Risk Management


 
risk management

Success always comes with risk

Complexity and risk are permanent components of business management. The more aggressive you want to be on your business, the more non-restrictive you may have to be with your customers. However, facing a payment default or a misuse of your products will have direct impacts on your bottom line. Those risks arise all along the customer lifecycle, from the moment you sign the contract and have to evaluate his or her solvency, to the moment you invoice him or her, when you have to decide your policy for cash collection . In each case, predictive analytics can enable companies to mitigate risk andadapt policies to the profile of your customers.

 

Profiling your customers to reduce your risks

Mitigating risk is not only about applying static rules to prevent misuse. Risk patterns shift over time, fraudsters adapt and play hide-and-seek, new products come with new customers and new behaviours. Tuning those rules is a real challenge for risk management systems. It can be done externally by your vendors and will capture standard behaviours but not necessarily your specificities or it can be done internally but might require a significant effort. This is where Machine Learning can play a significant role.

 

How to use PredicSis.ai to improve Risk Management?

PredicSis.ai learns automatically from your customers’ behaviour to identify patterns and evaluate risks. Through simply connecting with your historical invoice or payment defects data, PredicSis.ai can provide automatic profiles of risky customers , risky contracts or risky invoices. PredicSis.ai will learn from all available data you provide it with, from various sources and will highlight any weaknesses that may be used for prevention.