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Insurance analytics: Going beyond risk

The global insurance industry faces unique challenges with ever-increasing regulatory pressures, new product innovation, controlling operating costs and sustaining growth. Intelligent decision-making becomes imperative to facing challenging situations. The only substantial factor that can best support decision-making is data. Data analysis (analytics) provides organizations with a framework for decision-making, solving complex business problems, improving performance, encouraging innovation, and anticipating and planning for change while mitigating and balancing risk. In order to sustain and grow against the intensifying competition, the best choice for companies is analytics.

Most insurers are using very sophisticated analytical models in areas such as underwriting, where actuaries have been using risk models for years to underwrite and price policies. Another example of advanced analytics is in catastrophe modeling. By coupling internal data (e.g. historical loss trends) with external data (e.g. hurricane tracking) for placement into a catastrophe-avoidance model, insurance companies can avoid risk in high-tech ways.