How Row64 Aids Fraud Prevention

Financial fraud is a huge problem. Legacy data systems aren’t keeping up.

The costs of fraud to financial institutions are staggering. A report from Juniper Research estimates that global fraud losses to financial institutions could hit US$58.3 billion by 2030, up from about US$23 billion in 2025. Fraud doesn’t just mean losing money to criminals — it also means fighting disputes, as well as maintaining regulatory compliance and customer goodwill. 

Put simply, given the direct and indirect costs, fraud prevention continues to grow in importance, and legacy data systems aren’t equipped to handle it.

Legacy data systems can’t keep up.

Fraud is evolving rapidly, yet the fraud prevention systems are still playing catch-up. Some of the key pressure points:

Speed and scale

Attackers are using bots, automation, and synthetic identities at scale. Yet a 2025 LexisNexis study found that 44% of North American financial institutions still rely on manual fraud-detection processes. When millions of transactions, account-creation events, logins, and access attempts flow through an institution's systems, manual or batch detection becomes a liability.

Visibility and context

Many fraudulent events span multiple channels — including new account creation, loan origination, transaction behavior, and login anomalies — yet only some institutions track fraud comprehensively across all touchpoints. Without real-time access to data across the organization, subtle fraud patterns can go undetected until damage is done.

How Row64 helps institutions get ahead

Given the stakes, financial institutions can no longer afford to rely on systems that can’t process information at the speed and scale of today’s criminals. That’s why Row64’s CPU/GPU-accelerated, real-time visual intelligence platform is a game-changer for fraud teams in financial institutions. It provides real-time operational intelligence, acting as a command-and-control center for fraud detection teams by aggregating and correlating data from multiple sources—including data warehouses, streaming data, real-time data, and AI pipelines—so fraud teams can understand and act on events at a moment’s notice.

CPU/GPU-accelerated performance

Streaming updates at sub-millisecond speeds, visually exploring hundreds of millions of records (including both structured and unstructured data) in real-time demand a new level of performance. Row64’s CPU/GPU-accelerated architecture dramatically reduces latency, enabling fraud teams to bring together vast sources of information to explore, identify correlations, and flag issues that legacy systems simply cannot match.

Streaming data and interactive visualization at scale

Instead of waiting for batch fraud reports or isolated alerts, Row64 can stream aggregate data from batch, streaming, and real-time data sources, letting teams instantly explore millions of records across numerous touchpoints via GPU-accelerated dashboards. This means institutions can spot emerging threat patterns as they happen, not after the fact. 

Cross filtering for correlated data discovery

Humans are great at pattern recognition — but only if the data is surfaced in meaningful ways. Row64’s cross-filtering functionality enables fraud analysts to drill down from high-level dashboards into clusters of correlated information, e.g., multiple accounts created from the same device, followed by unusual transaction volumes or geographic locations. That kind of granularity helps spot bot attacks, account takeovers, and other incidents — before they escalate.

Cross-channel visibility

Because fraud doesn’t happen in isolation, Row64 enables teams to bring together data from multiple sources and streams — application data, transaction data, login/behavioural data, device & network signals — into a unified analysis interface where teams can detect patterns spanning the institution.

Putting humans in the loop

Institutions are leveraging artificial intelligence (AI) to help address this significant challenge. While AI automates parts of the process, institutions require a human in the loop to make final decisions when billions of dollars are at stake. Row64's precision and accuracy enable humans to quickly validate information, making it an indispensable part of the fraud detection pipeline.

Delivering ROI

Fraud isn’t simply a cost of doing business any longer — it’s a significant drag on profit, trust, and regulatory compliance. With every US$1 of fraud now costing financial institutions ~US$4–5 in total impact (and growing), the imperative for faster, more intelligent detection is greater than ever.

If a team reduces add-on costs by even $1 or 20-25% with a real-time visual intelligence platform like Row64, that could save an institution millions in direct costs while helping prevent customer churn. 

From Data Visualization to Real-Time Visual Intelligence

Legacy systems that rely on manual review, siloed data, and batch processing can’t keep up with the speed, scale, and complexity of modern attacks. Row64 changes the equation with a real-time, CPU/GPU-accelerated platform that transforms data visualization into a real-time command and control center, giving teams a single source for all operational data.