Guide-yakabatana mibvunzo · Pakati Nhanho

AI Fraud Detection Quiz

Test fraud class imbalance, false positives, network modeling, velocity signals, and changing fraud patterns. Check evaluation scope.

Nzira dzekutungamira dzinoenderanaAI Kubiridzira Kuonekwa
Mubvunzo 1 ye 8

Sei mitemo yakagadziriswa yega (semuenzaniso, 'mutero we block inodarika $5,000') kazhinji isingakwane pakubiridzira?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  1. Sei mitemo yakagadziriswa yega (semuenzaniso, 'mutero we block inodarika $5,000') kazhinji isingakwane pakubiridzira?
    • Kubiridzira kune mhandu uye kunogara kuchichinja, saka mitemo inoenda kare
    • Dzinodhura kunyora
    • Mabhangi haabvumirwi kushandisa mitemo
    • Mitemo inoshanda pakupera kwevhiki chete
  2. 'Kusaenzana kwekirasi' mukuonekwa kwehutsotsi kunoreva kuti:
    • Kune mabhanga akawandisa
    • Kutengeserana kwechitsotsi chikamu chidiki chezvese zvekutengeserana
    • Vatengi vese vanoshandisa mari yakafanana
    • Data inochengetwa mukirasi faira isiriyo
  3. A 'false positive' mukuona hutsotsi zvinoreva:
    • Chitsotsi chaicho chakapotswa
    • Sisitimu yaparara
    • Kutengeserana kuri pamutemo kwakanzi ndihwo hutsotsi
    • Mhosva yakapetwa kaviri yaitika
  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. Ndeipi chiratidzo muenzaniso we 'velocity' mukutarisisa kutengeserana?
    • Mhosva dzakawanda dzinoitika mukati memaminitsi mashoma
    • Bhavudhe remutengi
    • Ruvara rwekadhi
    • Chiratidzo chebhangi
  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