Model Development
Whether its building models from first principles or enhancing existing models, we always employ industry standard approaches that are commensurate to our client’s size and ambitions.
Our approach is based upon estimating IFRS 9 ECLs using the standard components of PD, EAD and LGD, with the application of discounting and compliant stage allocation applied.
PD
The probability of the account moving to default status within the forward-looking period. The PD is typically the most sophisticated component in the ECL framework due to the accessibility to its data drivers, the stronger trends with idiosyncratic and exogenous risk and the higher predictability and robustness from modelling it using statistical techniques.
EAD
The exposure or balance at the point of default. The approach to EAD is dependent upon the type of loan: amortising loans are modelled by simulating the pay-down of the capital balance of the loan and revolving is based on modelling the expected balance in the event of default, often modelled in relation to the limit.
LGD
The loss incurred given the account has defaulted. The approach to LGD is split by whether the loan is secured by collateral with the expected value of the collateral driving the magnitude of the loss. Modelling LGD can be challenging as it relies on sufficient loss cases although pragmatic workarounds can be deployed.
Stage Allocation
Stage Allocation is the assignment into accounts into 1 of 3 stages depending on the performance of the account.
Stage 1: Performance accounts (not stage 2 or 3.)
Stage 2: Under performing accounts that are either more than 30 days past due or an equivalent or have experienced a significant increase in credit risk which is informed by material shifts in lifetime PD from origination.
Stage 3: Non-performing or accounts in default.
ECL
The ECL is calculated by combining the PD, EAD and LGDs with the stage 1 accounts measuring ECLs over a 12-month period and stage 2 and 3 over a lifetime period with the losses discounted using EIR.
The ECLs are generally estimated under multiple economic scenarios with the final ECL being the probability weighted average of all scenarios.
What made Jaywing stand apart is their partnership engagement approach, their practical experience in risk modelling and loss forecasting, their flexibility and adaptability, and ultimately their commitment to timely delivering the solutions within budget to help the bank achieve its strategies including IFRS9 compliance.
“Jaywing has already proven to us through our existing partnership that they are industry-leading modelling, forecasting and regulatory experts. It was only natural to ask them to support us with the challenge of developing IFRS 9 stress testing models for our ICAAP. Once again, they surpassed our expectations."
"It was imperative that we selected a consultancy with the depth and breadth of technical modelling expertise, comprehensive knowledge of the regulation and a reputation for rigour with the regulators. Jaywing exemplified these attributes from the very beginning of our partnership and were proactive in aligning to our governance practices."