Rebuilding an expected credit loss model for a listed IT services company with US$855 million in receivables

The situation

The company is listed on the Saudi Exchange and serves government and large corporate clients on extended payment terms. Its receivables book was large relative to revenue, and its expected credit loss provision had turned into a recurring argument with the statutory auditor. Each reporting cycle ended in debate rather than documentation.

The challenge

• Loss rates taken from historical data alone, with no forward-looking information or link to economic conditions
• Loss given default hard-coded at 100 percent, with no calculation or support behind it
• No allowance for the time value of money, despite long collection cycles on government receivables
• Too little documentation to show the judgements built into the model

What we did

We started with a technical gap assessment of the existing model against each relevant requirement of IFRS 9, and agreed the findings with management before redesigning anything. The rebuild answered the concerns the auditor had raised.

The replacement combined three elements. Flow-rate analysis on ageing cohorts produced probability-weighted loss rates. Loss given default was calculated from actual recovery experience in each customer segment. Discounting captured the time value of money over realistic collection periods. On top of these sat a forward-looking layer that linked named economic indicators to the direction and size of any adjustment.

Segments followed the way credit risk actually differed across the book, with government and public sector exposure kept apart from corporate customers. The model was calibrated to the economics of the portfolio rather than to a target figure, and a methodology paper recorded each judgement, the reasoning behind it, and what would trigger a review.

The impact

• Full compliance with IFRS 9 across every part of the model
• Every credit loss query from the auditor resolved for the reporting period
• A documented methodology the finance team now runs and updates itself
• More confidence from the audit committee in the provisioning judgement

Client details are anonymised, and some facts are generalised to protect confidentiality.