Standard Chartered Bank
Directors’ Report and Financ
ial Statements 2022
159
Independent Auditor’s report
to the members of Standard Chartered Bank continued
Risk
Our response to the risk
Key observations
communicated to the
Audit Committee
Credit Impairment
Accounting polic
ies (page 187); Note 8 of the
financial statements; and relevant cred
it risk
disclosures (includ
ing pages 70 and 72)
At 31 December 2022, the Group reported
total credit impa
irment balance sheet
provis
ion of $4,601 m
ill
ion (2021: $5,377 m
ill
ion).
Management’s judgements and estimates
are especially subject
ive due to s
ign
ificant
uncertainty associated with the estimat
ion
of expected future losses. Assumptions with
increased complexity in respect of the tim
ing
and measurement of expected credit losses
(ECL) include:
•
Staging
– the determinat
ion of s
ign
ificant
increase in credit risk and resultant timely
allocation of assets to the appropriate
stage in accordance with IFRS 9;
•
Model output and adjustments
–
Accounting interpretat
ions, modell
ing
assumptions and data used to build and
run the models that calculate the ECL,
includ
ing the appropr
iateness, completeness
and valuation of post-model adjustments
applied to model output to address risks
not fully captured by the models;
•
Economic scenarios
– Sign
ificant judgements
involved with the determinat
ion of parameters
used in the Monte Carlo Simulat
ion and the
evaluation of the appropriateness of the
output from the model in terms of the extent
to which it adequately generated non-
linear
ity,
includ
ing the assessment of any
Post Model adjustments;
•
Management overlays
– Appropriateness,
completeness and valuation of risk event
overlays to capture risks not ident
ified by
the credit impa
irment models,
includ
ing the
considerat
ion of the r
isk of management
override; and
•
Indiv
idually assessed ECL allowance
s –
Measurement of ind
iv
idual provis
ions
includ
ing
the assessment of probabil
ity we
ighted
recovery scenarios, exit strategies, collateral
valuations and time to collect.
In 2022, the most material factors impact
ing
the ECL were in relation to the sovereign
downgrades, the enhanced Monte Carlo model
and the impact of the global economic
environment includ
ing the
impact of relaxing
pandemic restrict
ions. In add
it
ion, where relevant
we considered the impact of climate on the
impa
irment prov
is
ions. We cons
ider that the
combinat
ion of these factors has
increased the
risk of a material misstatement to the ECL.
We evaluated the design of controls relevant to the
Group’s processes over material ECL balances, includ
ing
the judgements and estimates noted, involv
ing EY
special
ists to ass
ist us in performing our procedures to
the extent it was appropriate. Based on our evaluation
we selected the controls upon which we intended to rely
and tested those for operating effectiveness.
We performed an overall stand-back assessment of the
ECL allowance levels by stage to determine if they were
reasonable by consider
ing the overall cred
it quality of the
Group’s portfolios, risk profile and the impact of sovereign
downgrades. Our assessment also included the evaluation
of the macroeconomic environment by consider
ing trends
in
the economies and countries to which the Group is exposed,
and the consequences of the easing of global restrict
ions
from the pandemic. We performed peer benchmarking
where available to assess overall staging and provis
ion
coverage levels.
Staging
– We evaluated the criter
ia used to determ
ine
sign
ificant
increase in credit risk includ
ing quant
itat
ive
backstops with the resultant allocation of financ
ial assets
to stage 1, 2 or 3 in accordance with IFRS 9. We reperformed
the staging distr
ibut
ion for a sample of financ
ial assets
and assessed the reasonableness of staging downgrades
applied by management.
To test credit monitor
ing wh
ich largely drives the probabil
ity
of default estimates used in the staging calculation, we
challenged the risk ratings (includ
ing appropr
iate operation
of quantitat
ive backstops) for a sample of perform
ing
accounts and other accounts exhib
it
ing risk characterist
ics
such as financial d
iff
icult
ies, deferment of payment, late
payment and watchlist. We also considered the vulnerable
sectors (as defined by the PLC Group).
Modelled output and adjustments
– We performed a risk
assessment on models involved in the ECL calculation using
EY independently determined criter
ia to select a sample
of models to test. We engaged our modelling special
ists
to evaluate a sample of ECL models by assessing the
reasonableness of underpinn
ing assumpt
ions, inputs and
formulae used. This included a combinat
ion of assess
ing the
appropriateness of model design, formulae and algorithms,
alternative modelling techniques and recalculating the
Probabil
ity of Default, Loss G
iven Default and Exposure at
Default parameters. Together with our modelling special
ists,
we also assessed material post-model adjustments which
were applied as a response to risks not fully captured by the
models, includ
ing the completeness and appropr
iateness of
these adjustments, for which we considered the applied
judgments and methodology, and governance thereon.
In response to the new or enhanced models implemented
this year to address known weaknesses in previous models,
we performed substantive testing procedures, includ
ing
code review and implementat
ion test
ing.
We reperformed model monitor
ing procedures for
models classif
ied as h
igher risk in accordance with our EY
independent risk assessment.
To evaluate data quality, we agreed a sample of ECL
calculation data points to source systems, includ
ing, among
other data points, balance sheet data used to run the
models. We also tested a sample of the ECL data points
from the calculation engine through to the general ledger
and disclosures.
We highl
ighted the
following matters to
the Audit Committee:
•
the pathway to achieve
a controls reliance audit
for the Group’s models;
• our evaluation of
management’s
high-level assessment
of the potential impact
on ECL from climate
change;
•
our assessment of the
Group’s enhanced
Monte Carlo approach
includ
ing benchmark
ing
the impact of non-
linear
ity from the
baseline ECL against
UK peers and the
non-linear
ity overlay for
retail exposures; and
•
our assessment of the
appropriateness of the
Group’s methodology
used to determine
the ECL in relation to
sovereign downgrades
includ
ing the
completeness and
rationale for country
downgrades and the
resultant overlays and
ECL impact.
We concluded that
management’s
methodology, judgements
and assumptions used
in calculating credit
impa
irment are mater
ially
in accordance with the
accounting standard.