Businesses in high-risk sectors — like fintech, crypto, iGaming and online lending — are under pressure to stop fraud and money laundering while keeping onboarding friction low. At the same time, regulators are tightening requirements and handing out harsher penalties. In 2024, AML fines soared to an unprecedented $19.3 billion, more than triple the previous year’s total, and the trend shows no signs of slowing.
Traditional AML programs are falling behind. Slow processes, reactive detection and a flood of false positives are overwhelming compliance teams. It’s time to rewrite the playbook. The best way to stop bad actors is to catch them before they even reach the KYC stage.
The Cost of Waiting Until KYC
KYC checks work, but they can also take a long time. By the time identity documents are verified, fraudsters may have already bypassed early detection layers using throwaway emails, masked IPs or synthetic identities. What’s worse, traditional AML tools often flood teams with alerts that turn out to be false positives. Without early context on the user compliance teams are left guessing. That means real threats can slip through, while legitimate customers get delayed or rejected.
That’s where pre-KYC screening comes in. By analyzing a user’s digital footprint at the point of registration, businesses gain critical context that traditional KYC simply misses.
The Missing Piece Of The Puzzle: The Power of Pre-KYC Screening
By bringing screening forward, pre-KYC checks allow compliance teams to spot red flags instantly. That means fewer fake users slipping through, fewer unnecessary manual reviews and less time wasted chasing false positives.
- Flag suspicious behavior early: Fraud always leaves a trace — you just have to know where to look. By analyzing digital footprints right at signup, you can spot early warning signs and stop bad actors before they ever reach the KYC stage.
- Reduce false positives: Smarter detection saves your team from wasting time on false alarms. By adding context to your screening process, you can focus only on users who actually pose a risk.
- Onboard legitimate customers without friction: Real users shouldn’t get caught in fraud nets. With better insights, you can approve trustworthy customers quickly and deliver a frictionless onboarding experience.
Early detection doesn’t just stop fraud. It keeps your onboarding process smooth for good users, your compliance team efficient and your risk strategy one step ahead.
The Early Fraud Signs — And How To Spot Them
Nothing ever leaves the internet. Real users use social media, sign up for services and typically maintain their devices over long periods of time. A real online presence is almost impossible to fake, especially at a large scale.
Conversely, fraudsters show up with fresh credentials, anonymous setups and minimal digital history. With the right tools, you can detect these signals and block bad actors before they cause harm to your business.
- Check the digital footprint: Phone numbers or email addresses with no associated digital presence are strong indicators of fraudulent identities.
- Detect suspicious device setups: Devices with disabled cookies, disabled JavaScript or usage of anonymizing tools (VPN, proxies) often point toward high-risk or fraudulent activity.
- Find behavioral inconsistencies: Actions that don’t align with typical user behavior, such as rapid form submissions, unusual navigation patterns or mismatched time zones, can indicate automated activity or coordinated fraud attempts.
Don’t let fraud drain your resources. Take proactive steps to ensure business continuity.
Speak with an Expert
Optimize Monitoring With Dynamic Strategies
To stay ahead of evolving fraud risks, your screening and monitoring strategies must be as dynamic as the threats themselves. And while there’s no one-size-fits-all solution when it comes to AML, these best practices will help you find the workflow that fits your business the best:
1. Align Monitoring Frequency with Risk
One key strategy for optimizing your AML screening process is adjusting your monitoring frequency to align with each account’s risk level. This way, you can ensure that resources are allocated efficiently without compromising security. High-risk accounts (such as new users, those from high-risk regions or those with irregular behaviors) may warrant more frequent daily or weekly checks. On the other hand, lower-risk customers could potentially be monitored quarterly or even annually.
2. Create Customized Workflows
Your customer base is diverse — so is the risk associated with different segments. Whether risk is concentrated by geography, product or other factors, your screening workflows should reflect this diversity. Tailor your processes to effectively screen users based on their specific risk profile and ensure compliance in each market you operate in. This level of precision ensures that no threat goes unnoticed and no unnecessary checks slow down legitimate customers.
3. Screen for Relevant FATF Crime Categories
Enhancing your screening process means focusing on the crimes that matter most to your jurisdiction. The Financial Action Task Force (FATF) outlines specific predicate offenses — such as tax evasion, terrorism financing or human trafficking — that need to be considered when screening customers.
By ensuring your system targets these relevant crime categories, you can increase the effectiveness of your screening efforts while reducing unnecessary noise. This approach makes your compliance efforts more targeted, ensuring that the right threats are flagged without overwhelming your team with irrelevant alerts.
Best Practices for Tuning Fuzzy Search Sensitivity
Fuzzy search is a powerful tool that can detect name variations, misspellings, transliterations and other discrepancies in identifiers, significantly enhancing your AML efforts and accelerating reporting. However, a poor setup can lead to an overload of false positives, wasting time and resources. Following these best practices ensures your fuzzy search works efficiently and effectively to support your compliance strategy.
- Match fuzzy search sensitivity to risk: Different users carry different risk levels. Adjust your fuzzy search sensitivity accordingly:
- High-risk users (e.g., from high-risk regions or new accounts): Use medium-to-high sensitivity to catch name variations, transliterations, or common misspellings.
- Low-risk users: Dial sensitivity down to avoid flooding your team with false positives.
- Continuously review and improve your settings: Don’t set it and forget it. Regularly review your alert outcomes to identify patterns, reduce noise and improve hit accuracy. This dynamic tuning ensures your fuzzy search adapts as your risk environment evolves.
- Leverage contextual data to refine matching: Fuzzy search is more accurate when combined with additional contextual data. Incorporate relevant user information (such as location, device data or account history) to better assess the likelihood of genuine matches. This approach reduces false positives and sharpens the overall effectiveness of your screening process.
Uplevel Your AML Screening With SEON
SEON brings pre-KYC intelligence and AML precision together so your compliance team can catch threats faster and onboard trusted users effortlessly.
- Spot threats early: Use digital footprint analysis from the first touchpoint to detect suspicious patterns and assess risk from the first interaction.
- Zero in on real threats: Selectively enable global data sources — from sanctions and PEP lists to adverse media — to focus only on the information that matters most to your jurisdiction.
- Automate efficiency: Set customized customer screening frequencies based on risk and let SEON’s scheduling system handle the rest.
- Adapt as you go: Continuously tune thresholds and alert volumes to find the sweet spot between robust compliance and manageable workload.
Fraud Doesn’t Wait
And neither should you. With threats evolving by the minute, relying on outdated defenses is like locking the door after the break-in. The goal isn’t to react to what’s already happened — it’s to stop it before it starts. By detecting threats early and moving with intent, you defend systems and protect trust, reputation and revenue.
