Advanced analytics and model risk management for insurance applications

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Overview

Advanced analytics continues to yield significant benefits for insurers, with increasing adoption outside of traditional applications and more accessible solutions for smaller insurers.

Analytics are now applied in all areas of the insurance organization, including claims, marketing, customer experience, finance, human resources and others. This expansion of advanced analytics’ role in the insurance process has yielded significant benefits, not just in more accurate and granular estimates of losses, customer behavior and claims outcomes, but also in efficiency gains. More business processed with fewer resources and increased quality of outcome has resulted in additional corporate investments in analytics resources to achieve even greater gains.

While the benefits of advanced analytics are clear, insurers also have developed a dependency on models and data. This dependency has grown in complexity over time as the model development and deployment process has adapted to more advanced methodologies and incorporation of additional data sources. Model risk management approaches to traditional models often fall short of meeting the evolving requirements of the modern analytics process. As insurers increase their use of advanced analytics to make important business decisions, they should enhance their model risk management programs to better incorporate these models.

How PwC can help

Our insurance risk and capital management practice advises insurers on assessing, monitoring and managing risks from all sources. Multi-disciplinary teams provide comprehensive services in all key risk areas:

PwC’s professionals also address risk management framework components, including strategy, governance and organization, measurement and analytics, reporting, and systems and data infrastructure.

Contact us

Mark Jones

Actuarial Services Advanced Analytics Leader, PwC US

Henry Essert

Insurance Risk & Regulatory Services Leader, PwC US

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