Pass Your Risk and AI (RAI) Exam with RAI Dumps (V8.02): We have RAI Free Dumps (Part 3, Q81-Q120) Online for Checking

1. A checkers AI program evaluates possible board positions using six criteria, each with a calculated score (c1 to c6) and corresponding weight (w1 to w6).

Which formula will provide the overall score v for a given board position?

2. A robotics company designs an AI model for a self-driving vehicle that must make quick decisions in various states, like road conditions and nearby obstacles. To handle the complexity, they decide against using a traditional tabular approach.

Which reinforcement learning strategy should they adopt?

3. A tech company wants to align its AI policies with ethical standards but is concerned that current laws might not cover all potential ethical issues.

What is the best approach the company could take to manage this concern?

4. In evaluating a model that predicts dividend payments, an analyst finds that increasing the threshold reduces the false-positive rate but also lowers the true positive rate.

What does this indicate about the threshold setting?

5. A credit card company wants to reduce the dimensionality of customer transaction data to identify spending patterns without using predefined labels.

Which technique would be most suitable?

6. A healthcare provider in the U.S. is looking to improve its data security practices. Under HIPAA, what is a key requirement for the provider?

7. A government official consults with the company’s Chief Privacy Officer about privacy risks in AI model training.

Which strategy would be most effective in protecting user privacy while supporting AI development?

8. During training, a credit scoring model using stochastic gradient descent shows fluctuating performance and fails to converge smoothly.

Which of the following is the most likely cause?

9. A retail company uses an algorithm to set product prices, which unintentionally raises prices in neighborhoods with a high concentration of minority groups.

Which factor determines if this is considered discrimination?

10. A financial institution is implementing a neural network to predict loan default risk. They use gradient descent with backpropagation.

What is the primary purpose of applying the chain rule in this process?

11. A bank wants to analyze long text sequences to understand customer sentiment over time. However, their RNN model faces difficulty in learning from words far apart in sentences.

What model modification could help with long-range dependencies?

12. A multinational healthcare provider is using AI to prioritize patient access to specialist appointments.

How should the provider apply justice in this scenario?

13. An AI research lab is evaluating different LLMs. They need a model that combines both encoding and decoding capabilities for versatile NLP tasks, including text understanding and generation.

Which LLM would be most suitable?

14. Which term best describes a dataset that includes a mix of organized, structured financial data and unstructured text data from customer reviews?

15. A bank is building a classification tree to identify high-risk loan applicants.

Which criterion is most suitable for evaluating the splits in this classification problem?

16. A financial analyst uses a QRM that outputs a point estimate for potential losses, which is lower than expected. The analyst recommends increasing risk exposure without examining the range of possible outcomes.

What misinterpretation is occurring here?

17. In solving the Tower of Hanoi puzzle, which method allows the problem of moving n disks to be broken down into simpler instances involving n-1 disks?

18. In an SVM model, which of the following statements best describes a support vector?

19. An analyst applies the K-means algorithm to cluster financial transactions and chooses Euclidean distance as the measure for assigning points to centroids.

If the data has features with different scales (e.g., transaction amount in thousands and frequency as an integer), what should the analyst do before running K-means?

20. During a model comparison, a data scientist notes that transformers outperform RNNs in both speed and ability to parallel process data.

What feature of transformers contributes most to this advantage?

21. A trading firm uses reinforcement learning to determine the best time to buy or sell an asset. They have partial information about the state transitions and aim to maximize long-term profits by identifying the best action in each state.

Which reinforcement learning approach is most suitable for this scenario?

22. A bank wants to analyze customer reviews, where certain words like "rate" may have different meanings depending on the context.

Which feature of the transformer model would be most beneficial in distinguishing between the different meanings?

23. A marketing firm uses a neural network to predict customer churn. During model evaluation, they observe that model accuracy fluctuates significantly depending on the data sample used.

What would be the best approach to reduce this fluctuation?

24. A data scientist is clustering a dataset and notices that as the number of clusters, K, increases, the inertia consistently decreases.

What does this indicate, and what technique can help identify the optimal K?

25. A firm’s AI/ML model has started displaying unexpected outputs likely due to data drift.

What should the firm do to manage this?

26. A digital marketing team applies a multi-arm bandit algorithm to decide which of several ad versions to display to users. Each ad version has a different conversion rate, but this rate doesn’t impact future performance.

Why is the multi-arm bandit model effective in this situation?

27. Why is inscrutability particularly challenging in deep learning models compared to classical AI models?

28. An analyst is using the K-means algorithm and calculates the Within-Cluster Sum of Squares (WCSS) to evaluate clustering quality.

Which of the following statements correctly describes the significance of WCSS?

29. A multimedia company wants to develop an AI model that can generate both text and images based on user prompts.

Which type of model is most appropriate for this task?

30. A financial institution is testing a new QRM for its trading platform.

Which type of testing is crucial to confirm that all integrated components of the model work correctly together?

31. In preparing text from central bank communications for analysis, a researcher encounters phrases like “interest rates might increase.”

Which preprocessing step can help convert these words to their base forms, making them easier to analyze?

32. 1.A problem-solving AI model is being developed to solve the Tower of Hanoi puzzle by systematically planning moves to achieve the final goal. The model needs to evaluate intermediate steps to clear disks strategically for future moves.

Which approach would best help the model to complete this task?

33. A bank’s machine learning team has developed a loan default prediction model that performs very well on the training data but poorly on the test set.

What issue is this model most likely experiencing?

34. An analyst calculates the Calinski-Harabasz index (Variance Ratio Criterion) to evaluate the performance of a K-means clustering model.

Which of the following correctly interprets a high Calinski- Harabasz index value?

35. A financial services firm is incorporating alternative data into its investment models.

What is a key step the firm should take to manage the potential risks of using this data?

36. In a fuzzy K-means clustering model with three clusters, a data point has probabilities of 0.2, 0.5, and 0.3 for clusters 1, 2, and 3, respectively.

What does this indicate about the data point?

37. An investment firm is setting up its model risk management framework.

Who is primarily responsible for approving or rejecting models based on validation results?

38. A bank is considering purchasing a credit risk model that uses alternative data from a third-party vendor.

What should the bank require from the vendor to manage potential model risk?

39. When building a classification tree, the bank’s analysts decide to use entropy as a splitting criterion.

Which of the following best describes entropy in this context?

40. A logistics company aims to use reinforcement learning to improve route optimization for its delivery trucks, seeking to minimize total delivery time. The company estimates immediate delivery time for each route but wants a method to continuously update optimal policies based on both immediate and future time estimates.

Which Bellman equation form should they use?