Our team contributes to industry research through published articles, workshops, and white papers on model risk management, fair lending, AI/ML bias, and quantitative methods.
A strategic briefing for community and regional banks on the revised interagency model risk management guidance, the $30 billion threshold, carve-in conditions, AI governance considerations, digital asset activity, and right-sized MRM expectations.
View →A strategic briefing for banking organizations over $30 billion in assets on the revised SR 26-2 framework, validation independence, model inventory re-scoping, AI governance, vendor risk, and recommended near-term actions.
View →Revised interagency supervisory guidance introduces a principles-based framework, narrows scope, and reshapes validation expectations across banking institutions.
Read article →How small and medium-sized firms can establish effective MRM processes without enterprise infrastructure.
Read article →Factors driving mortgage interest rate volatility and implications for prepayment modeling.
Read article →Practical guidance for institutions building MRM programs aligned with SR 11-7.
Read article →How ML models used in automated decision-making systems can harbor and perpetuate bias — and what to do about it.
Read article →Guidance on meeting Bank Secrecy Act and Anti-Money Laundering validation requirements.
Read article →Examining racial disparities in mortgage lending and their persistence over time, with E-value sensitivity analysis.
Read article →The 4 common and not-so-common types of anti-money laundering models, plus tips on AML model validation best practices.
Read article →What fair lending model validation is, what it does, and how it can benefit your institution's compliance program.
Read article →A recap of Kevin D. Oden's presentation at the 2020 RMA Annual Risk Management Conference.
Read article →What went wrong with Liquidity Stress Models in recently failed banks and how does it reflect on Stress Exercises going forward? The recent string of bank failures raises serious questions…
Read article →In an era of financial uncertainty, effective liquidity risk management is critical for institutions seeking long-term stability. Liquidity stress modelling helps banks, asset managers, and other financial entities assess their…
Read article →SR 11-7 and OCC 2011-12 have changed the landscape of model risk management broadly (and for the better) and in particular the practice of model validation. This guidance, which is…
Read article →By Kevin D. Oden and Maia Berkane. DOI: 10.47363/JMCA/2026(5)245
View publication (PDF) →By Kevin D. Oden and Maia Berkane. Published July 31, 2026. DOI: 10.17352/tcsit.000115
View publication (PDF) →Prepared by: Kevin D. Oden, PhD Founder & Principal, Kevin D. Oden & Associates LLC
View publication (PDF) →Kevin D. Oden
View workshop →Hands-on workshops covering fairness metrics, bias detection using Python, and correction methods for machine learning models.
View workshop →Hands-on workshops covering fairness metrics, bias detection using Python, and correction methods for machine learning models.
View workshop →Published in The RMA Journal. By Manish Kumar, Ph.D., Rahul Roy, Ph.D., and Kevin D. Oden, Ph.D. Covers pre-processing, in-processing, and post-processing techniques for ML fairness.
View publication (PDF) →We're always looking to advance the field. Reach out to discuss research partnerships, speaking engagements, or workshop opportunities.
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