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Fintech AR automation platform

B2B payments platform on invoice aging anomalies

Predictive outreach reduces DSO by 35 days on average

Reply rate
25%47%
Improved

How it works

The signal-to-meeting workflow

1
Sourcing

Trade credit data + AR aging reports

Aggregate anonymized ledger signals from credit bureaus and data partners.

2
Pre-process

Normalize invoice terms

Standardize invoice durations and identify aging outliers.

3
Triggers

2+ large invoices > 45 days overdue

Fires when anomaly pattern repeats for multiple customers.

4
AI Research

Root cause classification

NLP parses remittance notes and supplier statements to infer cause (cashflow, disputes, process).

5
Qualification

Mid-market revenue 50–500M and AR team < 10

High-fit if under-resourced AR department and chronic delays.

6
Activation

Payment workflow demo + cost recovery projection

Tailored outreach showing potential DSO improvement and ROI forecast.

Deep dive

Customer type

AR automation SaaS tackling late payments in manufacturing and distribution.

Its differentiator is anomaly-based detection that signals friction before CFOs see it.

How targets are sourced

Credit bureau and AR ledger data streams highlight firms with growing aging buckets.

Triggers

Two or more invoices greater than 45 days overdue in the same 60-day window.

Qualification

AI classifies root causes from remittance text and internal patterns, weighting recurrence and scale.

Success metrics

Reply rate doubled to 47%, win rate 64%, average DSO reduced by 35 days, producing measurable ROI.

Ready to map your market?

You will speak with a market engineer, review the signals and workflows that fit your market, and leave with concrete next steps.

Book a Strategy Call