Preview Questions Fraud Analyst | Role Specific Skill

Question 1: What role does data visualization play in presenting fraud findings to non-technical stakeholders?

Which action should you take?

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Providing a detailed audit trail of all fraud activities

Making complex data more accessible and understandable

Generating automated reports for fraud analysis

Making detailed statistical analysis less transparent

Question 2: What is the primary role of graph analytics in fraud detection?

Which action should you take?

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Identifying connections between fraud entities

Predicting customer preferences

Automating report generation

Encrypting transaction data

Question 3: Which of the following is a primary benefit of using anomaly detection methods in fraud detection?

Which action should you take?

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They require minimal data for training

They reduce the computational complexity of fraud detection models

They ensure higher accuracy in fraud detection

They can identify unknown fraud patterns that were not previously seen

Question 4: Which regulatory framework mandates fraud detection practices in BFSI?

Which action should you take?

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PCI DSS

GDPR

Basel II

SOC 2

Question 5: In fraud detection, how does anomaly detection differ from traditional rule-based systems?

Which action should you take?

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Rule-based systems detect known fraud types, while anomaly detection handles only unknown fraud

Anomaly detection requires manual input, while rule-based systems are fully automated

Anomaly detection looks for patterns that deviate from normal behavior, whereas rule-based systems only apply predefined rules

Rule-based systems use machine learning, while anomaly detection relies on statistical methods

Question 6: What is the main advantage of using a decision tree model in fraud detection?

Which action should you take?

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It can categorize transactions as fraudulent or legitimate

It requires less data to train than other models

It can only identify low-value fraudulent transactions

It only works with historical fraud data