to complex sorting systems or ‘landing zones,’ most of which have their own language and jargon. Often a datamart or staging layer is created to ensure that an analytical outcome can be created relatively quickly. The process by which data is moved through the system is referred to as ETL, or ‘extract, transfer, load.’
There are other alternatives, such as ‘data warehouse appliances’ which provide a parallel processing approach and create a modular, scalable, easy-to-manage database system. These high speed solutions allow very rapid computing power by providing an alternative to traditional linear processing, and often come with pre-bundled analytical and geospatial capabilities. In effect this is a ‘plug and play’ approach to Big Data and Analytics. These serve as a reminder that, as was experienced with the internet in the early days, both organizations and individuals will increasingly press for computing power in the form of analytics to be provided ‘at speed.’ It doesn't seem that long ago that, in a domestic environment, connecting to the internet was accompanied by some form of whistling and other strange noises down the telephone line. Now instant 4G connectivity is expected anytime, anyplace, anywhere – within reason. Perhaps in that light, if one level of differentiation between technology vendors is that of the breadth and depth of analytical capability, the other differentiating factor may well be speed of delivery of the analytical insight. The need for speed potentially opens the door for interesting alliances of what might previously have been competing organizations.
‘Cloud’ computing also needs to be considered here. One good and simple description of cloud computing, often just referred to as simply ‘the cloud,’ is the delivery of on-demand computing resources. This includes everything from applications to data centers – on a pay-for-use basis, often accessible through wireless. For the record (and just in case anyone is thinking it) this is not a process in the sky or somewhere in the ether, but rather is an expression to reflect a capability. Users should not be misled by the fact that there are usually no cables or physical connectivity involved. As with the other processes described above, the technology is too complex to be considered in detail, and in fact cloud computing as a topic is worthy of its own book (and there have been many of them). But cloud computing also provides another example of how a paradigm shift in the thinking of the insurance industry needs to take place. The entire concept opens the door to new thinking, and those who do not have an open mind will be disadvantaged. In their 2014 document ‘Predicts 2015: Cloud Computing Goes Beyond IT into Digital Business’ Gartner indicate that business leaders will need to ‘constantly adapt their strategies to leverage increasing cloud capabilities.’
It is increasingly critical that business users need to have some understanding not only of current IT capabilities but what are likely to be the IT capabilities of the future, in order to effectively manage their business and create new and compelling strategies.
It is easy to get bogged down in terminology. Readers should try not to become either distracted or confused by many expressions which are not familiar to them. It may be sufficient for individuals simply to become aware of what they do not know, and as a result have an open mind about technology and change. Some may view this as a catalyst, a personal challenge or perhaps a call to action in order to find out about new elements of their own industry and other associated industries. Managers may wish to encourage their direct reports to become more familiar with technology as part of their annual personal development planning.
1.2 Big Data and Analytics for All Insurers
At face value, Big Data and Analytics are for big insurers who have the economy of scale to supplement data external to their organization with a firm foundation of internal information. Many of the industry proof points, for example fraud analysis and telematics, are firmly aimed at the property and casualty market, and especially at the B2C sector. But insurance is a broad church, and there are many parts of the industry, perhaps all of them, that can benefit from an analytical approach.
1.2.1 Three Key Imperatives
At the highest level, all insurers are interested in three key elements
■ Operational efficiency – delivered through cost reduction, claims management and productivity strategies.
■ Profitable growth – delivered through profitable customer acquisition and retention, cross selling and upselling.
■ Risk management – delivered through capital efficiency and operational risk management.
Underpinning these three elements is what might be described as a ‘pure play,’ that of financial performance management. It is called ‘pure’ because the analytical approaches used in the Office of Finance are generally transferable from industry to industry. All CFOs are interested in the financial performance of their organization and need to report to stockholders using standardized techniques. In the case of insurance CFOs, there is often less certainty in the figures which invariably make projections for ‘IBNR’ (Incurred But Not Reported), a situation where insurers need to take into account the amount owed by them to customers who are covered for a claim but have not yet reported it, such as in the case of a major weather event. The effect of long tail claims, i.e., claims of lengthy duration, is also an important part of the consideration of the insurance CFO and their team.
Increasingly insurers are gaining greater insight into the convergence of the risk, compliance and financial performance management process. This approach, where data is reused and where reporting software for instance is repurposed, allows insurers to gain added value from the compliance process. It also creates a soft benefit in that it starts to break down the silos of risk and finance that exist in many organizations and increasingly embeds a risk culture into operational decisions.
It is tempting to suggest what are the typical trends for any given segment of the insurance sector, but different trends occur within the industry, in different sectors at different times and in different places. A typical example of this might be the Solvency II initiative in Europe, replicated to some degree in many other locations such as South Africa and parts of Latin America. While Solvency II has been a burning (and non-negotiable) platform, insurers had no real option but to pour in money and resource albeit to the detriment of other programs. For some insurers this represented 80 % of their IT development budget. To that extent, risk and regulation have been at the top of the league table in terms of prioritization, although risk and compliance in Europe are increasingly assuming a ‘business as usual’ status. Although some fine tuning is likely to occur especially around risk reporting, the topic seems less critical at the moment. Even so, there is a school of thought which indicates that now that insurers have crossed the Solvency II compliance ‘deadline’ of January 2016, the topic of risk and compliance will be revisited as insurers drive for improved operational efficiency and cost reduction.
Standard techniques such as PEST and SWOT analysis remain available to insurers to allow them to identify key issues. Such a methodology remains valid although increasingly there is concern that some traditional management school thinking may be slowly becoming out of date due to the nature, impact and speed of change. In such formal techniques, topics such as disruptive technology may be both an opportunity and a threat. Beyond this, the influence of disruptive
