Improved risk profile and insurance premium calculations
The insurance industry is inundated with data from a variety of sources and providers. With the introduction of new and varied data sources, underwriters are challenged to collect and combine the right mix of available data and strategically and appropriately apply it to risk assessment, customer experience, and policy turnaround time.
Underwriting of the future
The traditional underwriting processes is reliant on underwriters who are tasked with manually collecting, combining, and reviewing documentation. The reality is that highly skilled resources have limited capacity to consider historical performance or past experiences due to the manual effort involved in review of documentation. The end-to-end process to generate a policy can take up to 10-20 business days.
Introducing KPMG Intelligent Underwriting Engine
KPMG Intelligent Underwriting Engine is an Azure-based solution that helps businesses develop and assess risk profiles and calculate premiums with KPMG’s Signals Repository and Cognitive and Predictive Engines.
KPMG Intelligent Underwriting Engine gathers and aggregates data from external sources and applies cognitive capabilities to infer from data meaningful signals and “cause and effect” indicators of risk. This allows for a customer-focused operating model that reduces the time to generate policies and allows skilled human resources to focus on complex pricing, products, and risk profiles.
KPMG Intelligent Underwriting Engine helps underwriters understand and act promptly on emerging trends, identify operational issues or opportunities in real time, and price risk more accurately. It supports better decision making and faster processing, leading to higher profits. New underwriting insights improve application process flow, leading to better customer service and increased productivity.
Intelligent Underwriting Engine – business value
Underwriting for all types and sizes of insurance-related businesses faces a future of digital transformation. KPMG Intelligent Underwriting Engine responds to the need for better risk insights and faster underwriting lifecycles by providing an Azure-based solution that “listens” to big data real-time to identify risk factors and delivers policies to customers quicker via a digitized platform.
Sensing signals of risk: KPMG’s Signals Repository
Traditional decision models are predicted on a handful of exogenous factors; KPMG’s signal repository enables these same valuation decisions to be driven by thousands of data points, thus materially improving accuracy and outcomes and providing the cognitive engine meaningful data sets for deep learning. The system continues to improve or “learn” as more data is entered and more signals and causal correlations are identified. KPMG benchmarks sources together with enterprise, third party, consumer, social, and government data helps to create market, product, and consumer signals for intelligent risk profiles and recommendations.
With the Always On Signals Repository, traditional underwriting data is joined with several massive databases, improving risk estimates in ways that were not possible before, allowing insurers to come up with much more accurate scores.
Action map for insurers
As insurance underwriters progress down the transformational path, changes across the underwriting value
chain have brought chief executive officers to a cross roads. Now, the question is not about whether to move forward, but about the route to be taken. It is a challenge to manage many moving paths, involving a range of processes in the underwriting value chain with limited concrete success stories. It is recommended that the path forward be evaluated based on the current situation, corporate strategy, and profit-and-loss goals.
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