Not Being Aware of Disaster Risks Can Lead to Losses

disaster risk data

Did you know that the use of data analytics is changing the face of the insurance industry as well as other businesses? Analytics are also being employed in the spotting of troublesome claims that may cause losses to a business insuring people for natural disasters, such as floods, earthquakes and more.

All kinds of businesses want to get back to normalcy and be effective as soon as possible after a natural event. Minimizing the damage from natural disasters can help companies recover more quickly, avoiding a crisis from service interruptions. The key is in planning beforehand, and predictive analytics may be the answer.

Predictive Analytics

Predictive analytics is the future of insurance, as the use of artificial intelligence has entered the scene; it may help reduce issues of underwriting expenses. Data can be collected from a variety of sources, ensuring better prediction and understanding.

Some Uses of Analytics

It may be helpful in pricing and selection for risk. Data and feedback collected from smart devices, social media, and interactions of claims specialists and customers are accessed right at the source, rather than through such traditional sources as credit history, criminal records, etc.

Real-Time Information

Predictive planning and historical information may provide an accurate picture of the number of resources needed to cover the amount of anticipated work. Restoration can take place more quickly following a natural disaster, as customers are seen, and work is begun to give peace of mind to those affected.

Customers at Risk of Cancellation

Regarding insurance, predictive analytics may identify those customers who are at risk to cancel or want lower coverage. Insurers can identify those customers who may be unhappy with their insurer or their coverage. A personal connection can be made, in this case to ensure that those potential issues are alleviated.

Fraudulent Claims

Did you know that fraud makes up 5% to 10% of claims costs for insurers in the United States and Canada? Predictive analytics may spot fraud before it happens through the use of social media. After a claim is settled, data may be gathered, monitoring the insured person’s online activity for red flags.

Customer Loyalty

Companies can use predictive analytics to anticipate the needs of their customers while seeing their history. Brand loyalty is important when a company wants to keep its customer from turning to a competitor.

Potential markets can also be identified with data revealing behavioral patterns and common demographics and characteristics. With expanded global markets and social media interactions, much is now accessible.

It’s a wise move to learn more about how we can help you with predictive analytics, giving you the assurance you need. Live Earth can provide you with a competitive advantage, as well as minimization of losses. Your view of risk events expands with predictive modeling and the artificial intelligence of predictive analytics.

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