JP Morgan Chase 2015 Annual Report Download - page 176

Management’s discussion and analysis
166 JPMorgan Chase & Co./2015 Annual Report
Overall, the allowance for credit losses for the consumer
portfolio, including credit card, is sensitive to changes in the
economic environment (e.g., unemployment rates),
delinquency rates, the realizable value of collateral (e.g.,
housing prices), FICO scores, borrower behavior and other
risk factors. While all of these factors are important
determinants of overall allowance levels, changes in the
various factors may not occur at the same time or at the
same rate, or changes may be directionally inconsistent
such that improvement in one factor may offset
deterioration in the other. In addition, changes in these
factors would not necessarily be consistent across all
geographies or product types. Finally, it is difficult to
predict the extent to which changes in these factors would
ultimately affect the frequency of losses, the severity of
losses or both.
PCI loans
In connection with the Washington Mutual transaction,
JPMorgan Chase acquired certain PCI loans, which are
accounted for as described in Note 14. The allowance for
loan losses for the PCI portfolio is based on quarterly
estimates of the amount of principal and interest cash flows
expected to be collected over the estimated remaining lives
of the loans.
These cash flow projections are based on estimates
regarding default rates (including redefault rates on
modified loans), loss severities, the amounts and timing of
prepayments and other factors that are reflective of current
and expected future market conditions. These estimates are
dependent on assumptions regarding the level of future
home price declines, and the duration of current overall
economic conditions, among other factors. These estimates
and assumptions require significant management judgment
and certain assumptions are highly subjective.
Formula-based component — Wholesale loans and lending-
related commitments
The Firm’s methodology for determining the allowance for
loan losses and the allowance for lending-related
commitments involves the early identification of credits that
are deteriorating. The formula-based component of the
allowance calculation for wholesale loans and lending-
related components is the product of an estimated PD and
estimated LGD. These factors are determined based on the
credit quality and specific attributes of the Firm’s loans and
lending-related commitments to each obligor.
The Firm assesses the credit quality of its borrower or
counterparty and assigns a risk rating. Risk ratings are
assigned at origination or acquisition, and if necessary,
adjusted for changes in credit quality over the life of the
exposure. In assessing the risk rating of a particular loan or
lending-related commitment, among the factors considered
are the obligor’s debt capacity and financial flexibility, the
level of the obligor’s earnings, the amount and sources for
repayment, the level and nature of contingencies,
management strength, and the industry and geography in
which the obligor operates. These factors are based on an
evaluation of historical and current information and involve
subjective assessment and interpretation. Determining risk
ratings involves significant judgment; emphasizing one
factor over another or considering additional factors could
affect the risk rating assigned by the Firm.
PD estimates are based on observable external through-
the-cycle data, using credit rating agency default statistics.
A LGD estimate is assigned to each loan or lending-related
commitment. The estimate represents the amount of
economic loss if the obligor were to default. The type of
obligor, quality of collateral, and the seniority of the Firm’s
lending exposure in the obligor’s capital structure affect
LGD. LGD estimates are based on the Firm’s history of actual
credit losses over more than one credit cycle. Changes to
the time period used for PD and LGD estimates (for
example, point-in-time loss versus longer views of the credit
cycle) could also affect the allowance for credit losses.
The Firm applies judgment in estimating PD and LGD used
in calculating the allowances. Wherever possible, the Firm
uses independent, verifiable data or the Firm’s own
historical loss experience in its models for estimating the
allowances, but differences in characteristics between the
Firm’s specific loans or lending-related commitments and
those reflected in external and Firm-specific historical data
could affect loss estimates. Estimates of PD and LGD are
subject to periodic refinement based on any changes to
underlying external and Firm-specific historical data. The
use of different inputs would change the amount of the
allowance for credit losses determined appropriate by the
Firm.
Management also applies its judgment to adjust the
modeled loss estimates, taking into consideration model
imprecision, external factors and economic events that have
occurred but are not yet reflected in the loss factors.
Historical experience of both LGD and PD are considered
when estimating these adjustments. Factors related to
concentrated and deteriorating industries also are
incorporated where relevant. These estimates are based on
management’s view of uncertainties that relate to current
macroeconomic and political conditions, quality of
underwriting standards and other relevant internal and
external factors affecting the credit quality of the current
portfolio.
Allowance for credit losses sensitivity
As noted above, the Firm’s allowance for credit losses is
sensitive to numerous factors, which may differ depending
on the portfolio. Changes in economic conditions or in the
Firm’s assumptions and estimates could affect its estimate
of probable credit losses inherent in the portfolio at the
balance sheet date. The Firm uses its best judgment to
assess these economic conditions and loss data in
estimating the allowance for credit losses and these
estimates are subject to periodic refinement based on any
changes to underlying external and Firm-specific historical
data. In many cases, the use of alternate estimates (for
example, the effect of home prices and unemployment rates