Total Portfolio
$4.24B
Outstanding loan balance across all segments and risk grades
▲ +2.1% QoQ
Power BI · Banking & Credit Risk
Loan Portfolio Risk Dashboard
Real-time NPL ratio, CECL reserve coverage, delinquency aging, and risk grade migration — from your core banking system to Power BI in under 48 hours.
Built for Chief Credit Officers, risk managers, and bank CFOs who need accurate, trusted visibility into portfolio credit quality, delinquency trends, and regulatory compliance posture.
Powered by Power BI, connected to Fiserv, FIS, Jack Henry, nCino, and your CECL model.
Trusted by teams across 15+ countries
100+
Clients Served
300+
Dashboards Delivered
50,000+
Hours Saved
5.0★
Rating · 15 Reviews
Trusted by teams at
Audience
Who This Dashboard Is For
Ideal For
- Chief Credit Officers and credit risk management teams at community and regional banks ($500M–$25B in assets)
- Bank CFOs who own the ALLL/CECL reserve adequacy reporting and DFAST submission
- Loan review teams tracking risk grade migration across CRE, C&I, and consumer portfolios
- Internal audit and regulatory affairs teams preparing for FDIC, OCC, or Texas Department of Banking examinations
- Board-level risk committees that need a clear view of portfolio credit quality without a 50-page loan review packet
Not Ideal For
- Non-bank lenders or marketplace lenders using proprietary loan origination systems without a standard core banking extract
- Banks that already have a mature enterprise risk management platform (Moody's, S&P RiskCalc) with built-in reporting
- Very small community banks under $200M in assets where the loan portfolio can be reviewed in a single spreadsheet
By the numbers
Credit Risk KPIs That Drive Portfolio Decisions
Five indicators every Chief Credit Officer and bank CFO monitors daily — tracking portfolio quality, reserve adequacy, and delinquency exposure in real time.
NPL Ratio
1.24%
Non-performing loans as % of total portfolio — FDIC Call Report basis
▲ -0.18 pts YTD
CECL Reserve Coverage
1.58%
Allowance for credit losses as % of outstanding loan balance
▲ 1.27x NPL coverage
Watch List
10.8%
Risk grades 4-5 (Watch and Special Mention) as % of total portfolio
▲ -1.6 pts YTD
30-Day Delinquency
2.14%
Portfolio share with payments 30+ days past due — indicator of stress
▲ -0.24 pts YTD
The problem we solved
From Monthly Loan Review Reports to a Real-Time Credit Risk Command Center
Banking credit teams waste days each month manually compiling NPL ratios, delinquency aging reports, and risk grade migration summaries from core banking extracts — often presenting stale data at ALLL/CECL committee meetings.
The challenge
A Texas regional bank with a $4.2B loan portfolio was generating its monthly credit quality report by exporting data from FIS core banking, running it through a 47-tab Excel model, and presenting results two weeks after quarter-end. The Chief Credit Officer and CFO were routinely presenting different NPL ratios because each used a different calculation date. Risk grade migration was tracked in a separate SharePoint document, updated manually by the loan review team.
- NPL ratio calculation depended on which date the export was pulled — CCO and CFO consistently had different numbers
- Delinquency aging buckets were recalculated monthly — too slow to catch deterioration between formal loan reviews
- CECL reserve coverage ratio required a manual calculation after each model run, not integrated with live portfolio data
- Risk grade migration (Pass → Watch → Substandard) was visible only after the quarterly loan review, not as it happened
Our approach
We built a Power BI semantic model on top of a daily extract from FIS core banking, integrated with the bank's CECL model output and loan review system. NPL ratio, delinquency aging, and reserve coverage ratio are all calculated using agreed-upon definitions encoded in DAX — so the same number appears in the board package, the ALLL committee deck, and the DFAST submission.
- Defined canonical NPL, DPD, and reserve coverage formulas with the CCO and CFO before any measures were written
- Built FIS → Azure Data Lake daily pipeline with end-of-business refresh cadence
- CECL model output (expected credit loss by segment) integrated as a separate fact table, reconciled against the core banking balance
- Interactive slicers for Quarter, Loan Type (CRE / C&I / Residential Mortgage / Consumer), and Risk Grade (Pass / Watch / Substandard / Doubtful)
What we achieved
Monthly credit quality reporting cycle reduced from 14 days to next-day
CCO and CFO now share one NPL ratio — no pre-meeting reconciliation
Delinquency monitoring shifted from monthly review to daily — two CRE credits identified as deteriorating 6 weeks before formal loan review
CECL reserve coverage ratio visible in real-time, enabling faster reserve adjustment decisions
DFAST data submission preparation time cut from 3 days to 4 hours
Results verifiedRead full case study
FAQ
Common Questions
Questions we hear from credit risk leaders and bank CFOs before starting a loan portfolio analytics engagement.
We connect to FIS (Horizon, IBS, and Systematics), Fiserv (Precision, DNA, Portico), Jack Henry (Silverlake, CIF20/20), and nCino for loan origination data. For community banks on legacy platforms, we use the system's native ODBC export or scheduled file drop to a secure staging database. The exact connector is confirmed during scoping — if your core banking system generates a standard loan tape (loan ID, balance, risk grade, DPD, collateral type), we can build from it.
From Lets Viz
Ready to Consolidate Your Portfolio Risk Data?
Most regional banks are 7–10 business days away from a real-time loan portfolio risk command center. Book a free scoping call and we'll confirm your core banking system, CECL model, and reporting requirements.
NDA-safe · No obligation · FDIC/OCC exam-ready documentation