Fannie Mae 2011 Annual Report Download - page 77

required to expend significant additional resources to modify our protective measures or to investigate and
remediate vulnerabilities or other exposures arising from operational and security risks.
Since the conservatorship began, we have experienced, and we expect we may continue to experience, substantial
changes in our management, employees and business structure and practices. These changes could increase our
operational risk and result in business interruptions and financial losses. In addition, due to events that are wholly
or partially beyond our control, our systems could fail to operate properly, which could lead to financial losses,
business disruptions, legal and regulatory sanctions and reputational damage.
In many cases, our accounting policies and methods, which are fundamental to how we report our financial
condition and results of operations, require management to make judgments and estimates about matters that
are inherently uncertain. Management also relies on models in making these estimates.
Our accounting policies and methods are fundamental to how we record and report our financial condition and
results of operations. Our management must exercise judgment in applying many of these accounting policies and
methods so that these policies and methods comply with GAAP and reflect management’s judgment of the most
appropriate manner to report our financial condition and results of operations. In some cases, management must
select the appropriate accounting policy or method from two or more alternatives, any of which might be reasonable
under the circumstances but might affect the amounts of assets, liabilities, revenues and expenses that we report. See
“Note 1, Summary of Significant Accounting Policies” for a description of our significant accounting policies.
We have identified three accounting policies as critical to the presentation of our financial condition and results
of operations. These accounting policies are described in “MD&A—Critical Accounting Policies and Estimates.”
We believe these policies are critical because they require management to make particularly subjective or
complex judgments about matters that are inherently uncertain and because of the likelihood that materially
different amounts would be reported under different conditions or using different assumptions.
Because our financial statements involve estimates for amounts that are very large, even a small change in the
estimate can have a significant impact for the reporting period. For example, because our total loss reserves are
so large, even a change that has a small impact relative to the size of our loss reserves can have a meaningful
impact on our results for the quarter in which we make the change.
Due to the complexity of the critical accounting policies we have identified, our accounting methods relating to
these policies involve substantial use of models. Models are inherently imperfect predictors of actual results
because they are based on assumptions, including assumptions about future events. Our models may not include
assumptions that reflect very positive or very negative market conditions and, accordingly, our actual results
could differ significantly from those generated by our models. As a result of the above factors, the estimates that
we use to prepare our financial statements, as well as our estimates of our future results of operations, may be
inaccurate, perhaps significantly.
Failure of our models to produce reliable results may adversely affect our ability to manage risk and make
effective business decisions.
We make significant use of quantitative models to measure and monitor our risk exposures and to manage our
business. For example, we use models to measure and monitor our exposures to interest rate, credit and market
risks, and to forecast credit losses. The information provided by these models is used in making business
decisions relating to strategies, initiatives, transactions, pricing and products.
Models are inherently imperfect predictors of actual results because they are based on historical data and
assumptions regarding factors such as future loan demand, borrower behavior, creditworthiness and home price
trends. Other potential sources of inaccurate or inappropriate model results include errors in computer code, bad
data, misuse of data, or use of a model for a purpose outside the scope of the model’s design. Modeling often
assumes that historical data or experience can be relied upon as a basis for forecasting future events, an
assumption that may be especially tenuous in the face of unprecedented events.
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