Risk Exposure Management is a Key Driver of Profitability for (Re)Insurers

Allphins’ CEO, Laurent de la Porte, explains how underwriters can improve their approach to exposure management to enhance the ability to fully utilise their capacity limits and access more premium.

At a time when underwriters are challenged to maximise the premium income they can generate on the capacity they have been allocated, the ability to effortlessly obtain a detailed understanding of exposures and their impact on accumulation scenarios has become increasingly important.

In energy and other specialty lines, including emerging risks such as cyber, typically defined as low volume high claims value business, that need is even more pressing. In a low yield investment environment , the pressure to write more risks comes with the need to ensure that the risks assumed do not threaten the maximum loss limits that have been placed on the book of business. This need is exacerbated by the increasing scrutiny from shareholders and regulators.

Regulatory Pressure

Globally regulatory authorities are moving to risk-based systems which demand that insurers and reinsurers can clearly evidence their ability to understand and accurately measure their exposures. That low volume high value nature of the specialty classes has seen regulations take a tougher stance on capital requirements for these risks. Regimes such as Solvency II demand a higher level of capital reserving to support specialty underwriting operations, than is required for other classes of business such as household and motor, given the size of the potential claims from a single event. Therefore, there is greater pressure to deliver more granular evidence on your exposures in order to enhance your ability to free up capital, and access more premium.

Top Exposure and Premium

Exposure Management consists in knowing how much you have to pay in case worst case scenarios occur. Those worst-case scenarios for the energy and cyber markets are a major loss event that involves a very high number of risks rather than a single one. Analysing these demands the ability to understand the risk accumulations that such events would present to your business is highly attuned if you are to achieve the maximum return on your available capacity.

Underwriters need to ascertain how policy’s risks are impacting their critical accumulation scenarios through interdependencies with other risks which have already been written. While selecting policies, underwriters also need to maximise their premium. This multidimensional decision can be very complex, in particular in treaty where many policies cover the same risks. It has created a clear case for exposure management to be performed prior to acceptance. This enhances the ability to avoid overexposure while maximising premium. Typically, when it is possible, underwriters would select policies whose premium contribution compensates their marginal impact on the main accumulation scenarios. This analysis is a very important piece of the underwriting decision process.

Challenges Abound

However, insurers and reinsurers face a range of challenges when it comes to effective exposure management:

  • The poor quality of the data that underwriters will all too often receive. For treaty reinsurance for instance, there may well be tens of thousands of different risks, even more in terror, the details of which are likely not to be delivered in a uniform manner, leaving the reinsurer having to devote a significant portion of team time to manual data tasks, such as manipulating risk information, mapping them and only then calculating exposure. The risk description in these cases is also often very poor, limiting possibilities of analytics.
  • Time pressure. Increasingly, the time available for the underwriter to analyse the data is becoming ever more limited. For reinsurers it is likely to be two to three weeks in the run-up to the treaty’s annual renewal. In some cases, underwriting decisions even have to be made in a few days or less.
  • Growing complexity. The risks and the scenarios that these treaties can create are becoming ever more complex. For instance, in the energy market underwriters will need to not only assess the specific risks for a downstream platform but also its interconnection with other platforms in a particular field, adjacent pipelines and the impact in upstream facilities should a major event occur. For political risks, scenarios include a combination of geographies, obligors, insured and economic sectors. Cyber is even more complex. And in general, this complexity is increasing with the effects of globalisation and global warming.
  • Inadequate technologies. Currently, risk professionals in treaty specialty lines for example are often using spreadsheets across their risk management processes. This tool however is not designed to handle big dataset, lacks computation power and offers limited connectivity & scalability.

Fact-based Decisions

These stringent maximum exposure limits combined with the challenges above result in underwriters adopting an ever more conservative approach to the risks they write. Practically, they often use a buffer and take less exposure than they could because of how uncertain they are on their data and calculation. It is not down to an unwillingness to write more risks, rather the inability to analyse the data to understand their exposures. Additionally, these challenges do not allow for an optimised selection of policies to maximise their premium.

The market cannot effectively operate if underwriters are second guessing their decisions as they cannot answer with confidence and accuracy the question as to the impact a proposed risk or treaty will have on their aggregate exposure and premium.

At Allphins we have the capability to allow the underwriter to enjoy complete confidence in the impact that any risk will make on their exposure and premium and understand how much of the risk can be assumed to match the company’s risk appetite whilst falling within the capacity limits. The key is the speed with which Allphins can enable the underwriter to digitalise the risk and perform analysis. In a few minutes, underwriters can upload their risks and know the impact of their decisions on very different types of scenarios and events: per risk, per natural catastrophe events or man-made events that can be customised. This allows them to move from a rather passive exposure management approach to proactive portfolio management.

When you are asked to participate in a treaty programme which contains thousands of risks you need to be able to understand how the treaty will impact your overall portfolio before you decide which share of this treaty you want to take.

When you have the systems in place to digitalise those risks, which may have been delivered in a wide range of different formats, you create the ability to understand, manipulate and visualise the data and therefore to fully control your risks.

It allows the underwriter to not only assess the impact that the risks will have on their wider book of business but use the data to accurately assess the level of the risk they can underwrite while keeping aggregations within capacity. More importantly it allows the underwriter to enhance their risk selection to increase their premium while staying confident in the knowledge that they are meeting the requirements of their business plan.

Risk Relevant Data

Allphins’ ability to deliver high quality data can all too often enrich the risk and with it the opportunity for the underwriter. Our technology recognises the risks based on natural language processing technologies so it can provide granular analytics on assets, addresses, and companies without the need for a standardized input format. It delivers risks description and analytics in a clear and uniform structure which further enhances the underwriting team’s ability to benchmark the risk against the wider portfolio, identify potential interdependences and with it more accurately quantify the aggregation risk.

Our clients have discovered the benefits of what Allphins can deliver and the speed with which even the most complex data tasks can be achieved. As the industry continues on its journey to modernise the way it operates, enhancing the way in which the industry can identify, quantify, and more effectively manage their exposures can make a major contribution to their bottom-line performance.