Abstract: The present disclosure describes method and system for estimating the accumulated-exposure of an insurance company. The accumulated-exposure can be estimated per an insured customer, per an insurance event or per period of time. Some example embodiments of the disclosed technique take into consideration the history of the insured customer. Yet, some example embodiments of the disclosed technique take into consideration the frequent of appearance of an insurance event. Some embodiments of the disclosed technique are configured to alert when the accumulated-exposure is greater than a predefined threshold.

Abstract: The present disclosure describes method and system for recommending configuration of one or more environmental control devices that are associated with a certain cargo shipping unit (CSU) and carries a certain type of cargo. Some example embodiments of the disclosed technique recommend a certain configuration based on the “Wisdom of the crowd” (WOTC) and selects the most popular configuration that is used in similar cases as the recommended configuration. Other example embodiments of the disclosed technique may recommend a configuration that has low probability that damage may occur while using the recommended configuration.

Abstract: The present disclosure describes method and system for predicting the actual liability that is related to a certain event. An example embodiment of the disclosed technique may obtain a form of a demand for loss (DFL). Some example embodiments of the disclosed technique may predict the extend of loss (EoL) of a certain DFL that is related to event. Based on the predicted EoL and information retrieved from to the relevant bill-of-lading (BoL) an embodiment of the disclosed technique is configured to predict the actual liability that is related to that event. An example event can be a ship that was drowned.

Abstract: The present disclosure describes method and system for determining the extent of loss (EoL) that is related to a certain shipment of a certain type of goods along a certain path of a journey. An example embodiment of the disclosed technique may obtain a form that describes a loss (FTDL). The FTDL comprises a plurality of parameters that are related to that shipment, parameters such as but not limited to type of the cargo, temperature, relative humidity, acceleration, vibration, season of the year, etc. Some example embodiments of the disclosed technique may express the EoL by two or more ranks.

Abstract: The present disclosure describes method and system for recommending on a certain alternative for transporting a certain type of goods from an origin to a destination, wherein the recommendation is based on the predicted extent of loss (EoL) that is related to each alternative. Some example embodiments of the disclosed technique may express the EoL by two or more ranks.

Abstract: A cargo management system for handling cargo transportation is disclosed. The management system can be configured to determine the risk that is involved in a journey of a cargo-shipping-unit (CSU). The system comprises a Risk-Analyzer-Unit (RAU). The RAU can be configured to obtain one or more features of the journey of that CSU. Next the RAU can fetch a predictive model that can predict the likelihood that a demand for loss (DFL) will be filed. In addition the RAU can be configured to present the likelihood that a demand DFL will be filed as the risk that is associated with that journey of that CSU.

Abstract: A cargo management system for handling cargo transportation is disclosed. The management system can be configured to obtain information regarding one or more alternative routes of a journey of a cargo-shipping-unit (CSU). The system comprises an operational recommending unit (ORU), which is configured to obtain one or more define targets that are related to the type of cargo that is carried by the CSU and to present the impact of each alternative route on each of the define targets.

Abstract: Cargo management system for handling demand for loss (DFL) is disclosed. The management system is configured to obtain a DFL that is related to a certain journey, wherein the journey can comprise one or more segments. Based on analyzing the obtained DFL the system can recommend whether a filed DFL is for real occurred damages. In addition, the system can point on a suspected cause for the damage as well as the suspected segment of the journey in which the damage occurred.