Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Kugundua Ulaghai wa AI

Jaribu usawa wa darasa la ulaghai, matokeo chanya, muundo wa mtandao, ishara za kasi na kubadilisha mifumo ya ulaghai. Angalia wigo wa tathmini.

Njia za mwongozo zinazohusianaUtambuzi wa Udanganyifu wa AI
Swali 1 ya 8

Kwa nini sheria maalum pekee (k.m., 'ada za kuzuia zaidi ya $5,000') mara nyingi hazitoshi kwa ulaghai?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. Kwa nini sheria maalum pekee (k.m., 'ada za kuzuia zaidi ya $5,000') mara nyingi hazitoshi kwa ulaghai?
    • Ulaghai ni kinyume na hubadilika mara kwa mara, kwa hivyo sheria hupotea
    • Wao ni ghali sana kuandika
    • Benki haziruhusiwi kutumia sheria
    • Sheria zinafanya kazi wikendi pekee
  2. 'Usawazishaji wa darasa' katika ugunduzi wa ulaghai unarejelea ukweli kwamba:
    • Kuna benki nyingi sana
    • Shughuli za ulaghai ni sehemu ndogo ya shughuli zote
    • Wateja wote hutumia kiasi sawa
    • Data imehifadhiwa katika faili isiyo sahihi ya darasa
  3. 'Chanya ya uwongo' katika utambuzi wa ulaghai inamaanisha:
    • Ulaghai wa kweli ulikosekana
    • Mfumo ulianguka
    • Muamala halali uliripotiwa kimakosa kama ulaghai
    • Gharama iliyorudiwa ilitokea
  4. What challenge can neighbor-based message propagation create for a fraud GNN?
    • It guarantees every linked account is fraudulent
    • It removes all concept drift from the data
    • It prevents investigators from reviewing transactions
    • Neighbor and hub effects can amplify class-imbalance problems
  5. Ni ishara gani ni mfano wa 'kasi' katika ufuatiliaji wa shughuli?
    • Gharama nyingi hutokea ndani ya dakika chache
    • Siku ya kuzaliwa ya mteja
    • Rangi ya kadi
    • Nembo ya benki
  6. What fraud typology did FinCEN’s 2024 deepfake alert describe?
    • Deepfakes that automatically reverse settled transactions
    • Deepfake media and fraudulent identity documents used to evade identity verification or authentication
    • A rule requiring banks to reject every voice call
    • Synthetic identities that prove a customer committed a crime
  7. Why can accuracy be misleading for a highly imbalanced fraud dataset?
    • Accuracy is always equal to recall
    • Fraud labels are never used
    • A model can score high accuracy by predicting the majority legitimate class while missing fraud
    • The test set must contain no legitimate transactions
  8. What is one reason a graph model can help identify linked fraud patterns?
    • It removes the need for labels or investigation
    • It proves that connected accounts are criminal
    • It guarantees real-time detection
    • It can represent relationships among accounts, transactions, or devices