Guide-linked quiz · Medium Level

AI Cash Application in Accounts Receivable Quiz

Tests remittance matching, subset-sum payment combinations and late-payment prediction used in AI cash application for receivables teams.

Question 1 of 8

Why is cash application often difficult even when the bank shows exactly how much was received?

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Answers and explanations appear as you take the quiz.

  1. Why is cash application often difficult even when the bank shows exactly how much was received?
    • Banks do not send payment files to companies
    • Remittance details often arrive separately from the payment, by email, portal or EDI
    • Invoices usually lack invoice numbers
    • ERP systems cannot record partial payments
  2. A single payment with no remittance must be matched against many open invoices. What kind of search does this require?
    • Sorting invoices by due date only
    • Optical character recognition of the bank file
    • Linear regression on invoice amounts
    • A subset-sum search for open invoices that add up to the payment
  3. A customer deducts $1,200 for damaged goods. What does the guide describe as the better practice?
    • Leave the entire payment unapplied
    • Write off the $1,200 immediately
    • Apply the amount received and open a deduction case with a reason code
    • Return the payment to the customer
  4. Why can a high auto-match rate be misleading?
    • Wrong matches post silently and hide errors in customer balances
    • Automatic matching is not allowed by auditors
    • It increases days sales outstanding
    • Banks charge a fee for each match
  5. Why does the guide suggest survival analysis for late-payment prediction?
    • It requires no historical data
    • It accounts for invoices still open, whose final payment date is unknown
    • It guarantees accurate predictions
    • It only works for check payments
  6. Which formats does the guide name for bank statement data used in cash application?
    • BAI2 and ISO 20022 camt.053
    • EDI 850 purchase orders
    • XBRL financial filings
    • PDF/A archive files
  7. A wire arrives under a parent company's name. How does an AI system identify the right customer account?
    • It rejects the payment until remittance arrives
    • It applies it to the customer with the largest balance
    • It uses learned history linking payer names and bank accounts to customer accounts
    • It posts the amount directly to revenue
  8. How does the guide say late-payment predictions should be used?
    • To cut off customer credit automatically
    • To prioritize collections outreach and inform cash forecasts, with people making credit decisions
    • To change invoice prices after issue
    • To replace remittance advice

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