Drift Detection

Built for Rho

Surface slow-moving spend patterns your dashboard cannot see.

Demo by Armaan Kazi
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What this is

Rho processes every corporate card transaction, AP invoice, and bank transfer for a company in one place. Most anomaly detection tools flag large one-off transactions. Drift Detection surfaces something harder to catch: slow-moving patterns that compound over months - a SaaS category creeping up 12% month-over-month, a vendor billing inconsistently, recurring spend that nobody remembers approving.

What Rho currently shows

Rho's dashboard shows account balances and transaction history. It does not surface multi-month trends, flag gradual spend drift, or distinguish intentional growth from unnoticed cost creep.

Today - transaction list

Mar 5Figma
$760.00
Mar 12Slack
$441.00
Mar 15CloudOps Inc
$5,100.00

With Drift Detection

Mar 5Figma↑ drift detected
$760.00
Mar 12Slack
$441.00
Mar 15CloudOps Inc
$5,100.00

What changes

Spend visibility

Without

Transaction list - amounts and dates only

With

Trend analysis across 6 months per vendor

SaaS creep

Without

Invisible - looks normal month to month

With

Flagged when category grows >8% MoM

Vendor anomalies

Without

No way to spot inconsistent billing

With

Variance detected and surfaced automatically

Forgotten subscriptions

Without

Recurring charges go unnoticed indefinitely

With

Flat recurring charges with no usage correlation flagged at low severity

CFO time

Without

Manual review of every line item

With

AI surfaces only what needs attention

Data required

Without

Works with any bank

With

Uniquely possible with Rho's unified cards + AP + banking data in one place

What this demo adds

Drift Detection runs six months of synthetic transaction data through a pattern analysis engine that looks for what standard dashboards miss: compounding spend trends, inconsistent vendor billing, and flat recurring charges that nobody is watching. It surfaces each signal with severity ranking and a projected cost if left unaddressed.

Why it's better

Catches what one-off detection misses

Slow-moving patterns like SaaS creep at 12% MoM or inconsistent billing cycles are invisible to standard anomaly detection. Drift Detection finds them.

Only possible with Rho's unified data

Cards, AP, and bank transfers in one ledger means patterns can be correlated across sources. No other platform has this data advantage.

Surfaces signal, not noise

Instead of alerting on every large transaction, it ranks by severity and surfaces only what actually needs a CFO's attention.

Why This Is Different

Most spend tools show you what happened. Drift Detection shows you what's happening: the gradual shifts that compound quietly until someone looks at the annual budget and wonders where $40k went.

Try it

Six months of synthetic company transaction data. Switch scenarios to see how the detector responds.

The chart below excludes payroll. Watch the SaaS line.

Monthly spend - SaaS, Infrastructure & Misc

02k4k6k8k10kOctNovDecJanFebMarPayroll: stable ~$48k↑ +56% over 6 monthsgrowing
SaaS
Infrastructure
Misc
Stable

Payroll

$48k / mo avg

No drift detected

At current drift rates, here is where spend is heading

Solid lines = actual · Dashed lines = projected

03k6k9k12kToday →OctNovDecJanFebMarAprMayJunJulAugSep$5,257 / mo
SaaS
Infrastructure
Misc

Projected SaaS spend by Sep 2025

$5,257 / mo

vs. today

+$2,446 / month

Annualized overspend if unaddressed

$13,869 cumulative

Spend Health Score

Calculated from 6 months of transaction data

67C
SaaS Efficiency
HIGH RISK
Vendor Reliability
MEDIUM RISK
Subscription Hygiene
MEDIUM RISK
Payroll Stability
HEALTHY

Score updates automatically when new transactions are analyzed.