Banking

Reduce financial loss with real-time fraud detection.

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DataVisor Solutions for Banking

DataVisor protects banks from account takeovers, identity theft, money laundering, and fraudulent transactions before any damage is done. Unlike traditional rule-based solutions, DataVisor’s unsupervised detection algorithm looks at all user accounts holistically to find suspicious evolving patterns and drastically reduce false positives. The unique combination of unsupervised machine learning, supervised machine learning, rules and reputation signals enable DataVisor to detect fraudulent behavior with unmatched precision and coverage.

90%
detected early or in real-time

Early detection

Detect “sleeper cell” accounts at early incubation stages by continuously analyzing all events conducted by the user account

50%+
additional detection

Unparalleled accuracy and coverage

Detect more high-risk accounts and reduce false positives with superior accuracy to shorten manual review time

500K+
bad accounts detected per day

Unknown threat protection

Uncover new, sophisticated attack campaigns without any training data or labels

Financial Fraud Datasheet
AML Datasheet

Key Use Cases

Account takeover detection

Detect when good accounts have been compromised by bad actors before it leads to damage for your customers or your platform

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Identity theft protection

Prevent identity theft by stopping fake accounts created using stolen credentials

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AML transaction monitoring

Uncover the hidden links between linked accounts and reduce false positives with unsupervised machine learning detection and automated rules tuning

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Fraudulent transaction detection

Reduce financial fraud by up to 50% above traditional fraud solutions by catching entire crime rings hours or days before they attempt a fraudulent credit card transaction

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Bringing Real Value to Our Customers

QUOTE

“DataVisor has been a key partner of our growing banking units. Their innovative system not only helped us detect additional fraud, but also decreased our window of exposure by detecting bad accounts earlier. I was also impressed by the ease of integrating DataVisor into our existing systems.”

– Director of Bank Fraud Strategy, F500 Bank

CASE STUDY

DataVisor Uses AI to Stop Identity Thieves in F500 Bank

This F500 Bank experienced strong growth in new bank account openings. However, the rapid growth was accompanied by fake accounts created using stolen identities. Read this case study to learn how DataVisor detected an additional 30% of fraudulent accounts on top of the bank’s existing in-house detection solution.

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Key Platform Features

Unsupervised Machine Learning Engine

Identify unknown threats by linking bad actors through correlation of account and event attributes

Supervised Machine Learning Engine

Provide supplementary attributes from known bad actors discovered by unsupervised machine learning and client-provided labels

Automated Rules Engine

Automatically generate and sunset rules periodically using DataVisor’s recommendation engine, powered by unsupervised machine learning

DataVisor Global Intelligence Network

Monitor the broadest array of telemetry signals from over 1.3 billion users from a variety of verticals

Account linkage view to discover hidden links among malicious accounts

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Getting Started

Request a security assessment today to learn how DataVisor can help find malicious accounts hiding inside your financial institution.

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