Regulatory weight
RBI master directions on fraud, KYC, and customer due diligence demand real-time decisioning and a documented basis for every action you take. The bar rises every year.
Bank customer
DeviceTrusted
BehaviourGenuine
LocationConsistent
Digital footprintAged
One intelligence layer beneath every decision a bank makes about a customer
Banks make hundreds of decisions about a single customer — onboard, verify, lend, monitor, investigate — each drawing on a different system at a different moment in time. Sign3 puts one continuous intelligence layer beneath all of them: RBI-aligned, audit-defensible, built for Indian banking.
Every decision about a customer is only as good as the intelligence behind it. Banks are making them on half the picture
A bank carries obligations a fintech does not. Several pressures press at once.
Mule and ring exposure
Banks are the endpoint for mule networks. Clean-KYC accounts turn into pass-throughs, and the links only surface when you read across the whole customer graph, not one account at a time.
Audit accountability
Every decline must be reproducible months later. A black-box score the committee can't defend is a liability, not a control.
Banks' operational reality
Thin-file, first-time-formal customers under PSL targets. The segment hardest to understand and easiest to get wrong, in either direction.
A bank needs decisions that are fast, fair to thin-file customers, and defensible to a regulator — at the same time.
Device, behaviour, network and footprint, on every applicant
Money mule detection
Clean-KYC accounts that turn into pass-throughs, surfaced through device, behavioural, and network signals before the first transfer.
The decisions it sharpens
The decisions a bank’s risk team owns, mapped to Sign3’s intelligence layer.
A bank needs decisions that are fast, fair to thin-file customers, and defensible to a regulator — at the same time.
Account takeover prevention
A genuine login, the right password, a session driven by someone who isn’t the customer. Behavioural and device signals catch it before the transaction clears.
EDD case resolution
Cases that bounce between branch, zone, and head office for 15–20 days. Sign3 compresses the lifecycle and builds the audit trail as the case moves, not after.
Digital onboarding decisioning
Every new account scored across device, behaviour, and digital footprint before it opens. The applicant bureau can’t read, finally readable.
One platform across onboarding, monitoring, and financial-crime operations
The three suites map directly onto a bank's risk lifecycle, all reading from one customer graph.
Scores every applicant across device, footprint, location, image, and SMS before the account opens, catching mules and synthetic identities that clear KYC.
The modules that matter most for a bank: device and behavioural intelligence for mule and takeover defence, location for address verification, identity for KYC integrity.
The proof, from banking deployments
Measured across live banking and fintech deployments in India.
73%of money mules flagged at onboarding
Outperforming legacy systems by 3× (banking client).
83%reduction in money-mule account approvals
Neobank deployment.
47%reduction in fraud losses
Digital banking client.
<200msp95 decisioning latency
Inclusive of network round-trip.
Every decision about a customer is only as good as the intelligence behind it. Banks are making them on half the picture
A bank carries obligations a fintech does not. Several pressures press at once.
Regulatory weight
RBI master directions on fraud, KYC, and customer due diligence demand real-time decisioning and a documented basis for every action you take. The bar rises every year.
Mule and ring exposure
Banks are the endpoint for mule networks. Clean-KYC accounts turn into pass-throughs, and the links only surface when you read across the whole customer graph, not one account at a time.
Audit accountability
Every decline must be reproducible months later. A black-box score the committee can't defend is a liability, not a control.
Banks' operational reality
Thin-file, first-time-formal customers under PSL targets. The segment hardest to understand and easiest to get wrong, in either direction.
A bank needs decisions that are fast, fair to thin-file customers, and defensible to a regulator — at the same time.
Device, behaviour, network and footprint, on every applicantMoney mule detection
Clean-KYC accounts that turn into pass-throughs, surfaced through device, behavioural, and network signals before the first transfer.
The decisions it sharpens
The decisions a bank’s risk team owns, mapped to Sign3’s intelligence layer.
A bank needs decisions that are fast, fair to thin-file customers, and defensible to a regulator — at the same time.
Account takeover prevention
A genuine login, the right password, a session driven by someone who isn’t the customer. Behavioural and device signals catch it before the transaction clears.
EDD case resolution
Cases that bounce between branch, zone, and head office for 15–20 days. Sign3 compresses the lifecycle and builds the audit trail as the case moves, not after.
Digital onboarding decisioning
Every new account scored across device, behaviour, and digital footprint before it opens. The applicant bureau can’t read, finally readable.
One platform across onboarding, monitoring, and financial-crime operations
The three suites map directly onto a bank's risk lifecycle, all reading from one customer graph.
- At the gate
ScreenX
Scores every applicant across device, footprint, location, image, and SMS before the account opens, catching mules and synthetic identities that clear KYC.
- On the book
Cortex
Monitors every active account for mule formation, takeover, and behavioural drift, with adaptive authentication that steps up only where risk warrants.
- In operations
Escalation
Assembles financial-crime cases automatically and reads law-enforcement requests, freeze, lien, debit-freeze, routing them with a full audit trail.
The modules that matter most for a bank: device and behavioural intelligence for mule and takeover defence, location for address verification, identity for KYC integrity.
The proof, from banking deployments
Measured across live banking and fintech deployments in India.
73%of money mules flagged at onboarding
Outperforming legacy systems by 3× (banking client).
83%reduction in money-mule account approvals
Neobank deployment.
47%reduction in fraud losses
Digital banking client.
<200msp95 decisioning latency
Inclusive of network round-trip.