Companies employing the traditional, silo-based approach to managing market and credit risk are at a severe disadvantage in today's marketplace. Modeling the credit risk of obligors separate from modeling earnings forecasts produces inaccurate cash flows that don't capture the interplay between credit events and income accrual. If loss models are integrated, but unable to react consistently to forecasted risk drivers, companies can't easily quantify their impact on Provision/Allowance, stunting their ability to maximize returns on capital. Above all, institutions testing business strategies with earning forecasts that don't incorporate credit loss models miss the opportunity to refine those strategies based on best-practice calculations.

QRM's Credit Risk & Capital Management Practice understands the importance of a "bottom up" approach combining credit loss modeling with earnings forecasting to create credit loss-adjusted income. For over five years, our growing list of clients has been reaping the benefits of measuring and managing credit, market, and earnings risk for both consumer and commercial loan portfolios, in a single, integrated practice.

QRM clients model and measure the interest rate and credit risk of all on- and off-balance sheet instruments in one integrated process. By modeling and forecasting credit migrations, loan states, and draws on undfunded commitments, clients gain a greater understanding of their balance sheet's behavior under different economic scenarios and business strategies. Clients' forecasts also include recovery and liquidity effects, allowance for loan and lease losses (ALLL), and provisioning, to produce a best practice earnings simulation and stress tests. The business intelligence produced by this integrated model gives executives and business managers the accurate and reliable information they need to increase profit and returns on capital in an increasingly competitive market.

Accurately Model the Credit and Market Risk of the Entire Balance Sheet
QRM clients precisely model the foreign exchange, interest rate, and credit risk of all instruments in their consumer and commercial portfolios. Instrument models incorporate custom balance amortizations as well as transaction-specific prepayments, defaults, and recoveries. In addition, these models can be marked-to-market as of today or any future date using fully integrated interest rate term structure and credit risk pricing methodologies.

QRM clients employ several credit models, which are broadly grouped into two categories: single obligor and pooled asset models. Single obligor models, where default events are modeled explicitly, are used with larger, single name exposures where market-observable risk factors are used to extract information about default risk. Pooled asset models, where the pool default rate is directly modeled, are used where individual defaults are less significant and assets are modeled as pools based on common risk characteristics. Cross-model (both single obligor and pooled asset) correlations are accounted for through the default model's dependence on common risk factors.

Simulate Credit Migration for Enhanced Earnings-at-Risk Analysis
QRM clients analyze commercial and consumer portfolio migrations based on custom credit scoring methodologies. Working with our consultants, clients create migration matrices based on internal or external scoring information or historical deliquency analysis. These matrices are built using static transition probabilities, time-dependent transition probabilities, or economic, index-linked matrices that automatically adapt to each economic scenario.

QRM clients build sophisticated processes to forecast balance sheet dynamics, including portfolio runoff, growth, and reinvestment. Considering both existing and forecasted new volumes enables clients to create internally consistent projections. While traditional earnings-at-risk forecasts rely only on changes in interest rates to drive earnings, QRM clients use migration matrices to observe changes caused by migration from accruing states to non-accruing states. During the forecast, each transaction is tracked in one of four states: accruing, non-accruing, default, or recovery. Using these credit score or delinquency status migration matrices, clients link income accrual to the credit worthiness of the borrower to forecast portfolio credit quality distributions.

Moreover, clients model migration-dependent draws on unfunded commitments to capture the liquidity and exposure impacts from changes in the macroeconomic outlook. As a result, they integrate credit migration with transaction-level income and liquidity forecasting to create enterprise-wide, earnings-at-risk analyses.

Dynamic Simulation Capabilities for Provision and Allowance
As Allowance and Provision Expense calculations are fully integrated into the forecast, QRM clients are able to test management’s expectations of these measures under various economic scenarios, including stress test and “what if” analyses.   Throughtout the forecast,  defaults, Provision Expense, and the Allowance maintain consistent relationships. Credit and portfolio events drive the Allowance balance  allowing clients to adjust Provision Expense accordingly. This allows clients to  track all transactions individually and balance the balance sheet daily.

The First Major Step Towards True Enterprise Risk Management
Credit risk experts and asset-liabiltiy managers need no longer operate in different modeling spheres. The entire organization stands to gain immensely by leveraging the knowledge and expertise of the other. While this change could prove difficult, because of entrenched organizational structures and long-held traditions, technology and knowledge have finally rendered this type of risk structure outdated and obsolete. True Enterprise Risk Management is comprised of both credit and market risk, and these two groups need to work together to realize its goal.

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