### Q1: What is an easy way to define anomaly detection in the context of finance and fintech?  
### Q2: What moderate-level machine learning algorithms are commonly used for detecting anomalies in financial transactions?  
### Q3: What is a challenging aspect of using unsupervised learning approaches for fraud detection?  
### Q4: How can a low-code approach be utilized to implement AI strategies for fraud detection in Test_Company?  
### Q5: What moderate-level factors should be considered when assessing risks associated with financial transactions?  
### Q6: How can predictive analytics improve the risk assessment process in financial transactions?  
### Q7: What easy communication strategy can enhance collaboration across teams for more effective risk management?  
### Q8: Why is it important to educate employees about AI tools used in fraud detection?  
### Q9: What is a difficult communication challenge that arises when discussing AI implementation and its ethical implications with stakeholders?