Significant increase in financial loss in comparison with increase of premium payments over the years draws attention. Accurate ratio is estimated as 1,3% of demands even though some abuses are detected.
Most common abuse types,
It is possible to prevent abuses by detecting anomalies in fire insurance during production. Possible damages and anomalies are detected by using machine learning algorithms before they occur because of weather conditions or other reasons.
Main success points of preventing productions having high abuse risk