Building AI Confidence in Debt Collections | Mike Walsh, EXL | Ep. 221

Описание: AI pitfalls in debt collection are more common—and more costly—than you think. In this must-watch episode of the Receivables Podcast, Adam Parks sits down with Mike Walsh, AI expert and executive at EXL, to uncover the red flags, real risks, and rewarding strategies for integrating artificial intelligence into your debt collection operation.

Whether you’re evaluating new vendors or wondering if your current tools are actually AI or just automation dressed up, this episode reveals exactly what every executive needs to know before they buy. You’ll learn how to spot oversold features, protect consumer data, avoid regulatory minefields, and build confidence in deploying AI that truly performs.

🚨With debt collection technology trends evolving fast, now’s the time to build a future-ready AI strategy. Don't miss Mike’s real-world insights on self-service tech, smart agent assist, and how to avoid being someone else's training data.

👉 Like this video, 🔔 subscribe to the channel, and drop your questions in the comments!

⏱️ Key Moments:

00:00 – Introduction: Why AI Pitfalls Matter in Debt Collection
03:51 – What EXL Really Does for Debt Collectors
07:52 – Training Models the Right Way (and What NOT to Do)
14:45 – Real vs. Fake AI: How to Vet Vendors Properly
21:00 – Future Trends: Self-Service, Compliance, and Global Scalability
32:12 – Final Advice: Build AI Confidence Without Buying Blind

❓ Frequently Asked Questions

Q1: What are the biggest AI pitfalls in debt collection today?
Many companies mistake automation for real AI. Key pitfalls include poor vendor transparency, over-reliance on consumer data, and failure to build internal understanding before deployment.

Q2: How can debt collection companies build confidence in AI tools?
Start small, test thoroughly, ask hard questions, and prioritize back-office or audit tasks before going consumer-facing.

Q3: What are some of the most promising debt collection technology trends?
Two-way SMS bots, real-time agent coaching, and audit automation are gaining traction—especially when they work within a unified compliance framework.

Q4: What should I ask my AI vendor before signing?
Key questions include: Is this true AI or decision-tree automation? Where is data stored? Is the model commingled or isolated? Can I see your responsible AI policy?

Q5: Why does Mike Walsh recommend a phased rollout for AI adoption?
Phased rollouts reduce risk, provide measurable ROI at each step, and allow for internal training and client buy-in.

🔗 Supplementary Links

🌐Full Episode on ReceivablesPodcast.com
https://receivablespodcast.com/videos...

📺 Watch Mike Walsh’s 5 Minute Pitch
   • EXL PayMentor | AI for Debt Collection | M...  

💼 Learn more about EXL’s Paymentor Platform
https://www.exlservice.com/services-a...

👤 Connect with Mike Walsh on LinkedIn
  / mike-walsh-b88b271  

📚 Related Podcast: Cybersecurity & Risk in Collections
https://receivablespodcast.com/videos...

✅ Calls to Action
👍Like this video to support the show
🔔Subscribe to stay ahead of debt collection trends
💬Comment below: What’s your biggest challenge with AI right now?

#AIPitfallsInDebtCollection #DebtCollectionTechnologyTrends #BuildingAIConfidence