Avoid Catastrophe: Harness the Power of Location-Based, Predictive Risk Management
Over 80% of all data now has a location-based aspect. Our geospatial analytics technology explores the relationships of risk data linked to a specific geographic location, driving predictive insights and helping to model potential future scenarios.
Predictive risk analytics can also transform underwriting processes and improve risk avoidance because insurers can model the potential impacts of peril events on insured properties during the quoting process, before the policy is issued.
Location-based, predictive risk analysis is driven by a single view of operational risk that comes from high quality and complete transactional data, precise geocoding and location intelligence, and superior visualization tools.
|LPA Software Solutions and Pitney Bowes have formed a partnership offering insurance companies best-in-class technology leveraging superior location-intelligence with the power of IBM predictive analytics to create a single view of risk, allowing you to not only anticipate catastrophe, but avoid it.|
The ability to visualize a single view of risk provides a competitive advantage by combining multiple layers of information together displaying valuable insight into the insured, such as:
Leveraging risk visualization through a single, clear view of risk puts greater decision making power in the hands of actuaries, claims executives, chief risk officers, and upper level management.
Attend this free webinar to learn about how LPA and Pitney Bowes' location-based, predictive risk management technology will help you:
- Make better risk management decisions, more quickly, and in the context of all other booked business
- Analyze risk exposure down to the policy holder level
- Optimize policy premiums through risk-based pricing
- Discover unanticipated "hidden" risk
- Improve responsiveness and productivity by predicting fraudulent claims, fast tracking valid ones
- Manage agents more effectively by predicting the best cross-sell leads and increasing agent retention
- Retain at-risk customers by discovering policy termination profiles and predict new offers likely to prevent them from leaving