Mule networks
Score before
you trust.
The AI-powered API for identity, income, and fraud intelligence. iScoreIt transforms complex data into predictive risk scores. Evaluate every applicant with AI-driven precision and make confident, defendable decisions in under a second.
drag the globe
Built for banks, NBFCs, fintechs and marketplaces
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Verification APIs
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Median response
0%
Platform uptime
0 key
UAT and live, one console
The same platform, tuned to your risk.
Underwrite thin-file borrowers without asking for a single document.
Surrogate and bureau signals give you an income estimate, an ability-to-pay view and a fraud read before the applicant ever uploads a payslip.
- Document-less estimated income for salaried and self-employed profiles
- Bank statement analysis with salary, obligation and bounce detection
- First-party fraud checks on device, mobile vintage and email footprint
- Policy changes shipped from the console, not a release cycle
Application received
PAN, mobile, consent captured
Identity & bank verified
Name match + reverse penny drop
Income estimated
Surrogate model, no upload
Decision returned
Approve, limit ₹1.87L
Onboard merchants in minutes, and keep mules out of your payout rails.
KYB, beneficial ownership and payout-account screening run in the same call, so a seller goes live the same day without opening a hole in settlement.
- GSTIN, MCA, Udyam and shop licence checks with director linkage
- UPI ID and bank account verification before the first payout
- MuleNet screening against collection accounts seen in the wild
- Ongoing monitoring — accounts re-scored, not just checked once
Merchant signs up
GSTIN + PAN submitted
Entity graph built
3 directors, 1 linked entity
Payout account screened
Not seen on collection pages
Live with monitoring on
Re-scored every 24 hours
AML screening and an audit trail your regulator can actually read.
Every check, every model version and every override is stored against the case. Replay any decision from six months ago exactly as it was made.
- Sanctions, PEP and adverse media screening with tunable match thresholds
- Full decision replay — inputs, policy version, outcome
- Maker–checker on policy changes, with diff history
- Data residency in India, consent artefacts stored with every call
Case opened
Ref DEC-88214 · 14 Mar
Screening run
Sanctions, PEP, adverse media
Analyst disposition
False positive, note attached
Replay available
Inputs, policy and model frozen
One request enters — through the API door — Console and VerifyLink land in the same place.
Your policy loads — v3.2, versioned, owned by risk.
Checks fire in parallel, each against the issuing source.
One source stalls. Failover reroutes it — the funnel never notices.
Signals become one score, weighted by your policy.
Decision out — approve, with reason codes, consent artefact and audit trail attached.
Degrade gracefully, never silently.
A verification call that fails closed can stop your business; one that fails open can cost you far more. iScoreIt does neither — it tells your policy exactly which signal is missing and lets you decide.
Per-signal status
Every check returns its own status, not an all-or-nothing response — a slow source never sinks the whole call.
Automatic failover
Where more than one upstream source exists, traffic reroutes on its own and the journey never notices.
Replay & audit
Idempotency keys, versioned policies and a stored consent artefact make any decision reproducible months later.
Three products. One decision surface.
Pulse
The decision engine your risk team can edit themselves — policies versioned on save, shipped without a release cycle.
Verify
Onboarding journeys that stop asking once they are sure — risk-based step-up, hosted or headless.
MuleNet
The money-mule map, built from what fraud actually publishes — payout accounts screened before the money moves.
Dialect
Voice agents that verify while they talk — twelve Indian languages, identity confirmed mid-call, every conversation scored and filed.
What we learn from the fraud we see.
Our team publishes what the data shows — how mule chains are actually structured, which signals hold up under pressure, and where verification quietly fails.
Thin-file credit
Estimating income without documents: which surrogate signals actually predict repayment
Device intelligence
The shared-device problem: when account linkage is fraud and when it is a family
Customer · Head of Credit Risk
“We were running six vendors and reconciling them by hand. iScoreIt collapsed that into one call and one policy — and the review queue dropped by more than half in the first month.”
AI RISK INTELLIGENCE · KYC & FRAUD APIS FOR INDIA
IDENTIFY
Score before you trust. One API layer for identity,
income and fraud intelligence — 40+ signals · one request.
POST /v1/DECISION · 200 OK · 412 MS
SCORE
Every applicant, merchant and payout account becomes
a decision your team can defend — iScore 782 · low risk · approve — in under a second.
MULENET · CONTINUOUS FRAUD DISCOVERY
SECURE
MuleNet maps money-mule networks from the deposit pages fraud publishes,
and screens your accounts before the money moves.
SANDBOX KEYS THE SAME DAY · DATA RESIDENCY IN INDIA · 99.9% UPTIME
Pulse decides. Verify onboards. MuleNet protects. Dialect calls.
Three products on one identity graph, one policy engine and one audit trail — so a decision made anywhere is explainable everywhere.
Pulse decision engine
The decision engine your risk team can edit themselves.
- Visual policy builderno deploy
- Shadow & champion–challengersafe rollout
- Decision replayaudit
- Cost-aware waterfallsspend control
Verify onboarding suite
Onboarding journeys that stop asking once they are sure.
- Hosted or headlessyour call
- Risk-based step-upless drop-off
- UAT and live in one consoleone key set
- Re-KYC & periodic reviewstays current
MuleNet fraud intelligence
The money-mule map, built from what fraud actually publishes.
- Continuous discoveryalways on
- Screenshot-backed evidencedefensible
- Linkage scoringbeyond exact match
- Payout-time screeningbefore money moves
Dialect voice agents
Voice agents that verify while they talk.
- Twelve Indian languages, code-mixedswitches mid-call
- Identity confirmed inside the callnot assumed
- Conduct guardrails and calling windowenforced
- Every call scored, not sampledQA on 100%
Built for the teams who carry the risk.
Lenders, fintechs and compliance teams run the same platform with different policies — same signals, same audit trail.
Underwrite thin-file borrowers without asking for a single document.
Surrogate and bureau signals give you an income estimate, an ability-to-pay view and a fraud read before the applicant ever uploads a payslip.
- Document-less estimated income for salaried and self-employed profiles
- Bank statement analysis with salary, obligation and bounce detection
- First-party fraud checks on device, mobile vintage and email footprint
- Policy changes shipped from the console, not a release cycle
Application received
PAN, mobile, consent captured
Identity & bank verified
Name match + reverse penny drop
Income estimated
Surrogate model, no upload
Decision returned
Approve, limit ₹1.87L
Onboard merchants in minutes, and keep mules out of your payout rails.
KYB, beneficial ownership and payout-account screening run in the same call, so a seller goes live the same day without opening a hole in settlement.
- GSTIN, MCA, Udyam and shop licence checks with director linkage
- UPI ID and bank account verification before the first payout
- MuleNet screening against collection accounts seen in the wild
- Ongoing monitoring — accounts re-scored, not just checked once
Merchant signs up
GSTIN + PAN submitted
Entity graph built
3 directors, 1 linked entity
Payout account screened
Not seen on collection pages
Live with monitoring on
Re-scored every 24 hours
AML screening and an audit trail your regulator can actually read.
Every check, every model version and every override is stored against the case. Replay any decision from six months ago exactly as it was made.
- Sanctions, PEP and adverse media screening with tunable match thresholds
- Full decision replay — inputs, policy version, outcome
- Maker–checker on policy changes, with diff history
- Data residency in India, consent artefacts stored with every call
Case opened
Ref DEC-88214 · 14 Mar
Screening run
Sanctions, PEP, adverse media
Analyst disposition
False positive, note attached
Replay available
Inputs, policy and model frozen
Forty-plus checks. One key. One catalogue.
Send an applicant, name a policy, get a scored decision back with every underlying signal attached — sandbox and live behave identically.
Identity
PAN, voter ID, driving licence and passport — plus Aadhaar and every other document pulled straight from DigiLocker, on your own requester registration. Face match, liveness and OCR handle whatever still arrives as an image.
Business & KYB
GSTIN, CIN and MCA filings, Udyam, shop & establishment licences, director networks and beneficial ownership — resolved into one entity graph.
Banking & payments
Penny drop, reverse penny drop over UPI, UPI ID validation, IFSC resolution and bank statement analysis with salary and obligation tagging.
Signal intelligence
Device fingerprinting, email existence and digital footprint, mobile vintage and porting history, IP and geo risk — the quiet signals fraud can't fake cheaply.
Income intelligence
A monthly income estimate built from surrogate and bureau signals. No payslip, no statement upload, no drop-off in the middle of your journey.
AML & screening
Sanctions, PEP and adverse media screening with tunable thresholds, ongoing rescreening, and dispositions stored against the case for audit.
The module that matters
Fraud & mule intelligence
MuleNet continuously discovers illegal betting and gambling deposit pages, captures the collection UPI IDs, account numbers and QR codes shown on them, and screens your accounts against that evidence repository.
The full catalogue
26 endpoints, grouped by the question they answer.
Get sandbox keysBuilt for developers
- Idempotent requests and signed webhooks
- Sandbox that returns the same shape as live, with seeded test identities
- SDKs for Node, Python, Java and PHP
- Every response carries the policy and model version that produced it
One endpoint. Every signal.
Send an applicant, name a policy, get a scored decision back with every underlying signal attached. No orchestration code, no vendor-by-vendor error handling, no reconciliation job.
- Idempotent requests and signed webhooks
- Sandbox that returns the same shape as live, with seeded test identities
- SDKs for Node, Python, Java and PHP
- Every response carries the policy and model version that produced it
What the data shows.
Our team publishes what the data shows — how mule chains are actually structured, which signals move approval rates, what income estimation gets right and wrong.
Mule networks
Anatomy of a mule chain: how deposit money moves through hundreds of accounts in a single afternoon
Thin-file credit
Estimating income without documents: which surrogate signals actually predict repayment
Device intelligence
The shared-device problem: when account linkage is fraud and when it is a family
Customer · Head of Credit Risk
“We were running six vendors and reconciling them by hand. iScoreIt collapsed that into one call and one policy — and the review queue dropped by more than half in the first month.”
Identify. Score. Secure.
iScoreIt is a risk intelligence platform for the teams who have to say yes or no to a stranger in under a second — and then explain that answer months later.
Verification answers a field. Risk teams need an answer.
The gap between “this PAN is valid” and “approve this applicant for ₹1.87 lakh” is where most of the cost, most of the fraud and almost all of the manual work sits. iScoreIt is built to close it. We come out of lending, not out of a generic API business — which is why the platform is opinionated about cost-aware waterfalls, decision replay and what happens when an upstream source goes down mid-journey.
Six vendors, one decision
Risk teams were stitching together a PAN provider, a bank verification provider, a bureau, a device SDK and two spreadsheets — then reconciling the answers by hand. The decision was never the hard part. Getting trustworthy inputs to it was.
Score, don't just verify
A verification API tells you a field matched. That is not a decision. We wanted a layer that collects the signals, weighs them against a policy you control, and returns something you can act on and later defend.
One contract across every check
Same auth, same error grammar, same idempotency, same webhook signature — across identity, banking, business, device, income and AML. Learn one endpoint and you have learned all of them.
Fraud intelligence from the open web
MuleNet came out of a simple observation: illegal collection operations have to publish an account to get paid. That published evidence, gathered continuously, is a fraud dataset nobody else was assembling systematically.
Four things we will not trade away.
Every score comes with the signals that produced it. If we cannot show you why, we do not ship it.
A missing signal is reported as missing. Your policy decides what that means — we never quietly substitute a default.
Where a regulated registration belongs to you, it stays with you. We are the technology layer, not a middleman on your compliance.
Auth, idempotency, versioning and audit trails are unglamorous and non-negotiable. The interesting work sits on top of them.
Built for banks, NBFCs, fintechs and marketplaces
Verification APIs
Median response
Platform uptime
UAT and live, one console
Come break it on your data.
The fastest way to evaluate us is a sandbox key and your own back-book sample.
Sandbox keys the same day · Data residency in India · 99.9% uptime
Voice agents that verify while they talk.
Twelve Indian languages. Identity confirmed mid-conversation. Recording, transcript, consent and outcome filed against the same case your policy already reads.
Pick a voice your customers won't hang up on.
Each agent is a voice, a language and a manner. Tune the pace, the formality and how hard it pushes — then keep the same one across every campaign so the relationship stays consistent.
आपकी किस्त 5 तारीख़ से बाकी है — क्या मैं अभी भुगतान लिंक भेज दूँ?Aarohi · early-bucket reminder
Code-mixed Hindi–English handled natively · the agent switches when the customer switches
Any vendor can place a call. Ours comes back with evidence.
Verifies mid-call
Identity is confirmed inside the conversation, not assumed from the dialled number.
Stops where the rules stop
Conduct rules are configuration, not training data. The agent logs the reason when it refuses.
Acts before it hangs up
The call ends with something done, not a note for someone to action tomorrow.
Dialect Listen — quality assurance on all of it, not two per cent of it
Sampled QA finds the calls you happened to pull. Listen scores every call your team makes, agent or human, for intent, promise-to-pay likelihood, dispute language, hardship signals and conduct breaches — so a supervisor argues with evidence rather than memory.
Figures illustrative, pending measured data from live deployments
The calls nobody has enough people for.
Reminders, promise-to-pay capture and a payment link before the account ages into a costlier queue.
day 1–30Inbound and campaign leads answered in seconds, intent captured, only the worthwhile ones routed to a human with full context.
inboundPeriodic reviews run as a conversation, with the DigiLocker link pushed mid-call and the document fetched before the customer hangs up.
outboundUndelivered card, cheque book or device: the agent confirms the address, updates the record and reschedules in one pass.
NDRApplications abandoned at document upload get a call that explains the missing step and completes it on the line.
recoveryBalance, statement, EMI date and dispute intake around the clock, with anything sensitive handed to a person immediately.
24×7A call is just another check on the decision endpoint.
Same authentication, same idempotency, same webhook signature as every other iScoreIt API. Name an agent, name a policy, and the outcome comes back as structured data — not a recording someone has to listen to.
Numbers checked against DND, opt-outs and the calling window before a call is placed.
Recording notice read, consent captured, mobile-to-name and one knowledge check confirmed.
Agent follows your script and guardrails, handles objections, escalates on distress.
Payment link sent, callback booked, systems updated, policy re-run if the picture changed.
Recording, diarised transcript, consent artefact, reason codes and agent version stored on the case.
Give it a hundred of your own calls.
Send a bucket you already work — a delinquency slice, an abandoned-application list, a re-KYC batch — and hear the difference against your current contact rate before you commit to anything.
Sandbox keys the same day · Bring your own trunk · Data residency in India