AML, KYC & Financial Crime
S

Signzy

Signzy sells digital onboarding, identity verification and compliance automation to banks, non bank lenders, payment providers and global enterprises. Its no code platform and application programming interface (API) catalog let an institution assemble a risk based onboarding journey without engineering, covering document capture and optical character recognition, biometric face match, liveness and deepfake detection, forgery checks, know your business verification, sanctions and politically exposed person screening, transaction monitoring and contract execution. Trust Scores built on more than 200 device, transaction and identity signals target mule account fraud.

Business verification screens companies against registries in more than 150 countries and all 50 US states. An agentic platform connects a bank's core system to the Central Know Your Customer Records Registry for search, validation, upload and monitoring, converting records to the registry's 2.0 schema. Customers include HSBC, Citi, ICICI Bank, Amazon Pay, Stripe and Mastercard, and the company has grown to a team of more than 400 across three geographies.

Last VerifiedOctober 13, 2026
Compare Signzy with other vendors
Founded
2015
Headquarters
Bengaluru, Karnataka, India
Website
www.signzy.com
Categories
aml-kyc-financial-crime, fraud-and-transaction-risk, compliance-and-surveillance
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 9 graded A or B

AI Capability
AI Centrality
BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a rules or workflow system.
Vendor Published

Face matching, liveness and deepfake detection run on first party models, alongside patented video fraud detection. An orchestration layer that routes each customer through configured checks would still be worth buying on its own.

Autonomy and Oversight Model
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism, or full automation is presented as the entire disclosure. Human in the loop appears as a phrase rather than a described control.
Vendor Published

Risk based journeys let an institution route each customer by risk level, geography and product type, and verification that once took days now completes in under a minute. Those choices are made at design time. At decision time, a review queue, escalation threshold or alternative evidence path for someone the system cannot verify goes undescribed, which leaves the hardest cases to whatever process the institution builds around the product.

Model Risk Management and Transparency
CC on Model Risk Management and TransparencyTransparency is claimed in general terms with no mechanism a model validator could interrogate.
Vendor Published

Video verification is stated as 95 percent accurate for face match, liveness and live location detection, a figure published without its method or test population. More than 1 billion users verified measures volume, not how often a verification was right. False match and false rejection rates, presentation attack accuracy and accredited third party evaluation are absent.

Operational and Outcome Evidence
BB on Operational and Outcome EvidenceVendor aggregate claims with real figures, or audited scale disclosures from a publicly listed company.
Vendor Published

HSBC, Citi and Stripe sit among named customers, with more than 500 companies served, but none is joined to a measured outcome. Recognition from awards and analysts fills the space where results would sit.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

Models are trained on millions of real verification attempts from actual banking customers, so customer data improves the models every other customer uses. Consent, whether biometric captures join the training set and whether a bank can opt its customers out are not addressed.

Regulatory and Compliance
GLBA and Data Privacy Posture
BB on GLBA and Data Privacy PostureA substantive privacy document that reaches the product itself, short of the subprocessor list or the full data handling detail.
Vendor Published

Personal information collected through the APIs, directly or via integrating customers, falls under a privacy policy updated February 20, 2025, with heightened security for facial images and biometric templates. Illinois, Washington and Texas residents get specific biometric notices, and retention runs as long as necessary without fixed periods.

Security Certifications and Trust Center
BB on Security Certifications and Trust CenterA recognized certification named in the vendor’s own material without the artifact, or with a scope or renewal question the buyer has to raise.
Vendor Published

ISO 27001 certification is stated alongside an untyped SOC 2 compliance claim, 256 bit encryption and round the clock security monitoring. Certificate scope is not given, and no accredited presentation attack detection certification appears for the biometric checks.

Regulatory Status and Licensure
BB on Regulatory Status and LicensureThe regulatory position is clearly stated and appropriate to the product, with part of the verification left to the buyer.
Vendor Published

Searches, uploads and monitoring against the Central KYC Records Registry are automated, and video based customer identification, a modality the Reserve Bank of India introduced, is a core product. Those processes run under the regulated institution's own registration rather than any admission Signzy holds.

AI Governance and Bias Disclosure
DD on AI Governance and Bias DisclosureNothing published on a product where the bias risk is concrete, such as credit decisioning or underwriting with no fair lending, disparate impact or adverse action disclosure.
Vendor Published

False rejections in face matching and liveness fall unevenly by skin tone, age and gender, and Trust Scores built from device and behavioral signals can read atypical interaction as mule risk against a named person. Demographic error rates, independent face recognition evaluation and an appeal route are all unpublished.

AI Liability and Recourse
CC on AI Liability and RecourseMechanisms that enable challenge, such as audit trails and source traceability, with nothing standing behind the output and no route for the person affected.
Vendor Published

The person verified holds access, correction and deletion rights over API collected data, a data route rather than recourse for the decision. Someone failing a face match or liveness check is not told which system decided, and no guarantee or accuracy commitment stands behind the output.

Integration and Deployment
Model Supply Chain Disclosure
BB on Model Supply Chain DisclosureSubstantial partial disclosure, or a chain that is structurally short: an explicit in house build, on premise deployment, per customer instances, or zero retention at the model layer.
Vendor Published

Mastercard and Microsoft are named at the commercial level, and the endpoint catalog is openly an aggregation of external verification and data services. Individual data providers, hosting and analytics providers and any model provider for the biometric components are unnamed.

Core Systems and Integration Depth
BB on Core Systems and Integration DepthNamed systems or a documented public API, with the depth or the production evidence left open.
Vendor Published

API reference documentation at docs.signzy.com covers more than 340 endpoints and low code widgets, with go live stated in days. How deep the connection runs into an institution's own core banking or origination systems is left open.

Deployment Model and Data Residency
BB on Deployment Model and Data ResidencyStated residency commitments or regional hosting options.
Vendor Published

Data localization and residency are listed among security commitments, and processing occurs in the United States, India and other jurisdictions. Hosting provider, selectable regions and a private deployment option are left out.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

Pricing is absent from the vendor's own site, with no rates, tiers or basis of charge, so video verification and the API catalog cannot be sized before a sales conversation. Subscription plus per call descriptions come from outside reviews, not the vendor.

Institution and Segment Coverage
AA on Institution and Segment CoverageThe financial segments served are named and each carries its own maintained material, whether the coverage is broad or deliberately narrow.
Vendor Published

Banks, payments firms and crypto exchanges such as Coinbase and Binance sit alongside enterprises, with journeys covering account opening, loan disbursement and credit card issuance. Operations span India, the United States and the Middle East.

Head to Head

Compared With

Most editorial comparisons pair two vendors the index assesses as direct competitors for the same buyer. Some pair vendors that are adjacent rather than rival, where the useful question is where one ends and the other begins. Each carries a verdict, the buyer conditions that favor each vendor, and a graded side by side.

Alternatives to Signzy

Vendors in the same categories as Signzy whose profiles look most alike, each with a line on what the product does. Similar is not the same: check that each one does the job you need. No vendor pays for placement.

LexisNexis Risk Solutions is a data and analytics business founded in 1997, headquartered in Alpharetta, Georgia and owned by RELX.

Alloy is an identity risk orchestration and decisioning platform for banks, credit unions and fintechs.

IDfy runs identity verification, business verification, fraud detection and background verification for banks, non banking lenders, insurers, payments and wealth firms across India…

Fourthline handles customer due diligence and anti money laundering compliance for European banks, fintechs, insurers and brokers, combining proprietary models for document authenticity…

IMTF is a Swiss software company.

Nufi verifies people and businesses in Mexico through background check reports, identity validation APIs, a business verification product and a document extraction service.

The index publishes no overall score or ranking. See what we assess and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

No pricing data has been verified for this vendor. Pricing information will be published here once confirmed through vendor disclosure or third-party estimation.

Contact us

Found a vendor we missed? Have feedback on the index? We’d love to hear from you.

AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 610 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 20, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
© 2026 AI FinTech Index
3801 N Capital of Texas Hwy, Ste E240 · Austin, TX 78746