RegVizion LLC
Back to Case Studies
Credit Policy & Risk Management

Community Bank – FDIC Loan Review Process Remediation

Community Banking
Credit Policy & Risk Management

Results at a Glance

FDIC finding fully resolved and closed
Regulatory confidence restored
Improved loan quality through proactive identification
Standardized processes improving efficiency
Enhanced governance increasing board confidence
No repeat findings in subsequent examinations

Challenge

During a routine safety and soundness exam, a state-chartered bank received an FDIC finding citing deficiencies in its credit policy governing the loan review process. Specifically, the examiners noted the absence of a statistically valid sampling methodology and the lack of a documented, repeatable process for scoping, executing, and reporting loan reviews. The bank faced a supervisory recommendation and tight remediation timeline.

Key Issues:

  • Sampling Methodology: Loan review sample sizes were arbitrarily selected, lacking statistical justification
  • Process Documentation: No written methodology for risk-based selection, frequency, or portfolio rotation
  • Reporting Deficiencies: Findings were inconsistently reported, with limited traceability or executive oversight
  • Policy Gaps: No linkage between loan review results and credit policy adjustments or training
  • Governance Concerns: Examiners questioned the governance and credibility of the bank's credit review framework

Solution

RegVizion engaged with the bank's credit administration and risk teams to overhaul the loan review policy and program.

1. Statistically Sound Sampling Methodology

Developed a risk-based sampling approach tailored to portfolio composition with:

  • Statistical justification for sample sizes
  • Documentation of sampling rationale
  • Portfolio rotation schedule ensuring comprehensive coverage
  • Stratified sampling by risk rating and loan size
  • Probability-based selection methodology
  • Minimum coverage thresholds by portfolio segment
  • Annual coverage targets aligned with regulatory expectations

2. Formal Loan Review Framework

Created a comprehensive loan review policy and procedures manual including:

  • Standardized review templates and checklists
  • Risk rating validation methodology
  • Consistency standards across reviewers and review cycles
  • Scoping procedures for annual review plan
  • Execution standards for individual loan analysis
  • Issue classification and tracking protocols
  • Escalation procedures for identified problems

3. Standardized Reporting Process

Implemented a standardized reporting structure with enhanced governance:

  • Board-level reporting templates
  • Executive summary dashboards
  • Detailed findings log with tracking
  • Trend analysis and peer benchmarking
  • Quarterly reporting to board and management
  • Action item tracking with accountability
  • Historical trend analysis
  • Portfolio risk heat maps

4. Training & Change Management

Delivered comprehensive training programs focused on consistency and quality:

  • Comprehensive training to credit reviewers
  • Management training on framework and governance
  • Documentation best practices
  • Quality assurance procedures
  • Consistency in loan analysis
  • Proper documentation standards
  • Risk rating accuracy
  • Defensibility and transparency

5. Governance Controls & Feedback Loops

Embedded quality controls and feedback mechanisms throughout the organization:

  • Quality control reviews of loan review work
  • Linkage between findings and underwriting guidelines
  • Training programs based on identified trends
  • Portfolio strategy adjustments informed by review results
  • Independent loan review function
  • Direct reporting to board/audit committee
  • Annual policy review and updates
  • Performance metrics and KPIs

Results & Impact

Regulatory Compliance

FDIC finding fully resolved - Supervisory recommendation closed Regulatory confidence restored - Framework accepted by examiners No repeat findings - Passed subsequent examinations

Enhanced Credit Oversight

Improved loan quality through proactive identification of weaknesses Early problem detection enabling timely intervention Better risk rating accuracy across portfolio

Operational Improvements

Standardized processes improving efficiency and consistency Clear accountability for remediation actions Measurable results through KPI tracking

Strategic Benefits

Elevated credit oversight standards across the organization Integrated feedback loops improving underwriting and training Enhanced governance increasing board confidence Holistic remediation addressing root causes, not just symptoms

Key Takeaways

  1. Statistical Rigor is Required: Regulatory expectations demand statistically valid sampling, not arbitrary selection

  2. Documentation is Critical: Written policies and procedures provide defensibility and consistency

  3. Governance Links Matter: Loan review findings must inform policy, training, and strategy

  4. Proactive is Better Than Reactive: Addressing loan review deficiencies before examination prevents findings

  5. Quality Over Quantity: A well-designed, focused review program is more valuable than extensive but poorly structured reviews

  6. Comprehensive Remediation Works: Addressing the entire framework—not just the specific finding—creates lasting improvement

Facing regulatory findings or looking to strengthen your loan review process? Schedule a consultation to discuss how RegVizion can help you build a defensible, efficient framework.

Related Services:

Related Case Studies

AI Model Validation

Regional Mortgage Lender – AI Model Bias Audit & Fair Lending

A regional lender's proprietary AI credit scoring model faced FDIC scrutiny for potential fair lending violations and a lack of explainability, risking regulatory penalties and reputational damage.

CECL Model Validation

Mid-Size Bank – First-Time CECL Model Validation

A $3B bank built an in-house CECL model using cohort and DCF methods but lacked CECL expertise, risking inaccurate loss estimates and regulatory scrutiny due to insufficient validation.

Model Risk Management

Regional Mortgage Lender – AI Credit Scoring Model Validation

A regional lender's proprietary AI credit scoring model faced FDIC scrutiny due to lack of comprehensive validation documentation and concerns about model bias.

Ready for Similar Results?

Let's discuss how RegVizion can help your institution achieve regulatory compliance and business success.

Schedule ConsultationView All Services

Or reach out directly:

+1 555-123-4567info@regvizion.com