Typically, a corporate credit default begins when the economy or economic sector of which the company belongs is not doing well. For example, the crash in oil price in 2014. There will be (1) increase in market interest (internet searches) for this company. This spike in interest will be followed by news reports/analysis/commentaries which project a (2) negative market sentiment on the company. Its corresponding (3) stock (or bond) price will fall either simultaneously or shortly after. If the distress is felt throughout the economic sector (as in the case of oil prices), the company peers will also experience the (4) negative impact. Nonetheless, the trigger for the deterioration in the relationship component, for example, loss of major customers or major suppliers are unable to deliver, shareholders deterioration could also take place before an increase in market interest.

With the business operations negatively impacted, the company's (5) balance sheet will be weaken and may lead to breaches of loan covenants (e.g. positive cashflow after operations), triggering the lending bank to take action like asking for more collateral (a form of margin call) or withdraw credit lines. Eventually, if the company is (6) unable to fulfil the obligation/repayments (delinquent) or continue as an on-going concern, it will draw down all its credit facilities with all its banks before default. Finally, it defaults on all its obligations.

SamTech's unique Artificial Intelligence-powered Early Warning System (AIEWS) captures each stage of the corporate distress and flags them to our clients in real-time. We offer standalone modules with active monitoring based on multiple indicators and lenses. Users can set their monitoring thresholds for each module based on their risk appetite. When a module identifies a distress while the others are dormant, the user will be alerted. This overcomes the constraints of a single metric (e.g. Probability of default (PD)) for monitoring. In addition, each module can explain why early distress is detected based on the specific module alert. Current market products simply indicate that PD has deteriorated and further in-depth analysis is required to find out the reason for the deterioration.