Proven Results for Account Onboarding Fraud Solution

50%
Approval Rate Increase
Driving revenue and minimizing friction for good users
60%
Detection Uplift
Real-time detection system that stays ahead of evolving fraud patterns
$4M
Fraud Loss Savings
Mitigation of highest dollar losses with precise detection

You Have Challenges, We Have Solutions

Blind Spots

Limited
customer data

Accurate customer profile, Reduced risks.

Effortless integration with third-party signals including data from breaches found on the dark web, device intelligence and behavioral biometrics to build comprehensive customer profiles for effective KYC/KYB and fraud mitigation.

Unnecessary Friction

And costly reviews

Faster onboarding, Confident growth.

Customizable Decision Flows enables risk-based strategies to fast-track low-risk applicants and apply stricter controls to high-risk ones

False positives

Negative onboarding experience

Fewer disruptions, Happier customers

DataVisor’s dynamic Rules Engine, combined with AI Co-Pilot, reduces false positives by 50%.

Emerging tactics

New unknown fraud patterns

New threats unveiled, Reduced fraud losses

Patented unsupervised machine learning identifies new fraud patterns, including synthetic identities and bot-driven account creation. 

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Comprehensive Protection Against All
Types of Account Onboarding Fraud

Types and Methods of Account Onboarding Fraud
Synthetic Identity Fraud
Fraudsters create fake identities using partially or fully fabricated personal information, often combining fake names and IDs with stolen or random Social Security Numbers.
This is a common type of onboarding fraud where the fraudster uses stolen identity details to set up an account. They can then use this account to make purchases, take out loans, or launder money.
This occurs when a fraudster uses stolen or fake device information, or hides their real IP address, to avoid detection when creating a new account. Risk systems should track device information and flag suspicious activity, like multiple accounts created from the same device or IP address.
Fraudsters can use automated bots to create numerous accounts in a short period of time. Risk systems need to identify and block such high-speed, high-volume activity.
These are accounts created to launder money. A fraudster might convince an unsuspecting individual to open an account, then use it to receive and transfer illegal funds. Risk systems should flag unusual transaction patterns that could indicate a mule account.

Complete Protection for Your
Organization & Customers

Check Fraud
Stop first and third-party check
and deposit fraud.

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Application Fraud
Balance risk in account onboardings and loan applications.

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ATO Prevention
Protect customer accounts from takeover attempts

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ACH and Wire Fraud
Combat financial crime in electronic fund transfers

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Card Fraud
Block bad payments and reduce false declines.

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AML Compliance
Manage BSA/AML programs and limit risk exposure

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Stop Promotion Abuse with Advanced AI

Harness the power of superior detection, immediate decision, and real-time machine learning in a simple-to-use, intuitive platform. Confidently deploy sign-up bonuses, referral bonuses, free trials, reward policies, and other promotions with a powerful AI-based fraud solution that can process terabytes of behavioral and event information.

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Featured Resources

CASE STUDY
Leading US-based Card Issuer Reduces False Positives by 40% and Increases Detection.

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WEBINAR
Future-Proofing Customer Onboarding: Strategies and Practical Takeaways.

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CASE STUDY
Food Delivery Unicorn Uses DataVisor For Fraud-Free Rapid Expansion.

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