Industry
Financial Services
Challenge
This Bank processes over 800,000 check deposits per month across Teller, ATM, and Mobile channels. While Check Detect scoring helped flag potentially risky items, analystswere spending a disproportionate amount of time manually reviewing flagged deposits — themajority of which turned out to be legitimate transactions.
Results
Following Check Detect deployment (Q1 2025), the Bank saw measurable improvements across analyst workload, review queue efficiency, and loss exposure.
Key Product
Check Detect
| Channel | Avg Items / Month | Avg Dollars / Month |
| Teller | ~664,000 | ~$1.7B |
| ATM | ~41,000 | ~$44M |
| Mobile | ~113,000 | ~$67M |
The Analyst Review Burden
With no item-level risk score, analysts relied on broad thresholds to decide which flagged deposits needed manual review. This created three compounding problems:
01 High Review Volume
13.4% of all Mobile deposits and 6.6% of ATM deposits required manual analyst review each month — far above what a small team could efficiently process.
02 Low Signal Quality
The majority of reviewed items turned out to be legitimate. Analysts were spending most of their time clearing good customers rather than catching fraud.
03 Staffing Pressure
An average of 1.6 FTE and 230+ analyst hours per month were dedicated solely to hold review — a significant operational cost with limited fraud yield.
The Results
Following Check Detect deployment (Q1 2025), the Bank saw measurable
improvements across analyst workload, review queue efficiency, and loss exposure.
Analyst Hours per Month: Baseline vs. Post-Deployment
| Period | Avg Analyst Hours / Month | vs. Baseline |
| 2024 Baseline (Jan–Dec) | 230 hrs | — |
| 2025 Post-Deployment (Jan–Dec) |
206 hrs | ↓ 11% |
| 2026 YTD (Jan–Apr) | 194 hrs | ↓ 16% |
Mobile Deposit Review Rate
The percentage of mobile deposits requiring analyst review dropped dramatically following deployment — from an average of 13.4% to 5.7%, a 58% reduction.
| Period | Avg Mobile Review Rate | vs. Baseline |
| 2024 Baseline | 13.4% | — |
| 2025 Post-Deploy | 5.7% | ↓ 57% |
| 2026 YTD (Jan–Apr) | 5.5% | ↓ 59% |
Key Outcome Metrics (2024 Baseline → 2025–2026)
| Metric | 2024 Baseline | 2025–2026 Result | Change |
| Analyst Hours / Month | 230 hrs | 206 hrs | ↓ 11% |
| Mobile Deposit Review Rate |
13.4% | 5.7% | ↓ 58% |
| ATM Deposit Review Rate | 6.6% | 5.4% | ↓ 19% |
| Loss Rate (% of deposits) | 0.0059% | 0.0029% | ↓ 51% |
| FTE Dedicated to Hold Review |
1.62 | 1.25 | ↓ 23% |
| Customers Impacted / Month |
271 | 257 | ↓ 5% |
The Path Forward
Check Detect turned Bank's reactive hold process into a precision scoring engine. By scoring every check deposit at the item level, the bank's analysts now spend their time on genuine risk — not clearing false alarms.
What Changed
1. From Broad Thresholds to Item-Level Scores: Instead of applying uniform hold rules, every check deposit now receives a real-time risk score, letting analysts focus on the deposits that actually matter.
2. From Reactive Review to Proactive Triage:The analyst queue shrank from 13.4% to 5.7% of mobile volume. Reviewers now process meaningful signals rather than clearing false alarms.
3. From Staffing Pressure to Operational Efficiency: Dedicated hold-review FTE dropped from an average of 1.6 to 1.25, and monthly analyst hours fell from 230 to 206, freeing capacity for higher-value work.
Results at a Glance
| Metric | 2024 Baseline | 2025–2026 Result | Change |
| Analyst Hours / Month | 230 hrs | 206 hrs | ↓ 11% |
| Mobile Deposit Review Rate |
13.4% | 5.7% | ↓ 58% |
| ATM Deposit Review Rate | 6.6% | 5.4% | ↓ 19% |
| Loss Rate | 0.0059% | 0.0029% | ↓ 51% |
Reduce Your Analyst Review Burden With Check Detect
Valid Systems deploys Check Detect for financial institutions across Teller, ATM, and Mobile channels. Our check risk models are trained on your transaction data and validated against your fraud patterns delivering precision scoring without disrupting your operations.
