OneKYCby OneHypernet
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Stop account takeovers, mule networks, and synthetic identities

Real-time fraud signals across onboarding, login, and transaction events. Fused with your AML controls so one team, one case manager, and one customer view handle both.

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GDPR Compliant
AICB Asian Institute of Chartered Bankers
ISO 27001 Information security certified
Cyber Essentials Security controls assessed
MAS FSTI Proof of concept grant
Singapore Pawnbrokers' Association Official compliance partner
Standard Chartered Team background
Bank of Singapore Team background
Citibank Team background
Morgan Stanley Team background

Unify every signal into one real-time decision.

Combine device, behavioural, IP, velocity, and identity signals across login and transaction events to detect suspicious activity in milliseconds.

Signals capturedLive
DeviceNew device · emulator detected
alert
Behavioral biometricsTyping cadence drift
drift
IP / geoResidential proxy
alert
Velocity3 password resets in 24h
drift
Identity matchDoc hash matches prior session
ok
Fraud score
76/100
Medium-High
Decision
AllowStep-upHoldBlock
Stepped up to MFA · safe sessions stay frictionless

Fraud signals, connected

Every signal is evaluated together, not in isolation. Broader coverage, smarter decisions, and fewer false positives.

Device & session

  • New or unseen devices
  • Emulator / virtual environment
  • Residential proxy or VPN
  • Impossible travel patterns

Behavior & identity

  • Typing cadence & behavioral drift
  • Name mismatch & identity risk
  • Document reuse & tampering
  • Synthetic identity indicators

Network & velocity

  • Shared devices & fingerprints
  • Shared beneficiaries & payees
  • Rapid movement & structuring
  • Mule network patterns

All signals combinedto generate a real-time fraud score and recommended action.

Fraud score76
Recommended actionStep-up authenticationAdditional verification required

From risk score to real-time action

Configure what happens at every risk level, from allowing trusted sessions to stepping up, holding, or blocking risky activity.

Allow

Low risk, trusted session

  • Known device
  • Trusted behavior
  • Low risk score
Risk score0 - 39
ExampleUser can continue without interruption.

Step-up

Elevated risk, verify user

  • New or unknown device
  • Unusual behavior
  • Medium risk score
Risk score40 - 69
ExampleRequire MFA or additional verification.

Hold

High risk, review needed

  • High-risk signals detected
  • Unusual patterns
  • High risk score
Risk score70 - 89
ExampleHold the event and route to investigator.

Block

Severe risk, stop activity

  • Confirmed fraud indicators
  • Policy violation
  • Very high risk score
Risk score90 - 100
ExampleBlock the session or transaction.

Where fraud teams deploy it

Real-world scenarios. Real-time decisions.

Synthetic ID at sign-up

Block fabricated identities by combining device, behavioral, and identity-document checks.

NameJohn Smith
DocumentPassport
DevicePreviously used by 4 identities!
EmailDisposable domain
DecisionDecline application

Account takeover at login

Detect compromised credentials and unusual sessions in real time and step up the right ones.

Known locationSingapore
Current locationRomania!
DeviceNew device
BehaviorTyping cadence mismatch
Risk score76 /100
DecisionStep-up MFA

First-party and APP fraud

Surface social-engineering and authorized push-payment patterns before settlement.

BeneficiaryNew payee!
AmountUSD 18,500
Payment methodBank transfer
PatternMatches prior scam cases
Risk score81 /100
DecisionHold payment

One platform for fraud and AML

See how investigators work both fraud and AML cases out of the same workspace, with shared customer context.

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