Tech Voices Episode #1 – Detecting Fraud Without Slowing Customer Onboarding

Hi, I am Betty Wang, Solutions Engineer at Actian. In this episode of Actian Tech Voices, I'll walk you through a real Know Your Customer, or KYC, fraud detection challenge we frequently see in financial services, and how teams can address it without slowing down customer onboarding. Financial institutions are under constant pressure to onboard customers more efficiently while still meeting strict know your customer and anti-money laundering compliance requirements.

The problem is that KYC data is often fragmented across systems and pipelines. Teams lack end-to-end visibility, data quality issues often go undetected, and high risk customers aren't always identified early enough.

The real challenge isn't just fraud detection, it's maintaining trust in the data without slowing this onboarding pipeline. So the real question becomes, how do we maintain data quality and visibility across the entire customer onboarding process while identifying high risk applicants and automatically detecting fraudulent activity? The KYC process is a five stage customer journey.

The key idea is to treat KYC as an end-to-end data product with visibility, quality, and controls embedded at every stage.

In this episode, we will demonstrate how Actian Data Intelligence solutions enable this in practice, combining data catalog and observability to deliver end-to-end visibility into the five stage KYC journey, automated data quality validation at each pipeline stage of the onboarding process, intelligent data bending to segregate high risk customers without breaking the pipeline and integrated alerting and remediation workflows. Let's start by searching for our KYC process in the Actian Data Intelligence Platform catalog through a curated view. Here we can see the complete customer journey through the five stages; account registration, identity verification, address verification, risk assessment, and final approval.

The value of leveraging this view is having the ability to layer in semantic context like approval status, regulation, compliances, et cetera, to give business users insight into catalog assets. It also provides the governance components with the list of contacts for clear ownership and stewardship. Now, let's examine what metadata is associated with each stage of the KYC process and how we can use Actian's Data Lineage platform to perform impact analysis and ultimately help identify fraudulent activity.

As customers are registering, they enter personal information such as name, number, address, etc., which comprises the raw layer in the bronze layer. In the silver layer, we enrich the data with external watch list checks to calculate risk factors of individuals. With our observability tool, high risk customers with the score of 17 plus are automatically binned while low risk customers flow into the gold layer for registration approval.

This pipeline continues uninterrupted, bad data segregated, and not blocking. Finally, referencing transactions, account, and risk factor data, financial institutions are able to flag potential fraudulent activity. At each stage of the data pipeline, the data quality indicator is embedded directly within the lineage, indicated by this circle in the upper right corner, allowing users to get real time scoring on the reliability of their data.

If we navigate to the data quality scorecard of a particular dataset, we can explore the exact data quality checks. We can even click into specific data quality violations, like which transactions are flagged for potential money laundering activity, which then takes us to our data observability platform. This investigator view provides root cause analysis, so it lets you drill into anomalies for failed quality checks to see what fields, segments, or records are causing the problem.

In this example, violations are either transactions above a certain amount or any transactions by high risk individuals. When issues arise, teams need to act fast, and servicing tickets can be created directly within the platform to kick off the remediation process when violations are detected. Additionally, for all data quality policies, Actian Data Observability allows you to set the appropriate notification channel so the right team is notified immediately when a violation occurs.

From detection to remediation, this can all be done within a single unified platform.

To wrap up, what we've shown in the session is complete visibility into the KYC pipeline, through integrated catalog and observability, proactive data quality monitoring with automated validation at every stage, intelligent data segregation that keeps pipelines running without disruption, and rapid incident response with automated alerting and ticketing workflows. Together, the Actian Data Intelligence Platform explains how data flows and what it means, while Actian Data Observability ensures that data flowing through those paths is correct and reliable. This combination reduces operational and regulatory risk, accelerates root cause analysis, and increases confidence in regulatory reporting.

Thanks for watching. Please visit actian.com and subscribe to the Actian YouTube channel to explore more episodes and related content.