DEVELOPED BY DR. SUDIN BARAOKAR
Fabric trust index76.8

DKYC · module 03

Dating Know Your Customer

A high-trust identity safety framework for interpersonal digital environments — not a banking KYC substitute. Verification is continuous, because the risk appears long after onboarding.

Inject scenario

Continuous trust state

Rohit Menon · Social-discovery user · Bengaluru

70%Guarded

Trust_DKYC

0.70

Solicitation risk

31%

Voice authenticity

91%

Image-deepfake risk

6%

ID verification0.99
Face / liveness0.98
Device consistency0.94
Voice authenticity0.91
Image-deepfake risk0.06
Behaviour drift0.11
Scam-language risk0.08
Payment solicitation risk0.31

Signal-Wave phase sequence

SWAE matches an ordered phase pattern, not isolated anomalies

confidence 0.18
  1. 1New device registered+0.18
  2. 2Identity behaviour drift+0.24
  3. 3Rapid intimacy language+0.26
  4. 4UPI payment request+0.32
Behaviour(t)
Identity(t)
PaymentSolicitation(t)
DeviceRisk(t)

System output

Deterministic intervention, applied before money moves

ROMANCE_FRAUD_RISK = LOW
PAYMENT_NUDGE = NOT_REQUIRED

No phase sequence match. Trust state maintained; no friction applied.

Threat model

What DKYC exists to stop

CatfishingDeepfake identityRomance scamsImpersonationAccount takeoverCoercionMule recruitmentSynthetic identities

No claim is made that DKYC implements RBI KYC. Where a payment is involved, the regulated entity's own authentication, velocity, fraud and AML controls remain the binding controls.

AI risk narrative

Live reasoning over the current signal field

The deterministic layers above run without AI. Generate a narrative to add a plain-language explanation of the current state for reviewers and supervisors.