Asset Quality, Earnings, and Capital, Oh My!
How will the recession impact your institution? Particularly in these volatile economic times, stress testing can help drive an answer.
Robust credit risk stress testing models allow management to make informed decisions based on risk-related possibilities. DCG's deep model development experience and wide horizontal validation perspective position our experts as optimal resources to get your assessment of this most significant banking risk right. This includes how potential future states, from baseline economic projections to multiple adverse economic scenarios, can impact your institution.
Using a combination of standard statistical analysis and innovative testing techniques, DCG validates data inputs, modeling assumptions, statistical methods, and economic scenarios. This provides you the confidence that stress testing models are capturing the impact of macroeconomic variables on customer credit.
Credit stress testing models fit into multiple bank functions, including the allowance process, capital analysis, liquidity management, and strategic planning. It is important to make sure that the results from the stress testing models integrate with other bank functions -- not only in the current economic environment, but also over different potential scenarios.
Credit stress testing models come in a variety of shapes and sizes, including expected loss methods, migration models, regression models, and simulation models. The DCG team uniquely scopes and resources each validation to ensure that the skills and techniques of validators fully align with each model’s quantitative sophistication, as well as any MRM- or regulator-specified validation and testing requirements.
DCG's credit specialists possess expansive knowledge around stress testing, having built and validated complex credit stress testing models at the largest U.S. financial institutions. DCG has validated more than 200 credit stress testing models at institutions with assets from $5 to $100 billion, exposing our validation team to a wide array of model methodologies.
Helped improve institution’s risk position modeling through identification of missing contractual characteristics in loan file by performing data validation.
Identified deficiencies in assumptions development and support process for deposit behavior characteristics. Helped institution better understand alternatives to defend deposit assumptions and deposit stability. Strengthened model assumptions and re-focused management on strategic deposit initiatives.
Re-validated risk models for $2B bank after exam found third-party vendor's validation “did not provide sufficient rigor.” DCG's re-validation with effective challenge uncovered myriad input and model deficiencies that, once addressed, changed bank’s risk profile and strategic direction.