Quiz połączony z przewodnikiem · Średni Poziom

Quiz AI w windykacji i obsłudze kredytów

Testuje założenia dotyczące częstotliwości połączeń określone w rozporządzeniu F, kogo obejmuje FDCPA oraz dlaczego mechanizmy zgodności i wykrywanie trudności opierają się na modelach gromadzenia danych AI.

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Pytanie 1 z 8

Under Regulation F, which pattern of calls creates a presumption of a violation?

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Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.

  1. Under Regulation F, which pattern of calls creates a presumption of a violation?
    • More than three calls in one month about a debt
    • More than seven telephone calls within seven days about a particular debt
    • Any call made after 5 p.m. on a weekday
    • Two calls on the same day to different phone numbers
  2. Which party is generally outside the FDCPA but still subject to prohibitions on unfair, deceptive or abusive practices?
    • A third-party collection agency
    • A debt buyer that purchased charged-off accounts
    • An original creditor collecting its own debts
    • A law firm regularly collecting consumer debts
  3. What does Regulation F require when collectors contact consumers by email or text?
    • A clear and simple way to opt out of those communications
    • A handwritten signature from the collector
    • Approval from a court before each message
    • That messages be sent only on weekends
  4. What did the FCC rule in February 2024 about AI-generated voices?
    • They are exempt from all telephone rules
    • They count as artificial voices under the Telephone Consumer Protection Act
    • They may be used only by original creditors
    • They must be disclosed in the validation notice
  5. What does the guide mean by separating optimization from permission in collection systems?
    • Models choose which borrowers to sue, and lawyers approve
    • A model may rank actions, but a deterministic compliance engine must approve each one before execution
    • Borrowers must give permission before any model scores them
    • Optimization runs only on accounts that have granted consent
  6. Why is a single source of truth for contact history important?
    • It lowers data storage costs
    • Counts split across a dialer, email platform and outside agency can cause frequency limits to be exceeded
    • It is needed to calculate interest
    • It lets the model contact borrowers more often
  7. Why should hardship classifiers be tuned for high recall?
    • Missing a distressed borrower is costlier than an unnecessary handoff to a human
    • High recall makes the model run faster
    • Regulation F specifies a recall target
    • It reduces the number of payment plans offered
  8. Why does the guide say models optimized only for dollars collected are risky?
    • They cannot process payments
    • They may push toward aggressive contact or target people least able to push back
    • They always violate the validation notice rule
    • They require original creditors to register as collectors