AI agentIntake-to-pay

AI invoice spam filtering agent

An AI invoice spam filtering agent examines the sender, the document and the content of each message and compares them with known vendors, past invoices and typical patterns.

  • People stay in control
  • Every action is logged
  • Start with a small sample
Inbound emails and attachments
Vendor domain and contact records
Stored bank details
Previous confirmed senders
AI invoice spam filtering agentPrepared for review
  • ✓Risk label with reason
  • ✓Quarantine list
  • ✓Bank-change alerts
Handed toAP specialist receives suspicious items
4inputs it reads
6steps in the walkthrough
1point where a person decides
3outputs it prepares
See it run

Watch it work

Agent Record Person
Live walkthrough
  1. 1Receive messageRecord
  2. 2Check senderAgent
  3. 3Scan contentAgent
  4. 4Score riskAgent
  5. 5Reviewer decidesPerson
  6. 6Quarantine or passRecord

Scans each email and attachment.

Compares sender domain and name with vendor records.

Looks for phishing patterns and mismatched bank details.

Marks as clean, suspicious or likely junk.

A person inspects suspicious items.

Suspicious items are held, clean ones continue.

The basics

What is an AI invoice spam filtering agent?

It scores each item for signs of trouble, such as an unknown sender posing as a known vendor, mismatched bank details or an invoice for goods nobody ordered.

Read the full explanation

It holds suspicious items in a review queue with the reasons shown. People decide what is genuine.

Where it breaks

Why this step is hard by hand

Fraudulent and unsolicited invoices are designed to look ordinary, and a busy AP team has little time to inspect every sender.

Domains and names are changed by a character.

Scammers rely on bills being paid by default.

A familiar vendor name with new account details is a classic sign.

Links and files can carry malware.

Over-strict filtering delays real invoices.

The path

How the agent does it

  1. 01Check the sender

    Compares sender address, domain and display name with vendor records and prior mail.

  2. 02Inspect the document

    Reads the invoice and looks for details that do not fit, such as unfamiliar remit-to data or layout.

  3. 03Compare to your records

    Checks whether any PO, contract or past order supports the invoice.

  4. 04Score and explain

    Rates the risk and lists the reasons in plain language.

  5. 05Hold or pass

    Passes low-risk invoices on and holds suspect ones for a person, never deleting them.

Want to see this flow on your own items?

Bring a small sample and watch Flo work through it.

Book a demo
Under the hood

Inside the work

AspectBy handWith the agent
VolumeStaff delete junk by hand every day.Obvious junk is held away from the invoice queue.
Fake invoicesLook-alike invoices get past a glance.Sender and content are checked against vendor records.
Bank detailsChanged details are noticed only by careful readers.Bank detail changes are flagged for verification.
ExplanationsWhy a message was dropped is not recorded.Each hold carries a stated reason.
False dropsReal invoices can be deleted by mistake.Held items are listed for review, not removed.
People and control

Who decides, and what to watch

What stays with people

  • ✓
    People decide what is genuineA held item is released or rejected by a human.
  • ✓
    Security teams handle threatsPhishing reports follow your security process.
  • ✓
    AP verifies vendors by a known channelNever by replying to the suspicious mail.
  • ✓
    Finance owns the rulesTeams tune sensitivity to their risk.

Mistakes to avoid

  • ×
    Paying because it looks rightFakes copy real layouts.
  • ×
    Verifying through the contact in the emailUse a known contact instead.
  • ×
    Deleting suspected spamKeep it, since it may be evidence or a false alarm.
  • ×
    Tuning the filter onceFraud patterns shift.

Not sure where invoice spam filtering fits in your process?

Talk it through with the team. We will map it to your steps and show where a person stays in control.

  • Works from a sample of your real items
  • Shows what Flo handles and what it hands over
  • No commitment to start
Rollout

Rolling it out

  1. 1Label only

    Start by labelling, with no holds, and check false calls.

  2. 2Hold junk

    Hold clear marketing and junk away from the queue.

  3. 3Add bank-change flags

    Link flags to a verification routine.

  4. 4Review monthly

    Check missed and wrongly held items and adjust the rules.

Signs you would benefit

Look-alike invoices have appearedStaff have questioned a message once or twice.
Junk takes real timePeople delete it daily.
Bank changes arrive by emailVerification is informal.
Real invoices were once lostNobody could find the deleted message.
The numbers

How to measure it

Set your own baseline first. We do not publish benchmarks without a source you can check.
Metric 1

False positive rate

False positive rate (%) =
genuine invoices held for reviewinvoices held for review× 100

A high rate means the filter is slowing real invoices. A rate that is too low may mean it is too lenient, so review misses as well.

  • Record the reason when a held item is released.
  • Track genuine invoices caught late and add what you learn to the rules.
Questions

Frequently asked questions

Quick answers to what people ask most about invoice spam filtering.

Book a demo
What is invoice spam filtering?

It is screening AP mail to catch fake invoices, phishing and unsolicited bills before they reach approval, and holding suspicious items for human review.

How is it different from invoice email triage?

Triage sorts all AP mail by purpose. Spam filtering focuses on risk and decides whether a message looks genuine at all.

Will it block real invoices?

It holds, rather than deletes, anything it is unsure about, and shows why. A person releases genuine items, and the feedback helps tune the rules.

Can it detect changed bank details?

It can flag a mismatch between bank details on an invoice and those on record. A person verifies any change using a known contact.

Try invoice spam filtering on your own data

Bring a small sample of real items. We will show what Flo handles on its own and where it hands over to your team.

  • People approve, sign and pay
  • Every action is logged
  • Start with a small sample