IIL and Jaywing launch new broker price optimisation product
The IFRS 9 deadline draws closer: Are you ready?
Coventry Building Society prepares for IFRS 9 within 10 weeks
22 June 2016
Coventry Building Society appointed credit risk analytics expert, Jaywing, to help support them through the design of IFRS 9 compliant models.
The Society was founded in 1884 and prides itself on being committed to putting their members first in everything they do. That’s why Coventry Building Society appointed Jaywing to ensure it meets the guidelines to a best practice standard and well ahead of the 2018 deadline.
Jaywing was tasked with developing prototype IFRS 9 models for one of the Society’s key mortgage portfolios. The Society understood the benefits from a ‘test and learn’ prototype approach, considering the complexity associated with these forward-looking Expected Credit Loss (ECL) models. Early insight of the IFRS 9 models has enabled the Society to understand the data and compliance requirements and provided assurance around the ability to implement the models onto their systems.
As a result of Jaywing’s involvement, Coventry Building Society has been able to gain internal approval of their IFRS 9 design based on the prototype model, which was built within demanding timescales, thus enabling the project to progress to full model build. This will stand them in good stead during the final development process when models will be deployed across the remaining portfolios. Jaywing helped the Society to execute a best practice standard to IFRS 9, all without impacting on their day-to-day business.
John Lowe, Finance Director at Coventry Building Society, said: “Jaywing brings a wealth of IFRS 9 experience and combines excellent modelling credentials with extensive industry knowledge. Their development of high quality ECL models within tight timescales means that we are well placed to achieve IFRS 9 compliance within our project timescales.”
Jaywing will continue to work with Coventry Building Society throughout IFRS 9 and beyond to learn how these robust and predictive long-range loss forecasting models are utilised for future stress testing and forecasting exercises as well as leveraged for pricing and business or investment strategies.