Self Attempt 03

Credit Office Committee JSON SOP

Use this skill for credit-office tasks that ask for a committee-ready JSON answer about a bank branch, loan portfolio, pending applications, CRE comparison, watch-list stress, or credit-union segment posture.

Source Discipline

• Use the remote public API only: <environment_base_url>.
• Do not start, inspect, or read any local environment service, database, generated data file, run output, train output, test file, notes, reports, judge endpoint, or prior skill attempt.
• Read the task prompt and its input/payloads/answer_template.json first. The template is the output contract for top-level keys, enum spellings, precision, required empty arrays/maps, and ordering.
• Fetch only public API data needed for the target branch or segment plus /api/manifest, /api/policies, and the named benchmark endpoint.
• Return exactly one valid JSON object. Do not include prose outside JSON.

API Checklist

Start with:

• /api/manifest for policy_version and benchmark versions.
• /api/policies for rating thresholds, CDFI scoring, CRE weights, stress formulas, capacity rules, and material downgrade threshold.

For branch tasks, fetch as needed:

• /api/branches/{branch_id}: capacity, sector_ceiling_pct, cre_policy_limit_pct, total assets, state, benchmark set.
• /api/branches/{branch_id}/metrics: quarter metrics. For a 2025-03-31 review, use 2025Q1.
• /api/branches/{branch_id}/loans: balances, ratings, payment status, DSCR, LTV, FICO, debt-to-asset, liquidity, loan type, sector.
• /api/branches/{branch_id}/sector-exposures: current sector exposure, limit_pct, grandfathering.
• /api/branches/{branch_id}/applications: pending underwriting factors and requested amounts.

For benchmark/segment tasks:

• /api/benchmarks/fdic/q4-2024: FDIC ratios such as total_loans_noncurrent_pct, total_real_estate_30_89_pct, and total_real_estate_noncurrent_pct.
• /api/benchmarks/ncua/q1-2025: state rows with integer delinquency_bps, loan_to_share_pct, roaa_bps, and positive_net_income_pct.
• /api/credit-union-segments/{segment_id}: state, peer states, checklist gates, internal context, capacity, current outstanding, and risk tolerance.

Common Field Conventions

• Use outstanding_balance for loan exposure and requested_amount for application gross amount.
• metrics.total_loans_outstanding equals the sum of branch loan balances and is the denominator for branch portfolio, NPA, CRE, and sector concentration ratios unless the prompt says otherwise.
• For post-approval concentration, use a post-approval denominator: current total_loans_outstanding plus retained approved exposure.
• Sector limits come from sector-exposures.limit_pct; fall back to branch sector_ceiling_pct only when the sector has no override row.
• CRE exposure is the sum of outstanding_balance for loans with loan_type == "CRE". CRE concentration is CRE exposure divided by total loans.
• Keep ratios as decimals, not whole percentages. Basis points are ratio * 10000.
• Round only at the output boundary: currency to 2 decimals, ratios to 4 decimals, bps to 2 decimals, DSCR to 2 decimals, CRE weighted scores to 1 decimal, unless the template says otherwise.

Risk Rating Regrade

For a regrade population such as current_rating >= 3, filter by the requested current-rating minimum. Re-derive the final rating from objective policy factors, not from the prior rating.

Policy thresholds:

• DSCR: >=1.50 -> 3, >=1.25 -> 4, >=1.05 -> 5, >=1.00 -> 6, <1.00 -> 7.
• LTV: <=0.65 -> 3, <=0.75 -> 4, <=0.85 -> 5, <=1.00 -> 6, >1.00 -> 7. If LTV is missing but balance and collateral value exist, compute balance divided by collateral value.
• Delinquency minimums: 30 Days Past Due -> 4, 60 Days Past Due -> 5, 90+ Days Past Due -> 7, Nonaccrual -> 8, Current -> no minimum.
• Final rating is the worst numeric rating from available DSCR, LTV/collateral, and delinquency factors.
• A material downgrade is final_rating - current_rating >= policies.risk_rating.material_downgrade_notches.

For NPA benchmarks:

• branch_npa_exposure = metrics.nonperforming_loans.
• branch_total_loans = metrics.total_loans_outstanding.
• branch_npa_ratio = branch_npa_exposure / branch_total_loans.
• variance_ratio = branch_ratio - benchmark_ratio; variance_bps = variance_ratio * 10000. Preserve the sign unless the template asks for absolute variance.

For problem-credit selection, rank first by most severe final rating, then by nonaccrual/90+ status, then by largest exposure. Use only the action enums allowed by the template; a practical severity ladder is monitor, watchlist, special_assets, workout, partial_chargeoff_review, legal_referral.

CDFI Factor Scores And Watch-List Stress

For adverse-rated or watch-list loans, compute factor_score from policies.cdfi_factor_scores using available objective factors:

• FICO bins, LTV bins, debt-to-asset bins, and liquidity-month bins add together.
• Exact boundary values belong to the explicit middle range where listed, such as 0.40-0.60 or 680-720.
• Class by total score: 0-5 Prime, 6-9 Desirable, 10-13 Satisfactory, 14-18 Watch, >=19 Doubtful.
• Override to Projected Loss when score is >=19 and LTV is >1.0.

For watch-list DSCR stress:

• Use the policy formula exactly: stressed_dscr = dscr / (1 + 0.18), even when the label says +200bp.
• Use only loans with DSCR available in stress result rows.
• breaches_threshold is true when stressed DSCR is below policies.stress.coverage_breach_threshold unless the prompt defines a stricter comparison.
• Sort stress rows and breach ID lists exactly as the template requires.

Application Allocation And Concentration

For pending application packages:

• Capacity starts from branches.lending_capacity_q1.
• gross_approved_amount is the sum of approved or conditionally approved gross requested amounts.
• bank_capacity_used and committed_capacity_amount should reflect retained bank exposure after any SBA guaranty, participation, or reduced-amount condition. If no mitigation applies, retained exposure equals approved amount.
• remaining_capacity = lending_capacity_q1 - committed_capacity_amount.
• Rank only approved and conditionally approved applications in priority_ranking.

For concentration flags:

• Existing sector exposure is sector-exposures.current_exposure.
• exposure_after_approval = current_exposure + retained approved exposure for that sector.
• post_approval_pct = exposure_after_approval / (current total loans + total retained approved exposure).
• over_limit or flags should compare post-approval percentage to the sector-specific limit_pct.
• Grandfathered existing over-limit exposure may be tolerated, but a new approval should not worsen it without a template-allowed mitigation such as participation, reduced amount, board exception, or decline.

Reason codes should come only from the template. Typical mappings are: weak DSCR to weak_dscr, high LTV to high_ltv, low FICO to low_fico, recent bankruptcy to recent_bankruptcy, incomplete documentation to documentation_gap, capacity shortfall to capacity_limit, sector over-limit to sector_breach, adverse FDIC comparison to fdic_adverse_variance, and weak NCUA comparison to ncua_peer_weakness.

CRE Competition

For competing CRE applications:

• Fetch branch details, metrics, loans, sector exposures, the target applications, policies, and FDIC benchmark data.
• Use policies.cre_weighted_score.weights: capacity 0.45, capital 0.03, character 0.05, collateral exposure 0.36, conditions 0.11.
• Lower weighted score is better. Classify with policy thresholds: <=2.0 approve_quality, <=3.0 conditional, >3.0 weak.
• Derive components from raw factors: DSCR for capacity, LTV for collateral exposure, total debt divided by total assets for capital when present, FICO/bankruptcy/prior delinquencies/relationship/guarantor for character, and documentation, sector concentration, CRE policy pressure, and FDIC variance for conditions.
• CRE dual stress uses stressed_dscr = dscr * 0.85 / (1 + 0.18).
• Selected post-approval CRE concentration is (existing CRE exposure + selected retained exposure) / (current total loans + selected retained exposure).
• Policy variance bps is (post_approval_cre_concentration - cre_policy_limit_pct) * 10000.
• Sort application comparisons by application_id; sort reason code and condition lists alphabetically when required.

Credit-Union Segment Posture

For segment posture pages:

• Use the segment endpoint for state_code, peer_states, minimum_checklist, internal_context, quarterly_capacity, current_outstanding, notes, and risk tolerance.
• Use the NCUA benchmark row for the segment state, the US row, and all named peer-state rows.
• For peer_comparison, compare the state value to the US value and to the median of the peer-state values. Return only higher, lower, or equal.
• State metrics in the template are integer values exactly as reported by NCUA, not ratios.
• Required checklist gates usually come directly from minimum_checklist; add operating controls from current context, such as missing insurance or lien follow-up, state benchmark monitoring, second review, or capacity exceptions.
• Choose escalation triggers and owners only from the template enums, aligning owner responsibility with the trigger type.

Output Validation

Before finalizing:

• Confirm every required top-level key is present and no uncontrolled enum value appears.
• Confirm all specified sort orders: IDs ascending, final ratings ascending, actions alphabetically, workout queues by descending exposure then ID, or template-specific order.
• Confirm numeric values are numbers, booleans are booleans, and absent result groups are represented as empty arrays or objects if required.
• Do not include candidate train answers, hidden reasoning, citations, markdown fences, or explanatory text outside the JSON response.