Digital-first institutions collect fewer signals at onboarding than traditional banks, yet operate at the same risk exposure. Sign3 adds the intelligence layer that closes that gap, across onboarding, fraud, credit, and monitoring decisions.
Four gaps that open when the branch disappears but the exposure doesn't.
Digital-first onboarding collects fewer data points than traditional branch-led processes, yet the fraud, credit, and compliance exposure is equivalent. The decisioning layer operates on a fraction of the information a bank would require for the same risk decision.
Customer-facing onboarding has moved to real-time, mobile-first flows. The risk and fraud infrastructure behind them has not kept pace. Rule-based engines, static thresholds, and manual review queues were designed for a different volume and a different speed.
Most fintech risk infrastructure focuses on the point of onboarding. Post-signup, the customer enters the product with minimal ongoing monitoring. Abuse patterns, behavioural drift, and exploitation develop over weeks in the gap between signup and first loss.
Digital lending guidelines, DPDP compliance, and KYC master directions apply to fintechs with the same force as to banks. Regulatory infrastructure that was once optional is becoming mandatory, on the same timeline, with a fraction of the compliance headcount.
A fintech needs decisions that are instant, defensible, and made on more than the four fields a signup form collects.
Device, behaviour, footprint, location and image, on every signup
Every new signup scored across device, behaviour, and digital footprint before the account is created. Synthetic identities, device-farm registrations, and fabricated profiles caught at the point of entry. 84% reduction in fraud approvals at a leading fintech.
The decisions a fintech's risk and product team owns, mapped to Sign3's intelligence layer.
A fintech needs decisions that are instant, defensible, and made on more than the four fields a signup form collects.
Coordinated account creation across shared devices, IPs, and behavioural patterns, detected at the network level. Individual accounts that pass every check become visible when read as a group. 95% reduction in fraudulent referral payouts.
Alternate data signals from device, footprint, location, and SMS that provide a credit read on the borrower bureau cannot score. 128% disbursal uplift with no rise in defaults.
The same signals that identify a fabricated user also reveal the highest-value genuine ones. Digital maturity, affluence indicators, and behavioural depth turned into user segments for pricing, targeting, and premium experiences.
A single integration point. Three steps. A decision before the account is created.
The standard data points already collected during signup, phone, email, device, selfie, and document, are passed to Sign3 via a single SDK or API call. Nothing additional is collected from the user.
Measured across live fintech and neobank deployments in India.
14xROI in the first deployment phase
Neobank client.
95%reduction in fraudulent referral payouts
Investment app.
84%reduction in fraud approvals at onboarding
Leading fintech.
<200msp95 decisioning latency
Inclusive of network round-trip.
Four gaps that open when the branch disappears but the exposure doesn't.
Digital-first onboarding collects fewer data points than traditional branch-led processes, yet the fraud, credit, and compliance exposure is equivalent. The decisioning layer operates on a fraction of the information a bank would require for the same risk decision.
Customer-facing onboarding has moved to real-time, mobile-first flows. The risk and fraud infrastructure behind them has not kept pace. Rule-based engines, static thresholds, and manual review queues were designed for a different volume and a different speed.
Most fintech risk infrastructure focuses on the point of onboarding. Post-signup, the customer enters the product with minimal ongoing monitoring. Abuse patterns, behavioural drift, and exploitation develop over weeks in the gap between signup and first loss.
Digital lending guidelines, DPDP compliance, and KYC master directions apply to fintechs with the same force as to banks. Regulatory infrastructure that was once optional is becoming mandatory, on the same timeline, with a fraction of the compliance headcount.
A fintech needs decisions that are instant, defensible, and made on more than the four fields a signup form collects.
Device, behaviour, footprint, location and image, on every signupEvery new signup scored across device, behaviour, and digital footprint before the account is created. Synthetic identities, device-farm registrations, and fabricated profiles caught at the point of entry. 84% reduction in fraud approvals at a leading fintech.
The decisions a fintech's risk and product team owns, mapped to Sign3's intelligence layer.
A fintech needs decisions that are instant, defensible, and made on more than the four fields a signup form collects.
Coordinated account creation across shared devices, IPs, and behavioural patterns, detected at the network level. Individual accounts that pass every check become visible when read as a group. 95% reduction in fraudulent referral payouts.
Alternate data signals from device, footprint, location, and SMS that provide a credit read on the borrower bureau cannot score. 128% disbursal uplift with no rise in defaults.
The same signals that identify a fabricated user also reveal the highest-value genuine ones. Digital maturity, affluence indicators, and behavioural depth turned into user segments for pricing, targeting, and premium experiences.
A single integration point. Three steps. A decision before the account is created.
The standard data points already collected during signup, phone, email, device, selfie, and document, are passed to Sign3 via a single SDK or API call. Nothing additional is collected from the user.
Sign3 enriches the application across five signal modules: device intelligence, digital footprint, behavioural biometrics, location intelligence, and image intelligence. Over 3,000 attributes are generated and resolved into a single customer persona.
A risk verdict is returned in under 200 milliseconds: approve, step-up, or decline. Every score is explainable, every threshold is tunable, and every decision is logged with the full signal trail for audit and reproducibility.
Measured across live fintech and neobank deployments in India.
14xROI in the first deployment phase
Neobank client.
95%reduction in fraudulent referral payouts
Investment app.
84%reduction in fraud approvals at onboarding
Leading fintech.
<200msp95 decisioning latency
Inclusive of network round-trip.
We'll score it, surface the fraud patterns your current stack missed, and walk you through what we found. Your data, our scoring. No commitment, no integration, no decision required until you've seen the result.