Solving Correspondent Banking compliance: Consilient’s new model

Correspondent banking is essential for global trade and cross-border payments, but it comes with significant risks that traditional systems struggle to manage. Banks are expected to monitor high-risk transactions, ensure compliance with evolving regulations, and detect sophisticated financial crimes—all while operating with limited visibility into their correspondent banks’ underlying customers.

The result? Persistent gaps in risk detection, rising compliance costs, and mounting regulatory pressure.

The reality is that most transaction monitoring and due diligence systems weren’t built for today’s challenges. They rely on static rules and isolated datasets, generating excessive false positives while missing real threats. Compliance teams are overwhelmed, manually sifting through low-risk alerts instead of tackling genuine financial crime.

Banks know they need a smarter, more efficient approach—one that enhances risk detection without creating more operational burdens. That’s where Consilient’s new Correspondent Banking Model comes in.

The hidden costs and challenges of Correspondent Banking

Correspondent banking relationships present unique challenges that expose banks to financial, regulatory, and reputational risks. Here’s a closer look at the key pain points:

1. Limited visibility into underlying customers

Banks often act as intermediaries, facilitating transactions for other financial institutions without direct access to the end customers’ identities or behaviors. This creates a “blind spot” in risk management, making it difficult to:

🟣Assess the true risk profile of transactions.

🟣Detect suspicious activities, such as money laundering or terrorist financing.

🟣Comply with KYC and AML regulations.

Without this visibility, banks are forced to rely on incomplete or outdated information, increasing the likelihood of undetected financial crime.

2. Overwhelming false positives

Legacy systems generate a high volume of false positives, overwhelming compliance teams with low-risk alerts. This leads to:

🟣Wasted resources: Teams spend hours investigating false alarms instead of focusing on genuine threats.

🟣Operational inefficiencies: Clogged workflows slow down the entire risk management process.

🟣Missed risks: High-risk activities slip through the cracks while teams chase irrelevant alerts.

3. Evolving regulatory expectations

Regulators are demanding stronger controls and greater transparency in correspondent banking. Banks must:

🟣Monitor and report suspicious activities in real-time.

🟣Conduct enhanced due diligence (EDD) on high-risk relationships.

🟣Maintain comprehensive audit trails to demonstrate compliance.

However, outdated systems and processes make it difficult to keep pace, exposing banks to fines, reputational damage, and lost relationships.

4. Sophisticated financial crime tactics

Criminals exploit gaps in correspondent banking networks using tactics like:

🟣Layering: Breaking down large transactions into smaller, less conspicuous amounts.

🟣Identification nesting: Using intermediaries to obscure the origin of funds.

🟣Jurisdiction hopping: Routing transactions through high-risk or poorly regulated jurisdictions.

Traditional systems, which rely on static rules, are ill-equipped to detect these complex schemes.

5. Rising compliance costs

Manual processes, inefficient systems, and regulatory pressure have driven compliance costs to unsustainable levels. Banks must:

🟣Hire large teams to handle the volume of alerts.

🟣Invest in costly technology upgrades.

🟣Allocate significant resources to manual due diligence and audits.

These rising costs are particularly burdensome for smaller banks.

6. Reputational risks

A single compliance failure can damage a bank’s reputation, leading to:

🟣Loss of customer trust.

🟣Damage to brand value.

🟣Termination of correspondent relationships by other institutions.

In an industry where trust is paramount, reputational risks can be just as damaging as financial penalties.

The harsh reality is that most transaction monitoring and due diligence systems were not designed to handle today’s complex challenges. These legacy systems rely on static rules and isolated datasets, generating an overwhelming number of false positives while still failing to catch genuine threats. Compliance teams, already stretched thin, are bogged down by manual reviews of low-risk alerts, leaving little time or resources to address real financial crime.

Banks recognize the urgent need for a smarter, more efficient approach—one that enhances risk detection without adding to their operational burdens. Enter Consilient’s new Correspondent Banking Model, a revolutionary solution that is transforming how banks manage correspondent banking risks.

Here’s how it works…

A smarter solution: The federated learning model for Correspondent Banking 

Traditional compliance models are reactive, responding to threats only after they occur. Consilient’s model, on the other hand, is proactive—it anticipates risks before they materialize.

Developed in collaboration with leading global banks, Consilient’s Correspondent Banking Model leverages federated machine learning to transform how institutions detect, assess, and manage risk—without disrupting existing systems.

Sharper risk detection—without the noise

Forget rules-based scoring systems that overwhelm compliance teams with irrelevant alerts. Consilient’s model analyzes real transaction behaviors, flagging risks traditional systems miss.

🔹 Identification nesting: Detecting attempts to obscure transaction origins.
🔹 High-risk jurisdiction transactions: Pinpointing payments that require closer scrutiny.

By providing deeper insights into who is really behind transactions, banks can move beyond surface-level risk scoring and focus on genuine threats.

Collaboration without data sharing

Financial criminals don’t operate in isolation. Yet, most monitoring systems only see what happens within a single institution. This siloed approach makes it easy for bad actors to move illicit funds undetected across Correspondent Banks.

Consilient solves this with privacy-first collaboration:

🔹 Banks can detect high-risk patterns across institutions—without exposing raw data.
🔹 Federated learning aggregates insights from multiple sources, ensuring that each bank’s data remains private and secure.

Financial crime is evolving. Your risk model should too. By combining the latest technology with privacy-first collaboration, Consilient’s Correspondent Banking Model helps banks identify risks faster, cut down false positives, and focus resources where they’re needed most.

The results: Why banks are making the switch

Leading banks are already experiencing the transformative impact of Consilient’s Correspondent Banking Model:

✔ 76% fewer false positives: Compliance teams can focus on real risks.
✔ 244% increase in suspicious activity detection: Uncovering financial crime legacy systems miss.
✔ 92% reduction in compliance review costs: Cutting wasted resources and improving efficiency.

The best part? Banks don’t need to overhaul their systems to see results like these. 

Seamless integration, immediate impact

Consilient’s Correspondent Banking Model is designed to work alongside existing infrastructure, delivering faster, smarter detection without disruption.

🔹 No rip-and-replace: It enhances transaction monitoring and due diligence frameworks.
🔹 Plug-and-play integration: Designed to work seamlessly with existing compliance tools.
🔹 Minimal IT burden: Teams can stay focused on risk management.

From day one, banks see fewer false positives, sharper risk detection, and reduced operational strain.

Addressing common concerns 

“We already have robust due diligence processes. Why do we need this?”

Traditional due diligence processes, such as KYC and enhanced due diligence (EDD) provide an initial risk assessment but fail to capture evolving behavioral risks across a Correspondent Bank’s customer base. Consilient’s model goes beyond static risk profiles by: 

🔹 Continuously analyzing 12 months of behavioral data to identify emerging risks.
🔹 Flagging hidden risk indicators, such as identification nesting and high-risk jurisdiction transactions that traditional EDD might miss.
🔹 Provides risk-based scoring at scale, enabling banks to allocate their resources more effectively.

“How does this help us comply with evolving regulations?”

Regulators are demanding stronger controls in correspondent banking, and scrutiny around transaction monitoring and due diligence failures is only increasing.

✔ Strengthens your ability to identify hidden risks, making it easier to meet regulatory expectations around KYC and AML controls.
✔ Provides detailed risk scoring and explanations, helping banks justify their decisions to regulators and reduce compliance gaps.
✔ Enhances transparency without increasing manual workload, ensuring compliance teams stay ahead of emerging risks.

“How will this help with regulator and audit scrutiny?”

Regulatory fines and enforcement actions often stem from poor visibility into correspondent banking relationships—including failures to monitor underlying customers effectively.

Consilient’s model gives banks a defensible, data-driven approach:

✔ Providing clear risk scores and behavioral insights into Correspondent Bank’s customers, strengthening auditability.
✔ Reducing false positives, ensuring compliance teams aren’t overwhelmed with unnecessary alerts.
✔ Demonstrating a proactive approach to financial crime detection, boosting regulator confidence.

“We already have a transaction monitoring system—how does this fit in?”

Consilient’s Correspondent Banking Model isn’t a replacement—it’s an enhancement to your existing monitoring and due diligence frameworks. It:

🔹 Works alongside your current system, improving accuracy without requiring a rip-and-replace approach.
🔹 Adds a layer of intelligence specifically designed for the unique risks of correspondent banking, something generic AML systems don’t address.
🔹 Provides ongoing risk analysis, so you’re not just reacting to alerts, but identifying risks earlier.

“Is this scalable for global correspondent banking relationships?”

Absolutely. Consilient’s federated learning model is built for scalability, meaning:

✔ It adapts to different regions, risk profiles, and transaction types without the need for manual rule updates.
✔ It improves over time, ensuring detection stays sharp as criminal tactics evolve.
✔ It reduces operational strain, so compliance teams can handle large-scale monitoring efficiently.

So, now I have a question for you: Can you afford to wait?

Stronger detection. Fewer false positives. Smarter compliance

So there’s one question to ask: Can you afford to wait?

Regulatory pressure is increasing. Financial criminals are becoming more sophisticated. Sticking with the same outdated approaches is no longer an option.

With real-time behavioral risk analysis, privacy-first collaboration, and seamless integration, Consilient’s Correspondent Banking Model empowers banks to strengthen compliance, reduce costs, and stay ahead of financial crime.Take the next step today: Talk to us—we’d genuinely love to help.