Fear of falling behind is pushing the financial services industry to accelerate innovation at a speed we've never seen before.
In a recent blog, we discussed the applications of AI in collections and dove into the benefits and risks. Knowing the topic of AI is central to many boardroom discussions, what steps can you take to mitigate both internal and external risks associated with AI?
If you're in the beginning stages of considering if AI can help you solve the problems in your debt collection process, look closely at these nine questions to ask yourself or take to your leadership team before implementing an AI-driven tool.
1. What are your strategic objectives?
Begin by defining your business goals and core objectives in adopting AI in your collection strategy. Are you looking to reduce operational costs through automation, enhance customer satisfaction, increase recovery rates, or limit losses? Clear goals will serve as the foundation of your AI implementation plan.
2. What processes would be enhanced through an AI tool?
Identify areas in your collections process that can benefit from AI. Is it the lack of customer behavior data or the limitations in communication and response time?
Is it the repetitive, labor-intensive tasks that often lead to manual errors or operational inefficiencies due to the lack of human resources?
3. What are the ethical and regulatory considerations?
As AI regulations evolve rapidly, how does your institution intend to ensure compliance? Have you formulated a strategy to mitigate the risk of wrong information and guard against bias that could create regulatory problems?
How will you prevent decisions that lead to bias or discrimination against financially vulnerable populations?
Will you develop guidelines for fairness and implement controls to avoid unexpected outcomes? Do you have a designated team member who can deeply understand AI technologies, oversee its proper use, and ensure compliance with regulatory requirements?
4. How would AI impact your employees and workforce?
In a Forbes Advisor survey, over 75% of people are concerned that AI will cause job loss within the next 12 months. Addressing concerns about job displacement with your employees is important and reinforcing that AI can enhance your team's capabilities rather than replace them.
Another key factor to consider is whether you have the internal capacity to upskill employees or hire external talent with adequate AI skills.
A recent Salesforce survey highlighted that leaders believe that 66% of their employees must gain the skills to leverage the technology successfully.
5. Do you have necessary data to feed the AI model?
AI is only as good as the data it's trained on. Is your data accurate, updated, accessible, and complete? AI thrives on data. If your data is outdated or incorrect, that's what the AI system will use. Do you have the consent from your customers to use their private data to train AI models?
6. Do you have data governance policies to prevent security risks and fraud?
Data breaches are top of mind when dealing with highly sensitive information. How will you ensure that data is protected for customer privacy? How do you ensure the protection of AI systems from cybersecurity risks?
7. How will the integration of AI impact the customer experience?
The key to strong customer relationships is trust. Receiving human support easily and immediately is still crucial for consumers. Consider at what stage a human can step in if the AI tool hurts the customer experience and leads to frustration.
Evaluate how AI will enhance customer interactions by diving into what your customers want. Can the AI tool provide personalized and empathetic communication? Will AI help foster better customer relationships for increased retention?
8. How will you measure success and ROI?
Define KPIs to measure the success of your AI's effectiveness. Will you evaluate success through improved recovery rates, reduction in delinquency, better contact rates, and enhanced member satisfaction? How will you track these metrics over time?
9. Do you have a change management and implementation plan?
Change is never easy, and with many AI tools still being new, it's critical to communicate a plan to secure buy-in at every level. Keeping team members informed about developments throughout the implementation process will ensure they are equipped with enough knowledge to adapt to the changes to come.
By addressing these key adoption questions with your team, you can create alignment between potential AI systems and your institution's promise to your customers. You can also gauge your readiness for a seamless transition.
Asking and answering these questions will enable you to embrace AI responsibly and effectively in your collection strategy.
Want to learn more about AI in collections? Register for our upcoming webinar - The AI Revolution: Navigating the Risks and Benefits in Collections. Also, for further insights and valuable advice on enhancing your collection strategy, subscribe to our newsletter, where we delve deeper into these critical aspects.
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