1st TPRM Master Class by International TPRM Alliance

RTInternationalTPRMAlliance

1st TPRM Master Class

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Category: 1st-TPRMMasterclass

1. AI helps identify risks earlier by:

A. Reducing data inputs

B. Eliminating alerts

C. Ignoring historical data

D. Recognizing patterns and anomalies

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Category: 1st-TPRMMasterclass

2. Which of the following best describes the role of AI-based scoring models in Third-Party Risk Management (TPRM)?

A. They ignore real-time risk inputs

B. They replace all existing risk frameworks

C. They are always static in nature

D. They provide dynamic and continuous risk ratings

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Category: 1st-TPRMMasterclass

3. Which best describes AI-driven continuous monitoring in TPRM?

A. Continuous automated risk scoring

B. Continuous adaptive risk scoring

C. Periodic automated risk scoring

D. Continuous adaptive and contextual risk scoring

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4. AI-driven monitoring typically reduces

A. Human workload

B. Operational efficiency

C. Risk visibility

D. Data availability

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5. AI reduces third-party risk exposure primarily through

A. Ignoring low-risk vendors

B. Increasing manual reviews

C. Predicting and mitigating risks proactively

D. Eliminating vendors

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Category: 1st-TPRMMasterclass

6. AI contributes to continuous monitoring by

A. Static rule enforcement only

B. Eliminating human oversight

C. Learning from new data over time

D. Ignoring feedback

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Category: 1st-TPRMMasterclass

7. Continuous monitoring using AI primarily supports

A. Proactive risk management

B. No risk management

C. Reactive risk management

D. Static risk assessments

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Category: 1st-TPRMMasterclass

8. Which combination best represents an effective AI-driven TPRM system?

A. Dynamic models + real-time data + human oversight

B. Manual reviews + limited data

C. Static rules + periodic audits

D. Automated alerts without validation

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Category: 1st-TPRMMasterclass

9. AI enhances third-party risk visibility by

A. Delaying reporting

B. Removing dashboards

C. Integrating multiple data streams

D. Limiting external data sources

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Category: 1st-TPRMMasterclass

10. What is the primary goal of using AI in continuous TPRM monitoring?

A. Eliminate all third-party risks

B. Continuously detect and assess third-party risks

C. Automate periodic audits

D. Replace human risk managers

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Category: 1st-TPRMMasterclass

11. Continuous AI monitoring helps organizations

A. Eliminate all uncertainties

B. React slower to risks

C. Avoid compliance

D. Identify emerging threats early

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Category: 1st-TPRMMasterclass

12. Which type of data is commonly analyzed by AI in TPRM?

A. Only internal company data

B. Structured and unstructured data

C. Only legal contracts

D. Only financial statements

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13. The key differentiator between AI and rule-based systems in TPRM is

A. Learning capability

B. Data storage

C. Automation

D. Predefined logic

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14. Continuous monitoring differs from traditional TPRM because it

A. Is manual

B. Is ongoing and automated

C. Focuses only on compliance

D. Happens once a year

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Category: 1st-TPRMMasterclass

15. AI improves TPRM monitoring mainly by

A. Increasing paperwork

B. Slowing down risk detection

C. Reducing data usage

D. Providing real-time insights

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16. What is a key benefit of AI in TPRM?

A. Faster decision-making

B. Less data accuracy

C. Reduced transparency

D. Manual intervention at every step

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Category: 18th RT-International TPRM Alliance

Which topics would you like to see covered in future roundtables or masterclasses?
e.g.,

17. Third-Party Cyber Risk & Continuous Monitoring
AI Risk in Vendor Ecosystems
Cloud & SaaS Risk Management
Regulatory Compliance (e.g., outsourcing, data protection)
Fourth-Party / Concentration Risk
Incident & Breach Management involving vendors
Other (please specify): __________

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18. AI models in TPRM are most effective when

A. No training data is required

B. Data is limited

C. Data is diverse and high-quality

D. Only historical data is used

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Category: 1st-TPRMMasterclass

19. Which scenario best demonstrates AI’s advantage in TPRM?

A. Annual vendor review

B. Static risk scoring

C. Real-time detection of vendor breach signals

D. Manual compliance checklist

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Category: 1st-TPRMMasterclass

20. False positives in AI monitoring refer to

A. Data breaches

B. Incorrect risk alerts

C. Correct detections

D. Missed risks

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Category: 18th RT-International TPRM Alliance

How would you rate the overall experience of the event?

21. Highly insightful and engaging
Informative and valuable
Average / satisfactory
Lengthy but useful
Too long and less engaging
Not relevant / could be improved

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Category: 1st-TPRMMasterclass

22. Which AI technique is commonly used for anomaly detection?

A. Sorting

B. Regression

C. Clustering

D. Encryption

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Category: 1st-TPRMMasterclass

23. Which option most accurately differentiates “continuous monitoring” from “continuous assessment”?

A. Monitoring = data collection; Assessment = analysis and judgment

B. Both are identical

C. Monitoring = manual; Assessment = automated

D. Monitoring = evaluation; Assessment = observation

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Category: 18th RT-International TPRM Alliance

24. Please share your feedback on the event

What did you find most valuable?
What could be improved?
Any suggestions for future sessions?

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Category: 1st-TPRMMasterclass

25. One limitation of AI in TPRM is

A. Inability to process data

B. Over-reliance on accurate data

C. No scalability

D. Lack of automation

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Category: 1st-TPRMMasterclass

26. Which risk type can AI detect in TPRM?

A. Reputational risk

B. Financial risk

C. All (Cyber + Financial + Reputational)

D. Cyber risk

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Category: 1st-TPRMMasterclass

27. In AI-driven TPRM, “contextual risk analysis” refers to

A. Assessing risk considering environment and dependencies

B. Static scoring models

C. Ignoring external factors

D. Evaluating risk based only on internal metrics

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Category: 1st-TPRMMasterclass

28. What is the biggest challenge in AI-driven continuous monitoring?

A. Data quality and bias

B. Lack of vendors

C. Lack of algorithms

D. No computing power

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