What is transaction monitoring?

Don't get catfished by your customers — why you need transaction monitoring

In the age of dating apps, you have to sift through a lot of weird texts and bad first dates before you find your perfect match. If you're like me and have seen way too many episodes of MTV’s Catfish, the first thing you do when you come across someone you're interested in is make sure their profile belongs to a real person.

Then, you shoot some messages back and forth to get some preliminary information, see if there's chemistry, and confirm they aren't a total creep. A good first date is a promising sign, but you have to keep your eyes open for red flags as you get to know the person to protect yourself.

Oddly enough, financial institutions and fintechs follow a similar process when they onboard new customers and monitor their ongoing financial activity. First, they verify their customers' identities and evaluate whether they are a fraud risk. Then, they typically implement an ongoing monitoring solution to protect themselves from fraud risks. We’ve actually had requests come in to see if we could apply these same techniques to online dating, but sadly, we aren’t there yet.

What is transaction monitoring?

Transaction monitoring is the process of reviewing financial account activity — including customer transactions, money transfers, ATM withdrawals, etc. — against a set of rules to determine if the event or transaction should be approved, further investigated, reported, or denied. 

Transaction monitoring helps financial institutions and fintechs prevent money laundering, fraud, terrorist financing, identity theft, drug trafficking, and other illegal activity. It also supports sanctions compliance by screening transactions against government watchlists and blocking those involving restricted individuals, entities, or regions. This helps organizations avoid costly violations and stay aligned with evolving global regulations.

Anti-money laundering (AML) explained

Across the world, millions of financial transactions take place every day. According to the United Nations Office on Drugs and Crime, the estimated amount of money laundered globally is $800 billion - $2 trillion USD, or 2% - 5% of global GDP.

Anti-money laundering (AML) refers to the set of regulations, laws, and policies that prevent individuals from disguising money earned from illicit activities as legitimate income. To meet these requirements, financial institutions and fintechs must monitor transactions across multiple jurisdictions and report suspicious activity to law enforcement, helping prevent financial crime on both local and global scales. 

AML monitoring begins with customer due diligence (CDD) — verifying identities, understanding financial activity, and assessing risk before account opening. For higher-risk customers, institutions conduct enhanced due diligence (EDD), implementing more detailed verification and ongoing monitoring throughout the customer relationship.

A brief timeline of AML regulation

In the US, AML laws date back to the Bank Secrecy Act (BSA) of 1970, which requires financial organizations to keep records of financial transactions, flag any transactions exceeding $10,000, and report suspicious activity to prevent money laundering, tax evasion, or other illegal acts.

After 9/11, President George W. Bush signed the Patriot Act into law in an attempt to strengthen anti-terrorism efforts. Article III of the Patriot Act focuses on anti-money laundering to prevent terrorists from obtaining funds, adding new AML regulations to the existing BSA requirements, and tightening Know Your Customer (KYC) laws. 

These updates aligned the US more closely with global standards set by the Financial Action Task Force (FATF), an international body that guides how countries structure their AML and counter-terrorism financing frameworks. As a result, financial organizations must implement an AML transaction monitoring program with internal controls tailored to their business and customer base. 

To meet federal anti-money laundering compliance regulations, these programs must comply with requirements set by agencies such as FinCEN and outlined in the Bank Secrecy Act, including customer due diligence, ongoing monitoring, and the timely filing of suspicious activity reports (SARs).

Manually monitoring all financial activity would be impossible, so financial institutions and fintechs often turn to automated transaction monitoring systems. 

How automated transaction monitoring works

The transaction monitoring process works like having a digital bouncer available 24/7. The bouncer doesn’t just check IDs once. They keep tabs on who’s coming and going all night long, monitoring for behavioral red flags that could threaten the safety of other patrons and the establishment.

At a technical level, transaction monitoring involves continuously analyzing financial activity to detect suspicious behavior in real time. Here’s how it typically works under the hood:

Data collection and integration

Monitoring starts by pulling in transaction data through APIs from a wide range of sources — banking systems, payment processors, internal databases, and more — enabling real-time collection and analysis. This includes details like transaction amounts, locations, timestamps, counterparties, and customer profiles.

Rule-based screening

Every transaction runs through a set of predefined rules that flag high-risk behavior. Examples include unusually large transfers, frequent ATM withdrawals just below reporting thresholds, transactions involving high-risk countries, or parties listed on government sanctions lists.

Risk scoring and behavioral analysis

Transactions are then evaluated in context. Machine learning models or scoring engines assign a risk level based on factors like past behavior, account type, or transaction patterns. This helps prioritize which activities need urgent review.

Alert generation

If a transaction looks suspicious, the system triggers an alert. That alert can either be handled automatically (e.g., freezing a transaction) or escalated to a compliance analyst for review.

Case management and reporting

Compliance teams investigate flagged transactions and determine whether further action is needed, like filing a suspicious activity report (SAR) with regulators. Many systems also include case management tools to help track investigations and resolution steps.

Continuous optimization

Over time, institutions refine their rules, retrain models, and adjust thresholds to reduce false positives and improve performance as new threats emerge. 

Strong automated transaction monitoring programs don’t treat every customer the same. Risk-based monitoring allows institutions to tailor rules and thresholds based on each customer’s risk profile,  tightening scrutiny for high-risk individuals and reducing friction for low-risk ones. 

The best transaction monitoring systems combine rule-based logic with machine learning to identify suspicious activity while minimizing false positives. By analyzing historical data and adapting to new fraud patterns in real time, these systems offer both precision and flexibility. 

Learn what makes a machine learning model trustworthy, and how to act fast when threats hit

Transaction monitoring software within an ongoing fraud defense strategy

Aside from complying with AML regulations, the other main use case for transaction monitoring is to mitigate fraud. 

Most financial institutions and fintechs start with KYC and identity verification as a fraud prevention tactic as they onboard new customers. However, fraud doesn’t stop the moment someone’s identity is verified. In fact, only 33% of financial institutions detected fraud during onboarding, meaning the majority depend on transaction monitoring controls to identify threats after the fact.

Transaction monitoring is a crucial component of any anti-fraud strategy, as it provides a comprehensive view of your customers by identifying and evaluating ongoing fraud risks. I mean, things may be going great with the person you've started seeing. But if you're not paying attention to warning signs and trusting your gut, you might miss the moment your charming new partner starts double-tapping someone else’s selfies at 2 a.m.

When transaction monitoring is done correctly, you can be more lenient and experimental during the onboarding process because you’re confident your transaction monitoring software will catch any bad actors later.

In 2020, the fraud landscape faced more challenges than ever, as the COVID-19 pandemic forced everything to move online, whether organizations were ready or not. As a result, there was a significant rise in fraud, with mid-to-large digital financial firms experiencing almost a 40% increase in successful fraud attacks since the pandemic shutdown. The stakes are higher than ever now because fraud is not cheap. For every dollar lost due to fraud, financial services companies incur a cost of $4.76, up from $3.35 before the pandemic. A robust transaction monitoring software can help you catch fraudulent activity and protect you from losing money.

Is fraud just another cost of doing business? (It doesn’t have to be)

The expanding role of transaction monitoring

What started as a tool to flag suspicious activity for regulators has become something far more dynamic. Today’s transaction monitoring systems don’t just support compliance. They’re a key part of broader risk management strategies, helping institutions adapt to evolving threats and make smarter decisions across the customer lifecycle.

Here’s what that looks like in practice:

• For detecting fraud beyond onboarding — Identity verification is a starting point, not a finish line. Transaction monitoring flags suspicious behavior that surfaces later, like money muling, account takeovers, or unusual spending patterns.
• For continuous customer risk assessment — Monitoring helps institutions evaluate transactions in the context of a customer’s baseline behavior, enabling dynamic risk scoring as accounts evolve.
• For making faster, more confident decisions — Batch reviews aren’t fast enough for today’s threats. Real-time monitoring lets institutions act immediately by freezing transactions, escalating alerts, or applying safe-mode policies.
• For expanding coverage to new risk areas — From crypto and P2P payments to ecommerce flows, transaction monitoring now supports a broader range of financial products, channels, and risk surfaces.
• For smarter, AI-powered detection — As threats get more complex, artificial intelligence algorithms help spot patterns rules can’t catch, reducing noise and surfacing truly risky behavior.

Explore how Alloy’s AI-powered Fraud Attack Radar stops fraud at origination

What makes for good AML transaction monitoring systems?

Not all transaction monitoring tools are created equal. The strongest ones balance speed, flexibility, and transparency, helping you detect suspicious transactions in real-time, tailor your response, and back it all up with a clear audit trail. 

Here’s what to look for in an AML transaction monitoring system:

Real-time detection that keeps pace with modern threats

Historically, financial organizations used batch monitoring — reviewing transactions in bulk at the end of each day — to monitor for fraud. But as fraud grew faster, teams have shifted to real-time automated transaction monitoring to catch threats as they unfold. 

Modern transaction monitoring systems don't just detect suspicious activity — they connect detection to immediate action through automated decisioning. When high-risk behavior is identified, the system can automatically:

• Block suspicious logins before account access
• Freeze account activity if takeover is suspected
• Decline high-risk transactions in real-time
• Trigger step-up authentication for borderline cases

This automated response capability means institutions can mitigate risk without relying heavily on manual reviews. By automatically handling lower-risk alerts through measures like multi-factor authentication, compliance teams can focus their attention on investigating the most serious threats.

Today, more than half (56%) of financial organizations report catching fraud most commonly in real-time at the moment of transaction. But catching fraud is only half the battle — the ability to take immediate automated action is what prevents losses and protects customers while maintaining operational efficiency.

Ongoing monitoring across all account activity

Financial crime often manifests through patterns of behavior rather than individual transactions. The strongest monitoring systems look beyond individual transfers to track a wider range of account activities that might signal risk. This includes monitoring changes to personal information (PII), login patterns, device fingerprints, and attempts to link external accounts.

By tracking these behavioral signals alongside financial activity, institutions can build a more complete risk picture. For example, a customer updating their address might be routine – but if it's followed by unusual login locations and multiple large transfers, that combination could flag a potential account takeover in progress.

This holistic monitoring approach helps catch complex fraud patterns that might slip through transaction-only screening, while also reducing false positives by providing more context around suspicious activity.

Customizable rules that reflect your risk profile

Whether you're focused on AML compliance, fraud mitigation, or a little of both, flexible rules are non-negotiable. The best systems let you tailor transaction monitoring rules to match your customer segments, risk thresholds, and evolving fraud patterns. And, they don’t require coding.

With automated monitoring, every transaction runs through a custom-built set of criteria, flagging suspicious activity without slowing down everyone else. 

It’s like dating with standards: You're open-minded at first, but you’ve still got a clear list of red flags. Some things are personal preferences, others just happen to be widely agreed upon best practices — like avoiding someone who has bad breath or lives in their parents' basement.

Integrated case management for faster investigations

Flagging a transaction is only step one. You still need to figure out what to do once suspicious activity is detected, including whether to file a Suspicious Activity Report (SAR) or Currency Transaction Report (CTR). Strong monitoring systems come with built-in case management tools that promote operational efficiency by streamlining manual investigation and regulatory reporting workflows. Ideally, you should be able to view flagged activity, assign reviews, log outcomes, track resolution, and manage SAR/CTR filings all in a single dashboard, so you can avoid losing context by bouncing between systems.

Read the case study: How Grasshopper reduced manual reviews by 58% with Alloy

Audit-ready reporting that simplifies regulatory reviews

Whether you're preparing for an internal audit or responding to an exam request, a clear trail of decisions matters. Good systems make it easy to generate reports that show how alerts were flagged, reviewed, and resolved — helping you meet regulatory requirements without pulling data manually or stitching together PDFs at the last minute.

Explore the top challenges financial institutions face with AML monitoring

Alloy’s automated transaction monitoring software works for you and your customers

As a comprehensive identity and fraud prevention platform, Alloy unifies advanced fraud detection and scalable workflows in a single dashboard. Drawing from over 250 data solutions, we build dynamic customer risk profiles that evolve throughout their lifecycle. 

Our real-time monitoring capabilities, paired with flexible case management and detailed reporting, enable swift threat response while ensuring compliance and a seamless customer experience. Even better, our no-code APIs mean you can integrate our transaction monitoring solution without engineering resources.