Intelligent Fraud Operations: Regions Bank Cuts Operational Losses by 57% in Two Years

Overview

Deposit fraud losses at US regional banks are primarily detection and investigation problems. Most banks have the data; what they lack is the process architecture to turn that data into precise, fast, low-friction decisions. This case study documents how a leading American full-service bank addressed that gap. In a two-year engagement, Altimetrik supported the bank’s redesign of fraud operations policy and procedure, alert category enhancement, resulting in a 57% reduction in operational losses, a 43% reduction in false positives, and a 50% reduction in customers experiencing unnecessary deposit holds.

The Client

A leading US-based, full-service provider of consumer and commercial banking, wealth management, and mortgage products and services. The bank serves customers throughout the South and Midwest, including Texas.

Business Challenge

When Altimetrik began working with the bank, its deposit fraud operation had a structural challenge. Every suspicious transaction, regardless of risk level, check type, or dollar value, entered the same manual investigation queue. There was no prioritization based on risk category, and no direct hold for clear-cut cases.

The consequence was predictable. Investigators spent most of their time on alerts that led nowhere:

• The bank faced a coordinated fraud ring attack that drove losses to USD30 million per quarter in 2023.
• A Reg CC audit observation flagged the bank’s deposit hold practice for lacking sufficient justification in customer notices.
• 30% of deposit transactions were placed on hold; 99% of those holds were later confirmed unnecessary.

Our Approach

The engagement began with a structured diagnostic mapping of how fraud manifested across deposit types, where investigator decisions were made, and which process steps needed automation. After the diagnostics, we adopted a three-pronged approach and implemented the following:

Intelligent Process Design

• Implemented risk-weighted investigation procedures by check type, deposit mode, and dollar value, replacing a single undifferentiated queue or alert risk type.
• Built a hold prioritization matrix to cautiously make decisions based on alert category and straight-through hold for demonstrably high-risk items.
• Established a Green Profile Framework, where a senior analyst performed due diligence on the high-risk alert with SLA accountability tied to a balance between fraud loss and better customer experience, not alert throughput.

Data & Analytics

• Ran weekly structured workshops with Regions’ SMEs to translate live fraud patterns into rule-engine updates.
• Created a closed-loop feedback mechanism that feeds investigation outcomes back into detection rules so the system improves with every resolution.
• Deployed QA performance dashboards to enable real-time visibility into process health and investigator performance.

Targeted Automation

• Implemented Robotic Process Automation (RPA) for three time-consuming manual steps: Account block, automated hold, and automated Reg CC letter generation. 
• Proposed an AI solution for investigation steps: Check image comparison, Account activity history profiling, and decision recommendation.

The Impact

Operational Efficiency

• Reduced operational losses by 57% over two years.
• Reduced average handling time (AHT) per investigation by 28%.
• Achieved a 20% reduction in AHT through procedure redesign alone.
• Improved manpower productivity by 25% without reducing headcount.
• Maintained zero operational-loss SLA penalties since January 2023.
• Offshore team’s proactive intervention arrested USD 350 million in attempted fraud in 2025

Quality & Compliance

• Reduced false positives by 43%.
• Sustained an enterprise QC score above 99%.
• Maintained first-line-of-defense control testing below the 1% risk tolerance.
• Successfully closed Reg CC audit with zero observations in the year 2025.
• Annual fraud losses were slashed from $130 million to $60 million by 2025.

Customer Experience

• Reduced the transaction-to-alert rate by 50% (from 3% to 1.5%).
• Improved the hold-to-fraud rate by 30% (from under 1% at the start of the engagement).
• Helped the customer ascend to a top 5 position among its peer banks for fraud mitigation performance.

Three places to start.

• Measure your alert-to-fraud conversion rate. If you do not have this number readily available, that gap is the first thing to close. It is the single metric that most clearly reveals whether your detection model is calibrated or just generating volume.
• Audit how investigator time is spent. Separate time on confirmed fraud from time on alerts that clear. If the ratio is inverted, the process design and not the team is the constraint.
• Map your rule engine feedback loop. Determine how investigation outcomes currently flow back into detection rules, and on what cadence. If the answer is “manually, occasionally,” that is the highest-leverage process gap to address.

FAQs

What’s driving the surge in deposit and check fraud at regional banks right now?

Check fraud in the US is growing at 28% annually (Nasdaq 2026 Global Financial Crime Report), and most fraud operations were built for a different threat environment. Regional banks are particularly exposed because they often rely on undifferentiated investigation queues — every suspicious transaction, regardless of risk level or dollar value, gets treated the same way. That structural problem means investigators spend most of their time on alerts that lead nowhere, while genuinely high-risk activity moves at the same pace as low-risk noise.

How do I know whether our fraud detection model is calibrated or just generating volume?

The clearest diagnostic is your alert-to-fraud conversion rate — the share of alerts that ultimately confirm fraud. If you don’t have that number readily available, that gap itself is worth addressing first. A second useful signal: audit how investigator time is actually spent. If more time goes to alerts that clear than to confirmed fraud, the constraint is process design, not the team.

How do banks balance tighter fraud controls with not penalizing good customers?

This is the core tension in fraud operations, and it’s mostly resolved through segmentation. Not every alert warrants the same response. A hold prioritization matrix that differentiates by check type, deposit mode, and dollar value lets you apply straight-through holds only where the risk clearly justifies it, and route lower-confidence cases to senior review. The goal is to calibrate the hold-to-fraud ratio, reducing unnecessary holds without loosening controls on genuinely high-risk transactions.

What’s Altimetrik’s footprint in financial services, and what does the team cover?

Altimetrik works with five of the top ten US regional banks, seven Tier-1 global banking institutions, and five global payment leaders. It has over 20 years of experience in financial crime operations. Coverage spans the full stack: deposit, check, and bank card fraud investigation; dispute, claims, and reconciliation; case management and SAR pre-file; KYC (CDD and EDD); transaction monitoring and currency reporting; and AML investigation. The team also has hands-on delivery experience across the major platforms, such as Actimize, Verafin, Palantir, Detica, FCMS, LexisNexis, and IDology.

Who leads the fraud operations at Altimetrik?

Altimetrik’s financial crime operations practice is led by practitioners with deep banking backgrounds. Somesh Auddy (VP, Digital Operations) brings 25+ years of global delivery experience. Vanishri Balnad and Girisha Aithala, both GMs in Digital Operations, each have 20+ years in banking delivery and operations transformation, respectively. The people running the engagement have seen these problems across multiple institutions and regulatory environments.