Fraud & credit risk intelligence · India

See intent, not just identity.

Shruhani Technologies builds real-time risk intelligence for Indian banks, NBFCs, and lenders. We read the digital and behavioural signals around every applicant and transaction, so your team approves genuine customers faster and stops fraud before money moves.

Signal → Score → DecisionReal-time
Device intelligence Digital footprint Location signals Behaviour Image / KYC SMS activity RISK SCORE 0.12 LOW RISK Approve Review Decline
The gap

Documents are real. Intent often isn't. Today's checks confirm who someone claims to be. They rarely answer why an account is really being opened.

Mule accounts pass KYC

The Aadhaar is genuine, the PAN is genuine, the person is genuine. The fraud sits in what the account is used for, and document checks have no way to see it.

Bureau files run thin

New-to-credit borrowers, gig workers, and young professionals carry little or no bureau history. A backward-looking score cannot separate a good thin-file applicant from a fabricated one.

Fraud rings cycle devices and SIMs

Organised rings reuse a small set of devices across hundreds of applications, cycle SIMs, and lean on residential proxies that look like ordinary home broadband.

IP reputation has aged out

With carrier-grade NAT across Indian ISPs, thousands of users share a single public IP. Risk has to be read from the device and the behaviour, not the address.

What we do

One intelligence layer across the customer lifecycle

Shruhani sits on top of your existing fraud, KYC, and underwriting stack and adds the signal layer those systems structurally miss. No rip-and-replace.

Onboarding intelligence

Score every applicant in real time from device, digital footprint, location, and image signals, before disbursal. Green-channel genuine customers, flag the rest.

Credit risk for thin files

Alternate-data signals for new-to-credit and thin-file segments where bureau coverage is limited, so you can widen approvals without widening default.

Fraud & mule detection

Surface coordinated rings and mule accounts that clear document checks, using persistent device signals and network-level connections between accounts.

Monitoring, AML & EDD

Continuous post-onboarding monitoring and case workflows built for Indian regulatory reporting, with audit trails your team can stand behind.

How it works

From raw signal to a decision your stack can act on

01 / Signal

Capture

Collect device, phone, email, location, behaviour, and image signals through a simple API or a lightweight SDK. Most modules need no app-side change.

02 / Score

Interpret

Models tuned to Indian patterns turn raw signals into risk scores and explainable flags, calibrated to your portfolio rather than industry averages.

03 / Decision

Act

Scores feed straight into your onboarding, fraud, and underwriting systems. Approve, review, or decline, with the evidence behind every call.

Who it's for

Built for India's regulated lenders and digital platforms

01

Banks & SFBs

Onboarding, mule detection, and EDD workflows for regulated banks.

02

NBFCs & lenders

Thin-file underwriting and application-fraud control for digital lending.

03

Fintechs

Real-time risk scoring for high-volume onboarding and transactions.

04

Marketplaces

Trust scoring, fake-profile detection, and promo-abuse prevention.

Security & compliance

Designed for Indian data and Indian regulation

Shruhani is built around the requirements Indian financial institutions answer to, with deployment options that fit your data-residency needs.

Deployment: cloud, on-premise, or hybrid. Encryption in transit and at rest.

DPDP Act 2023 RBI KYC Master Direction PMLA / FIU-IND Role-based access Audit trails Data residency in India
Get started

Bring intent into your risk decisions.

Tell us about your onboarding and fraud challenges, and we'll walk you through how Shruhani fits your stack.