Cure Rate

From Open Risk Manual

Definition

Cure Rate is a metric used in the context of Non-Performing Loan management. It denotes the percentage of loans that previously presented arrears (where in delinquency) and, post restructuring, present no arrears.

Given the possibility that a cured credit asset can relapse into delinquency, (Re-Default Rate) the time horizon over which the cure rate is defined must be explicit.

Cure Types

Cure of arrears on facilities presenting arrears could take place either

  • through forbearance measures of the credit facility (forborne cure) or
  • naturally without modification of the original terms of the credit facility (natural cure).

Banks should have a mechanism in place to monitor the rate and the volume of those defaulted credit facilities cured naturally.[1]

Cure Period

Given the fact that most of the loans will present no evidence of financial difficulties right after the modification, a cure period is needed to determine whether the loan has been effectively cured. The minimum cure period applied to determine cure rates should be 12 months (aligned with the minimum cure period defined in[2]) . Thus, banks should conduct a vintage analysis and monitor the behaviour of forborne credit facilities after 12 months from the date of modification to determine the cure rate. This analysis should be conducted per loan segment (borrower with similar characteristics) and, potentially, the extent of financial difficulties prior to forbearance.

The re-default rate is another key performance indicator that should be included in internal NPL monitoring reports for the management body and other relevant managers.

IFRS 9

From an accounting perspective an exposure that is "cured" (ceases to be delinquent) will be considered a new asset if the old exposure has been derecognized post renegotiation/modification. If the exposure has not been derecognized, it can be in-principle either a Stage 1 Asset or a Stage 2 Asset, depending on the assessment of credit risk taking the entire history into account. More specifically the standard stipulates[3]:

If the contractual cash flows on a financial asset have been renegotiated or otherwise modified, but the financial asset is not derecognised, that financial asset is not automatically considered to have lower credit risk. An entity shall assess whether there has been a significant increase in credit risk since initial recognition on the basis of all reasonable and supportable information that is available without undue cost or effort. This includes historical and forward-looking information and an assessment of the credit risk over the expected life of the financial asset, which includes information about the circumstances that led to the modification.

Evidence that the criteria for the recognition of lifetime expected credit losses are no longer met may include a history of up-to-date and timely payment performance against the modified contractual terms. Typically a customer would need to demonstrate consistently good payment behaviour over a period of time before the credit risk is considered to have decreased. For example, a history of missed or incomplete payments would not typically be erased by simply making one payment on time following a modification of the contractual terms.

Model Estimation Guidelines

For regulated financial institutions (banks) the cure rate applicable to a individual Non-Performing Loan / Stage 3 Asset must be estimated in order to support the overall Loss Allowance calculation (which also affects the NPL Risk Capital calculation).

Guidance on Cure Rate model estimation is adapted from[4]. The assumption is that quantitative estimation of cure rates is possible for collectively managed exposures.

  • Cure Rates estimated on a collective basis should be based on historical loss experience for assets with credit risk characteristics similar to those in the group.
  • They should be adjusted on the basis of current observable data to reflect the effects of current conditions that did not affect the period on which the historical loss experience is based and the effects of conditions in the historical period that do not exist currently should be removed.

In applying these requirements, the following should be taken into account:

  • when estimating cure rates for collective provisioning models, the levels of management judgement should be minimal, and parameter estimations for collective provisioning models should be based on time series data
  • any parameters should be reflective of the credit characteristics of each appropriately stratified loan pool
  • the assessment of financial/economic conditions should take into account all relevant factors that have a bearing on cure rates, including (but not limited to)
    • macroeconomic variables (e.g. GDP, unemployment, property prices)
    • changes in relevant laws (e.g. bankruptcy code)
    • changes in international, national and local economic and business conditions
  • any possible impact deriving from changes in lending policies and procedures, extension of forbearance measures, write-off policy and recovery practices.

Modelling Approaches

A "Cure Event" for a given credit is a type of (positive) credit event and can be approached with the variety of tools available for default risk modelling. Some key dimensions

  • Whether the approach is estimated standalone or in conjunction with other credit states
  • Whether it is applied as a single period classification problem or as an ongoing state transition problem

A transitions-based framework is described in[5]

Issues and Challenges

  • False Cures is a term capturing the possibility that as a result of forbearance or other circumstances there is no genuine cure (hence Re-default)

References

  1. ECB: Guidance to banks on non-performing loans, March 2017
  2. EBA: Implementing Technical Standards (ITS) on supervisory reporting
  3. IFRS Standard 9, Financial Instruments, B5.5.27
  4. ECB: Guidance to banks on non-performing loans, March 2017
  5. A transitions-based framework for estimating expected credit losses, Edward Gaffney, Robert Kelly, Fergal McCann , Central Bank of Ireland November 2014

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