Going Beyond the "Tick & Tie"
It's time for your next model validation, but who should perform it - and how? Regulators make it clear that model validation is...
Enhanced decision-making begins with model confidence. With DCG, you can partner with model validation experts who asses the quality of your models, provide in-depth analysis of data, and deliver strategic insights to optimize performance.
For a full list of DCG's Model Validation coverage, click here.
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.
Confident decision making at ALCO begins with knowing unequivocally that your Asset/Liability Management (ALM) model is performing as intended and that your interest rate risk (IRR) assessment is accurate. ALM models are becoming increasingly more complex, being used for and more reliant on expanded data elements and dynamic assumption inputs, often driven by feeder models. DCG has the market insight, experience, and expertise to properly assess your model's vulnerabilities and deliver meaningful enhancements for all of your ALM model uses.
Getting credit risk scorecards right means better lending decisions, better portfolio management, and ultimately, better risk management. DCG's expertise in statistical and machine learning methods and extensive experience validating risk rating scorecards can drive meaningful improvements in credit risk scorecard models.
Liquidity stress models are a critical component of asset liability management. Including appropriate scenarios with varying degrees of likelihood and severity and providing documentation in a customized contingency funding plan leads to better liquidity management, regardless of the levels of liquidity you have today.
When fraud models don't work as intended, significant fines and reputation risk can result. Criminals are becoming more sophisticated, so you must make sure that your fraud models are up to the task with a rigorous validation to strengthen your program.
Robust credit models allow management to consider how potential future states, from baseline economic projections to multiple adverse economic scenarios, can impact their institution. With this information, management can make informed decisions based on risk-related possibilities. Our team's deep model development experience – and wide horizontal validation perspective – positions our experts as optimal resources to you get your assessment of this most significant banking risk right.
Robust credit models allow management to make informed decisions based on risk-related possibilities. Our team's deep model development experience and wide horizontal validation perspective positions our experts as optimal resources to you 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.
Given the vital role Funds Transfer Pricing (FTP) and profitability models have on your capital/strategic planning, product pricing, and performance incentives, ensuring these models' continued accuracy, reliability, and ability to provide management with actionable intelligence is paramount to financial success and gaining competitive advantage.