Data key to more accurate risk analysis and pricing
The arrival of big data theoretically offers the risk and insurance management community an unprecedented opportunity to significantly improve the way risks are identified, measured, modelled, priced and, ultimately, transferred. In a world of ever-tighter deadlines, swifter change and scarce resources, risk and insurance managers need to ensure they are taking advantage of the brave new world of analytics.
Commercial Risk Europe’s Adrian Ladbury discussed the way ahead with Angus Rhodes and David Thomas of Ventiv Technology, an international provider of risk, insurance and claims software solutions.
Spreadsheets and face-to-face remain core, but digital solutions arriving
Adrian Ladbury [AL]: How do risk managers currently use data to identify and map their risks, what data is typically used and where does it come from? How is it gathered? What are the latest tools and methodologies available to help in this key initial task?
David Thomas [DT]: Generally speaking, risk managers reach out into the company – to the risk owners – and identify the risks via face-to-face contact. They tend to use workshops to develop a consensus on the risks that the company faces. But the risks also need to be monitored and evidence gathered to measure frequency and severity accurately. This is commonly done on a quarterly basis. Typically, this is still done using spreadsheets, but digital solutions are now available that can be provided to the risk owners, and are easy to understand and use. Such tools enable users to upload content, photos and files, and even use apps that create a much better audit trail on losses and events. These tools are supported by reporting and analysis tools that, all combined, promote a culture of risk-based decision-making.
Angus Rhodes [AR]: The quality of the data really depends on the type of company and sector in which they operate. If the company is a digital company, such as Airbnb, then analytics can be used to spot emerging trends. More traditional companies that have usually been built up through the acquisition of various companies, tend to have many different systems in different countries that are not aligned. Also, it is worth noting that a lot of the risks that really matter to a company are external, such as political, competition and the weather. These are naturally harder to assess because the information is not held within the organisation.
[AL]: How can such external, strategic risks be identified, measured and analysed?
[AR]: The importance of such risks means that a lot of the analysis is very much qualitative, not quantitative. This does not mean that the risks cannot be analysed. Weather risk is a good analogy. How long has it taken the world to reach a point whereby weather risk can be relatively accurately modelled? There has been huge progress in this area in recent times. Think of all the observation equipment silently lying under the ocean collecting hidden information, for example.
There is also a huge amount of quantitative data gathered to analyse and predict the direction of the economy, but it too remains very subjective and qualitative. You cannot look at these areas from just one angle, because there are a lot of factors that are not financial such as politics, regulation, the law, human resources, health and safety and so on. So, each company needs to look at what is relevant to them and not just focus on the predictable risks.
Senior management do not want to know about the risks they already know about, they want to hear about the risks they don’t know about! But this is the natural tendency from an auditing and reporting perspective. The Harvard Review published research back in August 2015 that found 80% of significant losses were caused by strategic factors, but only 6% of auditors spent any time in this area because most are focused on compliance and not strategic risks.
Using data to deliver cost and time efficiencies with insurance
[AL]: How do risk managers currently use their data to price risks, work out an accurate cost of risk and thus retention and captive strategies? What is available to help risk and insurance managers do a more effective job in this key area?
[AR]: This is mainly done with renewal data, currently collecting data around lines of business and normally carried out on a programme basis. They will carry out loss scenarios, exposure and risk analysis, and look at property values, location of sites and the like. There will also be specific high-value risks that will be surveyed, cases that will have to be carried out every year, while others will be surveyed on a three-year basis.
[DT]: We do ask risk managers what they see as the day-to-day challenges. The common answers are: increased business complexity, more data, greater security risks and the heightened expectation of senior management. All this is coupled with less time and less resources. This is clearly one of the reasons why risk managers are increasingly turning to technology solutions. A good risk management system can give a real-time view, control and deliver underwriting data, policy data and claims data. If an integrated system is used, it can calculate the cost of risk, help work out retention levels and underpin and direct the captive strategy.
[AL]: Roughly how many of the larger companies are actually doing this in a structured way using the latest technology?
[DT]: In the UK I would say that of the FTSE 100 companies, probably about 40% to 50% are actually doing this currently.
[AR]: It is fair to say that 100% of FTSE 100 companies are formally reporting their risks from a compliance and governance perspective because they have to. I get the feeling that more than a third are doing it strategically.
[AL]: How can improved data capture and analysis help insurance managers negotiate more accurately priced and relevant coverage with insurers? How can improved data management be used to help more effectively ‘sell’ the risk to the insurance market and then help ensure claims are paid when they occur?
[DT]: The best way to secure a better price is to provide more accurate and reliable underwriting information to the market. In the UK, this has partly been driven by the Insurance Act, which is a positive result of the legislation. Insurance managers are more conscious of the need to provide more accurate data that is readily available because of the requirements of the Act and ensure that claims are paid. Historically, many insurance managers would have relied upon their broker, to an extent. Now the disclosure requirements are more onerous, so the capture, collation and reporting of risk and loss information has to be more robust. It is in the interests of insurance managers to capture exposure data and improve the process of collating, consolidating and auditing this data. If this is done well, the programme can be more actively sold to the market.
We are now seeing more insurance managers selling their risks to the market because they are using digital technology to more effectively capture, collate and package their risks. This provides insurers with greater confidence in the data and this, in turn, leads to more accurate pricing and better coverage over time.
[AR]: It is also interesting to note that the higher up the scale you travel – from medium-sized to larger multinationals – the focus shifts from more day-to-day claims to the more catastrophic claims, and particularly professional and product liability claims. Clearly, the risk manager at a large multinational buys plenty of compulsory motor and EL coverage and wants to make sure they can secure the best terms possible. But what they are really worried about are the big and very expensive legal liability claims, such as product liability. These are not so frequent events but can cost huge amounts of money. Risk managers are rightly concerned about the loss of a factory through fire or flood, but business interruption losses, for example, can be far more expensive and difficult to recover from. This is another example of the shift in focus from physical to non-physical damage.
Analytics and visualisation offer context, underpin loss prevention
[AL]: How does the data that risk managers have help them to predict and plan for the future, and help them understand certain characteristics that are influencing costs to their organisation?
[AR]: There are some really significant developments on the analytics side of real interest and use to the corporate risk and insurance management community. But before you can get anywhere with this advanced technology, you need the good underlying quality data in the first place. It does not necessarily need to be structured but you need access to the data. If you want to analyse company chatrooms, for example, you need to overcome the siloes in the business. You would be surprised at how few companies are at this point.
[DT]: Analytics is a big driver in the risk and insurance world. One important area is the material addition to data of support resources, the provision of data with a spatial element, the provision of visualisation and especially the use of maps. This can offer context, timing and location rather than just simple values in a spreadsheet.
[AR]: A good example of this is on a cruise liner. Such maps can much more effectively show where the incidents occurred and at what time, on which deck. This can really help with analysis and future loss prevention. So, you can create a plan of the ship rather than a geographical map. Compared with the old traditional claim form, this takes it to a different level. From the risk manager’s point of view, it also provides more context rather than just dry numbers that offer little insight into the underlying risk.
[AL]: And presumably such maps also make it easier to present the risks to fellow managers and the insurance market?
[DT]: Exactly. Such visualisation also helps immensely when risks are presented to the board of directors and other senior management who have limited time. It can be far easier to understand and more insightful for both the risk managers’ own management and the insurance market.
[AR]: One of the exciting things for the risk and insurance management community is that these new analytics tools are making the whole world of risk analysis and modelling more accessible. In the past, companies needed banks of analysts and experts to create the models. This could only really be carried out by the expert modelling firms and the big insurers and reinsurers. Now the barriers to entry are being lowered by the new technology and you do not need all the statistics experts to make sense of the data and find the trends. But, as ever, to take advantage of this you need access to the data in the first place.
