Existing Use Cases

Chatbots are a prominent example of AI in the credit landscape. These bots will become even more sophisticated as AI evolves, moving away from simple, list-based interactions to more human-like and intelligent dialogues through natural language processing.

In the realm of credit scoring and decision-making, AI has already been employed to process unstructured data, such as social media posts or email communications. However, regulatory frameworks are limiting how this data can be used in constructing a score. For instance, FICO does not use AI directly for its credit scores, but companies that supply data to FICO do leverage AI technology to analyze unstructured documents like rental agreements and invoices.

Problems to Be Addressed

AI still faces several challenges. For example, the issue of hallucination—where AI provides incorrect or unsupported data—remains a concern. Additionally, there are transparency issues with AI models, making it difficult for regulators to understand how algorithmic decisions are made.

Another significant problem is algorithmic bias, as biases present in training data can lead to skewed outcomes. Studies have shown that large language models and mortgage underwriting processes can perpetuate social inequalities due to these biases.

Personalizing Loyalty Programs

AI is increasingly integrated into loyalty programs, particularly through transaction data analysis. Card issuers collect vast amounts of data from transactions and use AI to offer personalized rewards based on individual spending habits.

For example, an individual’s purchasing behavior can be analyzed to deliver targeted offers. If someone typically buys coffee in the morning, a card issuer could tailor promotions accordingly, enhancing customer engagement.

The Future of AI in Credit

Advancements like agentic AI are set to further complicate but also enhance credit operations. Visa’s innovative approach hints at using AI-driven platforms to facilitate seamless transactions and personalized services.

AI will continue to play a pivotal role, enabling more efficient and personal interactions while addressing the ongoing challenges of bias, transparency, and data accuracy.