To clarify the reason of this rather naive post, banks are not lending to small companies because the risk perceived is too high. However, the way banks assess risk is mainly based on financial data and on some basic overview of operational performance. If banks were instead capable of having statistics on a company's performance throughout the end-to-end supply (i.e., value) chain, then the risk profile would be more accurate and banks could decide what portion of risk they want to take and how to price it accordingly. 

Just as the lifecycle of a vehicle or of a person are mapped to then identify specific "trigger points" that are statistically measured to determine the likelihood of certain events to happen-and therefore calculate correspondent actuarial values to properly price the insurance premium-the same should be possible for supply chain processes (e.g., procurement, manufacturing, shipping, distribution). 

My assumption is that an insurance company is already able of slicing and dicing the lifecycle of- i.e., a vehicle's- value chain thanks to the actuarial tables values of that value chain. Insurance premiums are then calculated and offered to clients. Why would the same not be possible for a supply chain? 

My assumption is that an insurance company is already able of slicing and dicing the lifecycle of- i.e., a vehicle's- value chain thanks to the actuarial tables values of that value chain. Insurance premiums are then calculated and offered to clients. Why would the same not be possible for a supply chain?