June 23-26, 2013
INFORMS Healthcare 2013
October 6–9, 2013
2013 INFORMS Annual Meeting
June 10-14, 2013
Predictive Analytics World
September 8-14, 2013
2013 ASE/IEEE International Conference on Big Data
New FICO solution accelerates ROI for insurance analytics
FICO, provider of analytics and decision management technology, recently launched a new solution aimed at improving the ROI for predictive models used in insurance. FICO® Model Central™ Solution for Insurance enables insurers to reduce model deployment times by as much as 50 percent, while also providing the first indications that a model's performance may be damaging profitability.
Insurers increasingly use predictive analytics models in mission-critical decisions, but today's model management processes hinder performance. Most insurers have inconsistent or inefficient methods for tracking model performance, updating models and implementing new models in production systems. In a recent FICO survey, 64 percent of insurers said they lacked the ability to rapidly deploy or update models to maximize business impact. One-third of insurers surveyed said that implementing a new model takes four-to-six months, and 51 percent said it takes six months or longer.
"Leading insurers rely on analytics across lines of business for marketing, customer management, underwriting, claims, and fraud prevention," said Russ Schreiber, FICO vice president and head of the company's insurance practice. "High-performing analytics are a cornerstone of high-performing insurers. The value Model Central offers is the ability to rapidly identify when model performance is drifting and then accelerate the deployment of more predictive models regardless of the modeling technology used."
"From mismatching product offers to getting the price wrong to missing fraudulent claims, weak analytic models hurt profitability," said Russ Schreiber, FICO vice president, who leads the company's insurance practice. "Yet in our recent survey, just 18% of insurers said they had a well-organized system for managing model performance. New insurance regulations such as Solvency II in Europe and similar proposals in the U,S. mandate that insurers do better than this."
FICO® Model Central(TM) Solution for Insurance provides a complete environment for managing predictive models in a reliable, automated and integrated way. It presents a management dashboard of overall model health, providing an "early warning system" that alerts personnel to performance degradation so they can take action before business decisions are impacted. It also creates a standardized process for easy management and monitoring of models, which have become central to business decisions made by insurers, and deploys new models quickly and efficiently - up to 50 percent faster - for improved time to value and return on investment.
Furthermore, FICO® Model Central(TM) Solution for Insurance coordinates model validation, task tracking and management reporting, storing complete and annotated audit trails to satisfy compliance requirements. It integrates models from various programming languages into one environment, further saving time and IT resources. It also improves business outcomes with the integration of simulation and testing capabilities and optimization of decisions.
For insurers operating within the European Union, FICO® Model Central Solution for Insurance lays a foundation for meeting Solvency II's capital adequacy and risk management requirements. It provides a view across silos, including geographies, lines of business, and process areas; access to legacy assets; improvements in data quality and availability, as well as advanced management of analytic assets; and complete transparency for audits. These capabilities also address insurance regulations in other parts of the world.
"An analytics-driven business organization is where insurers have to be," said Karen Pauli, a research director at CEB TowerGroup. "Those analytics need to be quickly deployed and actively managed to maximize their value to the business. Insurers that excel at the operational side of predictive models will have a competitive advantage in the market."