Top 50 fraud detection Interview Questions
The most frequently asked fraud detection questions across all roles and companies, ranked by real interview frequency. Updated daily.
Rewrite a fraud dashboard query so PostgreSQL can use date and entity indexes instead of scanning tens of millions of risk reports.
LexisNexis Risk Solutions
ByteDance
TapadUse LAG and conditional aggregation to identify accounts with repeated transactions occurring within short time intervals.
LyftCalculate weighted fraud-risk scores for Uber users using selected metrics and aggregated SQL results.
UberFlag suspicious Robinhood transactions using account-level amount anomalies and hourly transaction velocity.
RobinhoodUse a time-based window to identify users with more than three failed attempts within five minutes.
ByteDance
ChimeUse PostgreSQL window functions and time filtering to find nearby duplicate charges by account and amount.
American ExpressCompare financial crime detection architectures using joined run metrics, aggregates, NULL handling, and ordered performance results.
DeloitteEvaluate fraud model thresholds using CASE logic, aggregations, and window ranking for precision and recall.
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