The number of potential use cases for AI in both the credit union and small bank markets is growing daily, and AI enablement is rapidly becoming democratized. Initially, only the largest and most sophisticated banks had the resources required to implement and support AI. However, AI has rapidly been scaled and is now within reach for many smaller financial organizations.
AI has quickly made an extensive impact on financial services. Small banks and credit unions must keep pace with the broader adoption of AI throughout the financial services industry or jeopardize their long-term viability.
The time for AI adoption is now. Your organization should consider the many use cases where AI can transform internal operations and positively impact your customers.
Our Advice
Critical Insight
Your bank or credit union’s data isn’t ready to support AI. As you work to understand AI, you need to start maturing your data practices. AI doesn’t work well without good data.
You will likely need to augment your IT talent. AI requires new types of skills, such as those of data scientists, that you will likely need to hire or retrain for.
Your existing processes may need to be modified.The nature of AI will likely require updates/modifications to your processes and good governance and project management.
You are unsure of the regulatory implications of AI.Understanding the regulatory side of AI is essential.
Impact and Result
Info-Tech can support you in AI roadmapping, data maturation, and ongoing bias mitigation efforts.
This AI use case library will help you:
- Identify potential sources of value to strategically operationalize use case capabilities.
- Jumpstart the idea generation process during the capability development phase.
- Implement AI-driven use cases.
- Integrate AI opportunities using the reference architecture.