Augmenting Decision Support for Underwriting and Claims
Enabling superior underwriting decisions through the elimination of bias and facilitating data-driven decision-making aided by automation, better information management, and predictive analytics
Claims settlement and underwriting efficiency are influenced heavily by the human factor of subjective analysis. This can result in biased decision making, which has the potential to destabilize underwriting processes. Biased decisions drive underwriters significantly away from guidelines, objectives, and standard operating procedures prescribed for underwriting and ultimately may cause losses for the insurer.
To eliminate this risk, it is imperative that insurers move away from human-centric subjective analysis of claims and seek validation from automated decision systems that leverage data-driven modeling of scenarios. Decision support systems have the potential to unlock hidden insights and create additional value streams and opportunities to lower inefficiencies and errors.
By analyzing historical data, judgment behavior, and strategic business objectives, insurance companies can transform their decision frameworks for underwriting and claims processing. The correct application of technologies such as machine learning and predictive analytics at the right stages can help create a sustainable operational guideline for underwriters and claims processing which are the two most influential pillars of capital outflow for insurance companies.
