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Source: Guy Carpenter
16 November 2016 Insurance

Analytics: fuelling risk-informed decisions

Today’s rapidly changing global environment presents insurers with many challenges and opportunities as capital management and risk transfer techniques evolve at an unprecedented pace. Stakeholders, regulators and ratings agencies are deepening their focus on risk management practices, and revolutionary developments in technology, including the internet of things and hyperconnectivity, are driving companies to adapt to the challenges that senior management faces to support risk management decisions material to their business.

Insurers facing these new challenges and disruptions require the most advanced tools and solutions to convert challenges into opportunities as they pursue profitable growth. The analytic tools companies use should emphasise solutions that align with transparent, supportable decision-making. Guy Carpenter continues our commitment to innovation as we invest in the development of sophisticated analytics tools and solutions to meet our clients’ needs around underwriting analytics, portfolio analytics and strategic risk and capital management.

UNDERWRITING ANALYTICS

Insurers increasingly seek expertise and guidance to support underwriting that spurs profitable growth. Entry or expansion into new geographies, markets or products requires profit understanding and proper capital allocation. Pursuit and execution of these opportunities should be supported with full insight into projected profitability and volatility.

Sophisticated analytic tools can leverage public and private data sources for evaluating the probable impact that growth strategies—potential new product development, expanded geographic reach or deeper market penetration—may have on profitability and enterprise surplus volatility. Insurers may use predictive analytics for strategy refinement in an array of areas:

- Assessing rate adequacy in target markets;

- Reviewing changes to accumulation risk metrics for a book of business with potential exposure to catastrophic risk; and

- Analysing risk level catastrophe loads when the underwriting strategy is realised through point of sale underwriting.

PORTFOLIO ANALYTICS

With robust portfolio analytics, including advanced actuarial and catastrophic risk modelling, insurers are able to manage portfolio risk with confidence. Notable new portfolio-based models are being used for emerging areas such as casualty catastrophe and cyber risk assessment. Significant advances in sub-peril modelling, such as for flood, have transformed previously non-modelled perils into modelled perils, greatly improving knowledge and underwriting decisions in many regions.

Companies’ active understanding of catastrophe modelling results has become increasingly important as they are used in a growing array of business decisions. Through model sensitivity analysis, loss validation and comparison of critical model assumptions to academic and other scientific data, companies can now better understand the significant assumptions inherent in catastrophe models. The analytic results provide senior management with the requisite level of confidence to accept, recalibrate, bend or blend the catastrophe model results.

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