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The context layer
for modern fintech.

Every transaction carries context. Pay cycles, allocation context, holding posture. Neumetria turns that into signals your product or agent can read, so the moment to act, or the moment to wait, is clear.

Signal stream
Incoming
Signal
01The gap

Consumer fintech solved access.
Understanding is the open layer.

Anyone can open an account, connect their data, see their balance, and move money. The layer that reads what the behavior means, cadence, drift, posture in real time, rarely exists outside the largest institutions. Neumetria builds it.

100
Sign up
40
Complete onboarding
9
Active at D30

Illustrative. Onboarding abandonment and weak day-30 retention are well-documented across consumer fintech. The data to explain them already exists. The interpretation of what it means rarely does.

02The engine

Raw transactions. Interpreted context.
Clear signal.

01 · Input · rawTransaction
mcc: 5411
amount: 52.40
time: 2026-04-19 10:30
day: Sat
merchant: WHOLEFDS MKT #10847
02 · Interpret · contextLayered context
merchant: Whole Foods
category: Essential groceries
temporal: Sat morning
cycle: Payday +1d
cadence: Weekly rhythm
03 · Output · signalProduct-shaped
{
  signal: grocery cadence,
  rhythm: weekly,
  cycle: payday +1d,
  stability: 0.78
}
03Architecture

From signal to surface.

01
Transaction layer
Your existing stream, enriched with merchant, instrument, timing, and category.
interprets
02
Behavioral layer
Cultural, temporal, situational interpretation. Not simplified segments.
shaped to
03
Product layer
Signals shaped to the surface, whether that is an app screen, a notification, or an agent. Your product keeps the relationship.
04Where it works

One engine. Three domains.

01 · Spending
Deposits.
Cards. Transfers.
Income rhythm, capacity windows, category movement. For neobanks, card products, and retail banks.
02 · Investment
AUM.
Allocation. Tenor.
Allocation context, tenor of conviction, portfolio drift. For brokerages and wealth products.
03 · Crypto
Holdings.
Posture. Concentration.
Holding posture, concentration posture, volatility response. For exchanges and custody products.
05Use cases

Eight surfaces where
context changes the product.

Each surface is a different expression of the same engine. Different signal, different product move, different metric moved.

Ch. 05.1 Activation / Signal in · income rhythm, first-session shape

Recognize the first moment that matters.

Most fintech apps treat every new user the same. Neumetria reads the first ninety days as a pattern, not a funnel, so the product can engage only when engagement will land.

CAC paybackFunnel conversionUnit economics
FIG. 01 · INFLECTION MAP SIGNAL CONFIDENCE → D07 · FIRST DEPOSIT D24 · RECURRING RHYTHM D55 · ACTIVATION READINESS D00 D30 D60 D90
Fig. 01 Confidence builds across events. The engine surfaces readiness, the product picks the moment.
FIG. 02 · ENGAGEMENT DRIFT Expected cadence Observed cadence DRIFT DETECTED · W08 Typical churn · W15 W00 W04 W08 W12 W16 49 DAYS OF LEAD TIME
Fig. 02 Illustrative. The drift shows up in transaction cadence weeks before the app signals anything.
Ch. 05.2 Retention / Signal in · cadence, drift, posture

Read the drift before it becomes churn.

Cadence drops. Intensity shifts. Behavior drifts. These patterns show up in the stream long before a user opens the app less. The product responds with context, not reminders.

D90 retentionCohort LTVReactivation
Ch. 05.3 Personalization / Signal in · posture, temporal, environ

Segments are a convenience. Behavior is not.

Cohort averages tell the product what a group looks like on paper. Neumetria replaces that with live contextual signals, so the product can personalize without reducing the user to a persona.

ARPUCross-sell attachPromo leakage
FIG. 03 · SEGMENT DISINTEGRATION SEGMENT young_professional N = 12,340 READ AS 40 DISTINCT CONTEXTUAL STATES each axis = posture · temporal · environ
Fig. 03 Same label on the left. Forty different lives on the right. Personalization reads the right.
FIG. 04 · CLARITY IS RETAINED REVENUE RETENTION → Baseline · no cost-clarity events With cost-clarity surfacing M12 RETENTION DELTA M00 M03 M06 M09 M12 INPUT · FX MARKUP FLAGGED
Fig. 04 Illustrative model, not a measured result. The engine feeds the moments. The operator's P&L measures the delta.
Ch. 05.4 Trust / Signal in · cost-exposure events  ·  Signal out · operator KPIs

Products that show, not sell.

Transparency isn't a brand posture. It's a retention instrument. Operators who surface cost-exposure moments renew longer, dispute less, and earn regulatory goodwill the market prices in. Neumetria feeds the product the moments worth showing; your product does the showing; the compounding shows up on the P&L.

Renewal liftDispute costRegulatory posture
Ch. 05.5 Capacity growth / Signal in · inflow timing, allocation context, holding posture

One engine. Three balance sheets.

Deposits at banks. AUM at brokerages. Holdings at exchanges. The same inflow context, expressed across three surfaces, at the moment capacity actually becomes available.

Deposit growthAUM growthHolding growth
FIG. 05 · THREE SURFACES, ONE SIGNAL CAPACITY WINDOW · 0.78 01 · DEPOSITS + $1,240 / 30d cohort 02 · AUM + $3,860 / 30d cohort 03 · HOLDINGS + $2,180 / 30d cohort
Fig. 05 One inflow signal, three product surfaces. Growth is where capacity lands, not where it originates.
FIG. 06 · CASH FLOW VIEW INCOME RHYTHM W1 W4 W8 income_rhythm biweekly income_stability 0.87
Fig. 06 Income regularity and capacity window, before origination.
Ch. 05.6 Qualification / Signal in · income rhythm, recurring load, capacity window

Read cash flow before you commit.

The bureau file is fixed. Cash flow is live. Neumetria reads income rhythm, recurring load, and spending stability before origination so lenders can underwrite with context alongside credit history.

Approval qualityThin-file coverageContext coverage rate
Ch. 05.7 Engagement / Signal in · first-use, utilization, repayment rhythm

The file is static. The borrower is not.

The credit file is fixed at approval. The behavior on the line is not. Neumetria reads the post-origination stream so lending products can engage borrowers at the moments the line actually matters.

First-use liftPrimary-line shareReactivation
FIG. 07 · FILE VS STREAM FILE VIEW · AT APPROVAL Static. segment: near_prime fico: 680 dti: 0.34 status: approved STREAM VIEW · NEUMETRIA Current. first_use: d+3 · active utilization: 0.42 · rising recurring: on-time debt_service: 0.22 drift: stable
Fig. 07 Same borrower. Two views. The product can only engage the one on the right.
FIG. 08 · LIQUIDITY WINDOW BALANCE OPTIMAL WINDOW COMPRESSION PAYDAY intelligent retry D00 D07 D14
Fig. 08 Payday is the signal. The engine aligns payment requests to the window, not the calendar.
Ch. 05.8 Payments / Signal in · liquidity trend, payroll cycle, merchant history

Payments that know the window.

Open Banking payments carry none of the behavioral context card networks built over decades. Neumetria routes confidence, timing, and legitimacy into the payment layer before a request is made.

Pay-by-Bank conversionFailed payment recoveryDispute reduction
07Signal vocabulary

The language your product reads.

income rhythmcapacity windowsspend cadencerecurring loadengagement driftcategory movementtemporal contextliquidity trendallocation contextholding postureconcentration postureconfidence

A partial view. Signals return synchronously, versioned, with interpretation metadata.

08Posture

Clear about the line.

Neumetria is infrastructure for fintech products. It does not make financial decisions. Your product does.

What Neumetria is not

  • × A financial advisor
  • × A robo-advisor
  • × A credit decisioning engine
  • × An investment platform
  • × A tool that advises, approves, or denies
  • × A payment processor or payment initiator

What Neumetria is

  • A behavioral intelligence layer
  • B2B infrastructure for fintech products
  • A reader of transaction streams in context
  • A source of product-shaped signals
  • A layer under your decisions, not instead of them
09Integrate

A focused surface. Synchronous where it matters.

One endpoint for send. One endpoint for read. Light-weight context returns in-line. Deeper profiles compute in the background and are fetched when the product needs them.

POST POST /v1/transactions
Your product streams transactions in. Minimal payload: amount, merchant hint, timestamp, direction.
→ synchronous response
Classifications, behaviors, and context tags return in-line. Latency budget under 200ms at p99.
· async processing
Skill scoring, trait geometry, lifestyle patterns, recurring detection, rhythm cadence, and allocation / holding-tenor / stablecoin-posture reads compute in the background within minutes. One engine across spending, investment, and crypto.
GET GET /v1/actors/{id}/profile
Full behavioral profile returned on demand. Versioned, timestamped, inspectable down to the field.

What integration looks like.

Setup
2 to 4 weeks from first call to first live signal in a staging environment.
Security
SOC 2, ISO 27001, and GDPR compliance in progress. Data residency and PII handling agreed before any integration begins.
Pricing
Annual contracts, scoped to the surfaces you integrate. We size with you once we understand the deployment.
Support
We work directly with your engineering lead during integration. No procurement-scale SDK tour.
GET /v1/actors/{id}/profile
// response
{
  "actor_id": "a_4f2a9e...",
  "as_of": "2026-04-18T09:41:00Z",
  "window": "90d",
  "context": {
    "spending": {
      "cadence": "biweekly_dining",
      "stability": 0.91,
      "temporal": "post-payday"
    },
    "investment": {
      "contribution_cadence": "monthly_recurring",
      "holding_posture": "lengthening",
      "allocation_shape": "equity_weighted"
    },
    "crypto": {
      "stablecoin posture": 0.62,
      "hold_duration": "medium"
    },
    "behaviors": [
      "leisure_dining",
      "disciplined_accumulation",
      "stablecoin holding"
    ]
  },
  "confidence": 0.92
}
Get in touch

Building in Fintech?
Let's Talk.

Patent pending. Built for regulated environments. Designed to embed via API or MCP, into your product or your agent.