An AffluenceQ score out of 100 and 40+ attributes — locality, credit depth, assets, investments, digital behaviour — from the one field every lead form already captures.
Watch the profile assemble on the right — score, signal families and attributes.
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~180 ms
Affluent, asset-owning, digitally active, investment-ready, self-employed profile in a strong locality.
* Illustrative only. The figures above are a graphical representation of what the API returns, not data about any real person or number.
Most acquisition teams rank leads by source or recency. That puts a salaried first-jobber and a business owner with two demat accounts in the same queue. Affluency Bundle sorts them before anyone picks up the phone.
Results from client pilots, 2025–26. Outcomes vary with lead source and product.
AffluenceQ is a weighted roll-up of eight signal families. The headline number sorts your queue; the buckets underneath explain it; the attributes drive the conversation.
Your headline. Sort on it, threshold on it, or cut it into premium, mass-affluent and broad cohorts.
Each contributes a capped share of the total, so no single family can carry a score on its own.
Bands and flags — house owner, demat present, credit-limit band — for routing and for the pitch.
NA means not observed, never negative. Every field says whether it was seen, so nothing is inferred silently.
Pincode affluence band, dwelling type, age band, household stage.
Credit-limit band, utilisation, product mix, tenure of the oldest line.
Demat presence, mutual-fund activity, insurance depth beyond the mandatory.
App breadth, transacting intensity, premium-service presence.
House and vehicle ownership, home-loan band, registered addresses.
Income continuity signals, address and employment tenure.
Occupation type and CIN/DIN linkage — flags founders and business owners.
Number age, telco status and reachability, so a good score is also a callable one.
Family maxima are capped independently; the published AffluenceQ is a weighted roll-up, not a sum. Exact weights are shared under NDA during integration.
One endpoint, one input field. Here's the journey your product manager implements, end to end.
From your CRM, LOS or lead form. Single call or batch file.
POST /v1/affluencyConsented, publicly available sources stitched into one profile.
~180 msAQ 0–100 is your headline. Sort, threshold or bucket on it.
"aq": 90Eight signal families show why the score is what it is.
"locality": 25Attributes drive product fit, RM assignment and the pitch.
"occupation": "self_employed"{
"aq": 90,
"band": "premium",
"buckets": {
"locality_demographics": 25,
"credit_profile": 14,
"investment_footprint": 14,
"digital_consumption": 14,
"asset_ownership": 13,
"financial_stability": 10,
"business_signal": 5,
"contactability": 21
},
"attributes": {
"house_owner": true,
"car_owner": true,
"cc_limit_band": "high",
"utilisation_pct": 39,
"demat": "observed",
"mutual_funds": "observed",
"occupation": "self_employed",
"age_band": "31-35",
"home_loan_band": "NA"
},
"observed_fields": 41,
"na_fields": 6,
"billed_calls": 1
}
Illustrative payload. Field names are stable across versions; new attributes are additive.
Sort inbound and purchased leads by AQ, send 80+ to a premium desk and let mass offers run on the rest. Credit-limit band and utilisation give the desk a talking point before the call connects.
Demat presence, mutual-fund activity and investment footprint flag people already investing elsewhere. Route them to RMs with a wealth conversation instead of a generic SIP nudge.
House and car ownership, home-loan band and locality affluence indicate the protection gap a household can afford to close. Lead with the right sum assured the first time.
Segment on AQ and bucket mix, then build lookalikes from locality, investment and digital combinations. Digital footprint tells you who converts self-serve and who needs a call.
Results are illustrative, drawn from pilot configurations. Outcomes vary with lead source and product.
Every score arrives with the eight buckets that produced it. Compliance and product can see exactly why a lead ranks where it does.
Bands, not rupee claims. NA means not observed, never negative. Inverse fields like utilisation are handled so nobody misreads them.
A mobile number is the one thing every lead form already captures. No PAN, no consent-heavy bureau pull to get started.
Score a two-million-row base overnight, or a single inbound lead while the form is still open.
Occupation and CIN linkage flag founders and business owners so SME propositions reach the right desk.
One ProfileX key, one bill, one audit trail. Consent tokens from Blutic attach to every enrichment call.
"We were dialling 90 leads to get one premium-card conversation. With AQ on the agent screen we're at 55, and the desk knows the credit-limit band before they say hello."
"Our base had thousands of people with demat accounts and mutual funds elsewhere. We didn't know. One batch run and the RM team had a warm list they could actually work."
"What sold it to compliance was the explanation layer. Score, then buckets, then fields. Nobody has to trust a number they can't see behind."
Testimonials shown are illustrative placeholders pending client approval.
Publicly available and consented databases, stitched against the mobile number. No bureau pull, no PAN required, and nothing that needs the individual to complete a journey first.
No. AffluenceQ measures affluence and product fit for prioritisation. It is not a creditworthiness measure and must not be used as one in an underwriting decision.
You get a low observed-field count and NA on the fields we couldn't see, not a low score by default. Treat a sparse profile as unknown, not as negative.
Sources refresh on their own cadence, from daily to quarterly. Each response carries the observation window so you can decide what is fresh enough for your use.
Yes. Batch a CSV of numbers and get scored rows back, typically overnight for a few million. The same fields come back as the real-time API.
Per successful enrichment, with volume tiers. It sits on your existing ProfileX contract if you have one, or stands alone if you don't.
Consent references attach to every call and are enforced before any source is queried, the same way KYC Orchestration handles them. Blutic, Neokred's DPDP consent manager, integrates natively.
Yes. The attribute block is available on its own if you'd rather run your own model on top and use ProfileX purely for enrichment.
In 30 minutes we'll run a slice of your lead list, walk your product manager through the integration and the reading rules, and show you the cohort split you'd get tomorrow.