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Link: Credit Shift
The credit and collections industry has been slower to adopt new technologies compared to other financial services sectors. There are fears around new technologies like AI, especially around media exposure, regulation and job losses. However, AI can be used as an assistive technology to improve productivity if the underlying data infrastructure and governance are improved. The key is to focus on capturing and structuring data to enable the use of new techniques.
Key Points
- The credit and collections industry has been slower to adopt new technologies compared to other financial services sectors
- There are fears around new technologies like AI around media exposure, regulation and job losses
- AI can be used as an assistive technology to improve productivity
- Improving the underlying data infrastructure and governance is important to enable effective AI adoption
- Focusing on capturing and structuring data is key to enable the use of new techniques
- AI can provide extra guidance and assistance to employees
- Customer adoption will drive AI adoption in the industry
- Having a fallback plan is important in case AI models fail
- Setting up dedicated teams focused on data governance and AI is important
- Investing in internal capabilities to curate and critique AI models is needed
Key Takeaways
- Focus on data infrastructure and governance to enable effective AI adoption.
- Capture and structure data to enable the use of new techniques and AI.
- Use AI as an assistive technology to improve productivity, not replace jobs.
- Customer adoption will drive AI adoption in the industry.
- Have fallback plans in case AI models fail.
- Set up dedicated teams focused on data governance and AI.
- Invest in internal capabilities to curate and critique AI models.
- There are fears around new technologies like AI that need to be addressed.
- The credit and collections industry has been slower to adopt new technologies.
- AI can provide extra guidance and assistance to employees.
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