By John Zugelder, Head of Solutions, North America

In my conversations with banking executives across North America, one theme consistently emerges: the fundamental shift from reactive to proactive risk management is becoming a regulatory necessity, not just a competitive advantage. After meeting with dozens of commercial lenders over the past year, I’ve witnessed firsthand how sophisticated early warning systems are revolutionizing how banks manage their portfolios, support their customers, and optimize their operations.

What Are Early Warning Systems in Commercial Lending?

Early warning systems (EWS) in commercial lending are sophisticated monitoring frameworks that continuously analyze borrower behavior and market conditions to identify potential credit deterioration before traditional financial metrics reveal distress. Unlike static annual reviews that provide snapshots in time, these systems create a dynamic view of portfolio health using a combination of financial indicators, transactional data, and behavioral signals.

These frameworks enable institutions to take predefined actions such as increased monitoring and strategic watch list placements well before problems escalate.

The Preventive Power: Turning Struggling Customers into Success Stories

Here’s what I find most compelling about early warning systems: they don’t just protect banks – they protect customers. When we identify subtle shifts in business performance early, we create opportunities for intervention that can help struggling borrowers turn their situations around.

Consider the difference between these two scenarios: In the traditional model, deterioration is spotted during an annual review when financial statements show declining performance. By then, the borrower may be months into a downward spiral, with limited options for recovery. Collection activity becomes the primary path forward.

With robust early warning systems, we detect these patterns months, even years, earlier, through declining transaction volumes, changes in deposit patterns, or shifts in payment behaviors. This early detection creates space for constructive dialogue.

Banks can offer restructuring options, additional resources, or strategic guidance when the borrower still has flexibility to adapt. The result? What could have been a charge-off becomes a success story.

The Strategic Advantages of Robust Early Warning Solutions

Through my work with banks implementing these systems, I’ve identified five critical strategic advantages that extend far beyond basic risk mitigation:

1. Operational Efficiency and Resource Optimization

Early warning systems dramatically reduce the need for resource-intensive annual reviews. When continuous monitoring provides real-time risk assessment, banks can shift from blanket annual reviews to risk-based monitoring. This means focusing closer attention where it’s needed most while reducing administrative burden on healthy accounts.

2. Enhanced Customer Relationships

Proactive outreach based on early signals transforms the bank-customer dynamic. Instead of reactive collection efforts, relationship managers can engage in strategic conversations about business challenges and solutions. This positions the bank as a partner rather than an adversary.

3. Regulatory Compliance and Examination Readiness

In today’s regulatory environment, examiners expect sophisticated risk management practices. As highlighted in recent OCC guidance, banks must demonstrate proactive credit risk management capabilities. Early warning systems provide the documentation and analytical framework that regulators increasingly require.

4. Portfolio Quality Protection

By identifying deterioration earlier, banks can take remedial action while borrowers still have options. This proactive approach reduces ultimate charge-offs and preserves portfolio quality metrics that are crucial for capital allocation and regulatory ratios.

5. Data-Driven Decision Making

Modern early warning systems integrate multiple data sources – financial statements, transaction data, market indicators, and behavioral patterns – creating a comprehensive view that enables more informed lending decisions and risk pricing.

The Power of Transaction Data

One of the most significant developments in early warning systems is the integration of transaction-level data. Traditional credit monitoring relied heavily on periodic financial statements, creating blind spots between reporting periods. Transaction data fills these gaps with real-time insights into business performance.

Payment patterns, deposit regularity, transaction volumes, and cash flow timing all provide early indicators of business health. A retailer’s declining daily deposits, a manufacturer’s irregular supplier payments, or a service company’s changing collection patterns can signal emerging challenges months before they appear in financial statements.

This granular view enables what I call “seeing around corners” – identifying trends and patterns that predict future performance rather than simply reporting past results.

The M&T Story: Seeing Around Corners with Transactional Signals

M&T Bank, one of the largest commercial lenders in the US, recognized this gap. Like many banks, they had a desire to improve their early intervention capabilities – not only to meet internal risk standards, but to better support customers before deterioration became visible through traditional metrics.

Working with RDC.AI, M&T leveraged our platform to ingest and analyze a broader set of behavioral signals, including transaction data. The goal was to detect subtle shifts in business performance and customer resilience that wouldn’t show up in static financials.

The results have been powerful: since implementation, M&T has seen a more than 70% improvement in early warning detection, enabling their risk and credit teams to act sooner, protect portfolio quality, and enhance customer outcomes.

The Regulatory Imperative

It’s important to note that sophisticated early warning capabilities aren’t just about competitive advantage – they’re increasingly about regulatory compliance. Financial regulators have made clear their expectations for proactive risk management. Recent guidance from the OCC emphasizes the need for banks to demonstrate comprehensive credit risk monitoring capabilities.

In my discussions with risk officers, the message is consistent: examiners are asking detailed questions about early warning systems, their effectiveness, and their integration into the bank’s overall risk management framework. Banks without robust capabilities find themselves at a disadvantage during examinations, so robust early warnings are both regulatory compliance and competitive advantage.

Looking Forward: The Evolution Continues

As we move through 2025, I expect to see continued evolution in early warning systems. Artificial intelligence and machine learning enable ever more sophisticated pattern recognition, and integration capabilities are expanding to include alternative data sources like industry-specific indicators and macroeconomic signals.

The banks that will thrive in the future are those that view early warning systems not as compliance tools, but as strategic enablers that strengthen customer relationships, optimize operations, and create competitive advantages in an increasingly complex lending environment.
The question isn’t whether your bank needs robust early warning capabilities – it’s whether you can afford to operate without them. In my experience, the banks making this investment today are positioning themselves not just for better risk management, but for stronger customer relationships and sustainable competitive advantage in the years ahead.

John Zugelder is Head of Solutions, North America at RDC.AI, where he works with financial institutions to implement advanced risk management and AI solutions. He has over 15 years of experience in commercial lending and risk management.