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Airmic Technical
6 Data driven-decision making
'The key to using risk data effectively is to start small and keep
it simple and focused. Big data should be used to highlight small
changes that could enhance existing business processes, e.g.
board risk reporting, resulting in measurable improvements
to overall quality and insight. Risk managers will need to
demonstrate the cost-benefit of any changes using interactive
and visual messaging to get the support of senior leadership.
By starting small and building on success, the case for broader
adoption and investment into analytics will become easier.'
Philip Songhurst-Thonet, Head of Risk Consulting, Aon Risk
Solutions
Data driven-decision making involves a risk manager gathering
relevant data and using analysis and evaluation to inform risk
management, risk financing and business strategy.
Insurers and brokers are beginning to take the leap by exploring new
sources of data such as machinery sensors and telematics and using
automated decision making when quoting to improve accuracy. Risk
managers must follow these trends, e.g. by looking at the numerous
sets of data available to them and discovering new relationships
between sets if they want to keep up.
However, there is no doubt that there are internal challenges. Figure 3
summarises the actions and key questions risk managers should take
to combat these obstacles.
