The speakers emphasized the importance of identifying the right problems to solve with AI, applying the right data, and choosing the right data partner. They highlighted the need for a well-defined business challenge and use case before moving forward with any data-driven solution. They also stressed the importance of having an unbiased sample that offers a good representation of the behaviors the institution is trying to pin down. The selection of fintech partners for innovation is also crucial, especially in a climate where funding is often an issue.
Key takeaways:
- Successful AI and analytics strategies in the financial services and tech industry require expertise in data and modeling. It's crucial to partner with experienced data and AI organizations to develop and launch AI initiatives.
- Identifying the right problems to solve with AI involves two considerations: identifying problems where data can provide real insight, and ensuring access to reliable, generalizable data that can be enriched to drive a particular insight.
- Before moving forward with any data-driven solution, it's important to have a well-defined business challenge and use case. This informs what data is gathered and how the sample is built. It's also crucial to have an unbiased sample that offers a good representation of the behaviors the institution is trying to pin down.
- Choosing the right data partner is crucial. Organizations need to select partners wisely, and select them for innovation. It's also important to perform due diligence and de-risk the selection of partners.