ECL for trade receivables

ECL for trade receivables:
What is the challenge?
• Ad-hoc provision matrix no longer acceptable.
• Provision matrix should be based on historical loss percentage.
• Historical loss percentage is computed from the bucketed snapshot of receivables data.
• However, this is difficult to compute this manually using spreadsheet.
How do you derive the bucketed snapshot of receivables data?
• For this just upload the raw data namely customer master, invoices and collections data.
• The system computes the bucketed snapshot automatically.

Should I provide the invoice reference for the collections?
• Absolutely no need.
• The system allocates the collections based on FIFO.
• The reason is that we are concerned only about the credit risk here for ECL computation.
Is it necessary to consider forward-looking macroeconomic data?
• Yes, it is.
• As per the Standard, you must create additional two scenarios, based on macroeconomic data.
• Then compute the probability weighted ECL.
How does this tool take care of this requirement?
• Upload the macro data like say GDP growth rate, inflation rate, unemployment rate, interest rate etc.,
• The system will automatically run a multi-variate regression analysis.
• Based on the statistical results, the system will build additional two scenarios on the fly.
What are the Benefits of this cloud-based tool?
• Designed by professional accountants having in depth practical experience.
• Developed by hard core software engineers.
• Hosted on cloud servers - Amazon Web Servers which is best in the class.
• Complete audit trail available.
• Extremely fast processing thanks to load balancing features offered by AWS.