Catastrophe models became widespread in insurance almost as suddenly and unexpectedly as the hurricanes that they model.

After the dust settled, and the initial excitement at the opportunities that these products would bring – improved risk selection, optimised portfolios, greater downside control – came the realisation that significant investment was required if value was to be extracted from the noise of data quality issues, portfolio specifics and uncertainty ranges. In essence we’d been handed our first sat nav, only to find it set up in a foreign language.

As the first wave of exposure management professionals oversaw the widespread adoption of these models into risk pricing, portfolio management and capital modelling, underwriters discovered that their natural curiosity and attention to detail was enhanced by ready access to databases of cleansed, organised detail about their exposures. Functions interacted more readily with a “common language” of catastrophe risk; and management revelled in the newly transparent reports.

The second wave sought to build on this position. Already a diverse group, we’ve seen an influx of skill-sets, experience and backgrounds. PhDs and natural hazard specialists; mathematicians; economists; lawyers and programmers – introverts and extroverts; the analytical and the creative – everyone had something to contribute. A vibrant ecosystem emerged, with each insurer pursuing a USP that made the most sense for them.

Over 10 years we’ve seen an astonishing pace of progress. In an industry notorious for its inertia, consider how rapidly it has become the norm to have instant access to your active portfolio of risks; be able to visualise exposure, potential scenarios or hazard zones on a responsive, detailed map; and consider marginal risk contributions within timescales that enable it to form part of point-of-sale underwriting.

This particular cycle appears to be coming to a natural end. The catastrophe models have largely been tamed – to be replaced with the legacy of annually maintaining vast model validation documents.

At the same time, software providers have caught up so that what was once the preserve of those who sought advantage through technical tinkering can be bought off-the-shelf, fully documented and supported. A dearth of headline-grabbing catastrophes and a weak rating environment have suppressed appetite for further innovation. There is even a faint hint that regulatory focus and reporting requirements may step back, now that standards have been proved. Exposure management has earned its place in the business-as-usual; and at Asta we have a comprehensive and flexible framework that enables us to quickly and efficiently bring our managed syndicates up to speed.
So what comes next?

With a highly skilled exposure management workforce and ever improving technology capability and speeds, the discipline could be the pioneers of a range of new developments including:

– Enhanced focus on efficient use of capital – more strongly linking point-of-sale underwriting and business-planning to capital implications with faster end-to-end calculations, and improved connection between front-line (‘regional aggregates’) and back-end (‘risk appetite’);

– “Artificial Intelligence” – rules based decision-making as a complement to bespoke underwriting to meet increasing customer demands

– Data enhancement – smoothly integrating third-party data, whether improving or challenging your own data quality; gaining insight into current or potential customers; or understanding your own ‘brand awareness’.

– Automation – within any data-intensive function, focusing on control, scalability and maintainability.

– Not to mention repurposing of skills with data analytics and visualisation, software-design and process efficiency that could be applicable to any function from finance to HR.

The success of the next phase of the exposure management revolution will be defined by those who stop asking ‘what should I do?’ and start asking ‘what could I do?’.