1st TPRM Master Class by International TPRM Alliance

RTInternationalTPRMAlliance

1st TPRM Master Class

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Category: 1st-TPRMMasterclass

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

A. No computing power

B. Lack of algorithms

C. Lack of vendors

D. Data quality and bias

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2. AI-driven monitoring typically reduces

A. Human workload

B. Risk visibility

C. Data availability

D. Operational efficiency

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

A. Automated alerts without validation

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

C. Manual reviews + limited data

D. Static rules + periodic audits

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4. AI helps identify risks earlier by:

A. Recognizing patterns and anomalies

B. Eliminating alerts

C. Reducing data inputs

D. Ignoring historical data

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Category: 18th RT-International TPRM Alliance

How would you rate the overall experience of the event?

5. 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

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

A. Automate periodic audits

B. Continuously detect and assess third-party risks

C. Replace human risk managers

D. Eliminate all third-party risks

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Category: 1st-TPRMMasterclass

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

A. Only financial statements

B. Only internal company data

C. Structured and unstructured data

D. Only legal contracts

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Category: 18th RT-International TPRM Alliance

8. 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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9. False positives in AI monitoring refer to

A. Data breaches

B. Correct detections

C. Missed risks

D. Incorrect risk alerts

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

A. Regression

B. Encryption

C. Clustering

D. Sorting

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11. 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

12. 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 provide dynamic and continuous risk ratings

D. They are always static in nature

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13. Which risk type can AI detect in TPRM?

A. Financial risk

B. Cyber risk

C. All (Cyber + Financial + Reputational)

D. Reputational risk

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14. AI enhances third-party risk visibility by

A. Limiting external data sources

B. Removing dashboards

C. Delaying reporting

D. Integrating multiple data streams

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Category: 1st-TPRMMasterclass

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

A. Predefined logic

B. Data storage

C. Automation

D. Learning capability

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16. Continuous monitoring using AI primarily supports

A. Proactive risk management

B. Static risk assessments

C. No risk management

D. Reactive risk management

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

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

B. Monitoring = manual; Assessment = automated

C. Both are identical

D. Monitoring = evaluation; Assessment = observation

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18. Continuous AI monitoring helps organizations

A. Eliminate all uncertainties

B. React slower to risks

C. Identify emerging threats early

D. Avoid compliance

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Category: 1st-TPRMMasterclass

19. AI improves TPRM monitoring mainly by

A. Reducing data usage

B. Increasing paperwork

C. Slowing down risk detection

D. Providing real-time insights

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Category: 1st-TPRMMasterclass

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

A. Continuous adaptive risk scoring

B. Continuous automated risk scoring

C. Periodic automated risk scoring

D. Continuous adaptive and contextual risk scoring

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Category: 1st-TPRMMasterclass

21. AI contributes to continuous monitoring by

A. Static rule enforcement only

B. Eliminating human oversight

C. Ignoring feedback

D. Learning from new data over time

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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.,

22. 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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Category: 1st-TPRMMasterclass

23. AI reduces third-party risk exposure primarily through

A. Eliminating vendors

B. Increasing manual reviews

C. Ignoring low-risk vendors

D. Predicting and mitigating risks proactively

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Category: 1st-TPRMMasterclass

24. Continuous monitoring differs from traditional TPRM because it

A. Happens once a year

B. Is manual

C. Is ongoing and automated

D. Focuses only on compliance

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Category: 1st-TPRMMasterclass

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

A. Reduced transparency

B. Faster decision-making

C. Less data accuracy

D. Manual intervention at every step

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Category: 1st-TPRMMasterclass

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

A. Static risk scoring

B. Annual vendor review

C. Real-time detection of vendor breach signals

D. Manual compliance checklist

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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. Ignoring external factors

C. Static scoring models

D. Evaluating risk based only on internal metrics

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Category: 1st-TPRMMasterclass

28. AI models in TPRM are most effective when

A. No training data is required

B. Data is limited

C. Only historical data is used

D. Data is diverse and high-quality

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