Integrating & optimizing data flows

Effective financial crime prevention hinges on one critical task: identifying bad actors while protecting legitimate users. This challenge becomes increasingly complex in high-volume transaction environments where determined fraudsters aim to blend seamlessly into the crowd. SEON equips you with the tools and data needed to tackle this complexity head-on.

Maximizing detection capabilities while minimizing operational overhead starts with identifying the right data. SEON helps strike this balance by supporting diverse data types to enhance fraud detection and AML compliance.

There are several data types you can provide:

• Customer data: Information about customers, including their identity and any known affiliations or relationships.
• Transaction data: Details of individual transactions, such as amounts, currencies, locations, parties involved and transaction methods.
• Geographic data: Location-based information that may help identify trends or anomalies in transaction patterns, such as transactions originating from high-risk jurisdictions or unusual cross-border activity.
• Counterparty data: Information about entities involved in transactions, such as businesses, individuals, or intermediaries, including their identities.
• Organization data: Setting up detailed organization information and contact details will enable automated prefilling of any SAR form, reducing repetitive manual workload.

And there are additional data types that SEON will provide:

• Behavioral data: Based on your transaction data, SEON will identify patterns of transactions and account behavior that may indicate suspicious activity, such as unusual transaction amounts, frequency, or timing.
• Alert data: Information generated by SEON’s alerting systems to flag potentially suspicious activity for further investigation, including alert details, severity levels, and timestamps.
• Compliance data: Records of compliance-related activities, such as due diligence checks, investigations, SAR filings, regulatory reports and audit trails.
• Fraud signals: Email verification, identification of risky emails, IP address data and phone numbers, along with a risk score based on Digital Footprint analysis.
• AML customer screening: This process involves checking individual or entity names against various watchlists and databases to identify potential matches with known criminals, terrorists or sanctioned individuals/entities. Additionally, it includes screening for politically exposed persons (PEPs) and adverse media mentions to assess reputational risk and ensure compliance with regulatory requirements.

One of the main advantages of using SEON is its highly flexible format. With our easy-to-integrate API, automating the entire data flow is effortless. Check out our API reference site.

However, for a quick start with SEON and seamless integration, leveraging our default AML transaction rules and enabling SAR autofill capabilities, we recommend using the following data points and format. If this doesn't suit your needs, SEON can provide customized mapping according to your requirements. Please consult with your onboarding officer.

Did you know: It's essential to understand that using the right data can enhance crime detection capabilities, and proper mapping can automate SAR creation by populating data automatically and generating SAR narratives with AI!

Setting up organization data to enable autofill capabilities for regulatory filings

Say goodbye to repetitive manual work. By inputting your organizational data once in Settings - Case Management - Filing Information, all future regulatory report filings will automatically include prefilled data. This ensures consistency, saves time, and allows your team to focus on high-priority tasks.