Background:

Banks and credit granters are facing an uphill battle since the launch of the new IFRS9 Financial Reporting Standard, which came into effect on 1st January 2018. The new financial standard has credit granters frantically trying to ensure that they are now reporting in line with a far more detailed and transparent accounting standard compared to legacy methods (IAS39).

McKinsey & Company calls it “a silent revolution in banks’ business models”, mentioning that organisations will need to make fundamental changes to their business model, affecting areas including treasury, wholesale and retail credit, IT and operations. On a global scale, at least a 20% increase in impairments is expected as a one-off adoption, as well as a further 30-40% P/L volatility caused by fluctuations in the shape of the book as accounts are constantly migrating to and from different stage classifications (IFRS 9: A silent revolution in banks’ business models – McKinsey & Company, April 2017).

The focus of the new standard is correcting the previous backward-looking asset classification standard by incorporating future projections and scenarios (Expected Credit Loss – ECL), which is an understandable reaction to the financial crises seen around the world over the past decade. The new standard is forcing credit granters to adopt a completely new level of sophistication in their valuation methods, and an array of new principles in the form of life-time estimations calibrated by macro-economic drivers that need to be validated and proven upon audit.

Even in the Middle East, where there has been a considerably different business operating model often based on ‘subjective partnerships’, organisations will have to drastically alter their policies and their adherence will be tested. Geographical locations where data collection and storage have not been a priority over the past 10 years will suffer the most. They will have to apply a prescribed, over-compensated industry standard (IFRS 9: ready for impact – Deloitte, A Middle East Point of View).

In a nutshell, the IFRS9 framework comprises of three main components:

  • Classifications
  • Impairements
  • Hedge Accounting Principles

Thus far, organisations have been focussing on solving the analytical, model building side of IFRS9. But in fact, its implications are much wider, also touching the strategic and operational side of businesses. Therefore, it is important for organisations to see the overall picture, and turn their compliance survival mentality into opportunity thinking.

This paper is largely focused on classification and impairments within IFRS9

IFRS 9 – Classification and Provision Conceptual Process

Classification:

  • Stage 1 (Good Risk): No signs of risk deterioration since application (regular comparison), in-order and early delinquency (internal rating).
  • Stage 2 (Strain): Significant increase in Credit Risk (SICR), clear signs of potential future default based on numerous internal and external factors, pre-actual default definition.
  • Stage 3 (Loss Official): Already defaulted, aligned to previous Basel definition (Basel 2).

Impairments + Providing:

  • Stage 1 (Good Risk): Make use of a 12-month Probability of Default (PD) Point in Time (PIT) model. Expected Credit Loss (ECL) = 12 month Probability of Default (PD) x Loss Given Default (LGD) x Exposure at Default (EAD). Prescribed and mainly quantified methodology.
  • Stage 2 (Strain): Make use of a Lifetime Probability of Default (PD) Point in Time (PIT) model, also bringing in macro variables like GDP growth, debt burden, unemployment rate and specific industry exposure modelled through numerous stress scenarios. Expected Credit Loss (ECL) = Lifetime Probability of Default (PD) x Loss Given Default (LGD) x Exposure at Default (EAD). Make use of discounted EAD, only recognising cash flows from the predicted window before default. ECL should also be calculated at each time point in the remaining tenure and should be discounted back to the point of reporting. A survival model can be used to predict time before default. Less prescribed methodology making use of experience overrides. Methodology needs to be validated and proven.
  • Stage 3 (Loss Official): Expected Credit Loss (ECL) = Lifetime Probability of Default (now 100%) x Loss Given Default (LGD1 / LGD2) x Exposure at Default (EAD). Make use of discounted EAD, only recognising cash flows (recoveries) projected post default, excluding interest. Prescribed and mainly quantified methodology.

Blessing or Curse?

Instead of looking at this as a negative, time-consuming and cost-intensive exercise, many organisations are seeing it as an opportunity for future competitive advantage.

On the opportunity side, many organisations are viewing the new standard as one that will separate the ‘analytical investors’ from the ‘compliant survivors’.

  • Opportunities include a far more aligned strategy from finance, credit risk and operations, bringing together the age old silos.
  • Organisations see implications across the whole credit customer life cycle in terms of prioritisation and treatment, from setting risk appetite and portfolio management to early collections.
  • Seasonally robust coverage will future-proof business liquidity and an improved portfolio shape will drive sustainability. Timely recognition using good modelling practices will protect the organisations from high ticket unplanned write-offs and P/L fluctuation.
  • More granular segmentation will also drive customer economic stage related actions in the form of communication and responsible lending (CX).
  • The portfolio product mix will be considered as a whole (collateral based vs non-collateral based lending), forcing a merged product P/L view and a subsequent one customer view.
  • Drive the right industry focus. Proactive risk policies based on specific industries (for example, the mining industry customer might be performing worse compared to a financial industry customer). Grow the most profitable industries.
  • Considerations around product lifetime period and more flexible T/Cs enable pricing over the lifetime to ensure future profitability.
  • Provisioning on non-defaulted accounts will ensure a more profitable focus when it comes to marketing and proactive risk management.
  • Proactive migration prevention from Stage 1 to 2, and curing from 2 to 1 will focus prioritisation strategies.
  • Improved commercial customer relationships on the back of proactive risk management.

Whether the IFRS9 reporting standard is a good thing for business remains to be seen, but it will surely improve the way organisations use analytics to segment and prioritise their actions, drive improved transparency, and encourage responsible lending.

We can get you on a solid path to IFRS 9 compliance

Qarar is a leading analytical, advisory and software provider in the GCC and can assist organisations on competing post IFRS 9.

Analytical (IFRS9 Models):  

  • Build new 12-month PD, lifetime PD, LGD and EAD models.
  • Validate your existing PD, lifetime PD, LGD and EAD models.

Advisory:

  • Advise on your existing IFRS9 framework by doing a proactive strategy assessment across the customer credit life cycle.
  • Automating IFRS9 models.
  • Proactive strategy best practice advice including:
    • Origination policy including scorecards, limit setting, risk-based pricing and manual sanctioning.
    • Customer management including behavioural scorecards, limit management, authorisation, activation, utilisation, cross-sell, upsell, loyalty and retention strategies.
    • Proactive and reactive collections strategies.