### Q1: What is one easy method to ensure data integrity in finance-related data products?  
### Q2: How can employing a mixed approach enhance the effectiveness of data product development in finance?  
### Q3: What are the key ethical considerations that can prevent failures like those experienced by Wells Fargo?  
### Q4: How does understanding user needs contribute to the success of data products in finance?  
### Q5: What moderate challenges might arise when implementing predictive analytics in credit scoring systems?  
### Q6: How can collaboration among diverse teams improve the development process of data products?  
### Q7: What are the potential risks of using a low-code approach in developing financial applications?  
### Q8: Discuss the importance of addressing regulatory landscapes when launching new financial data products.  
### Q9: What is a difficult lesson learned from the failure of the Facebook Libra project regarding stakeholder engagement?