Why Collection Data Silos Are the Biggest Barrier to AI Success | Ep. 5
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Why Collection Data Silos Are the Biggest Barrier to AI Success | Ep. 5
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Why are data silos in collections still preventing organizations from getting value from AI?
In Episode 5 of Applying AI, Adam Parks sits down with Daniel Yakimenko and Mike Walsh from EXL to discuss how behavioral data for debt collection is often trapped across disconnected systems, limiting real-time collection decisioning and performance.
Together, they explore how leading agencies are leveraging AI-driven collection strategies and digital engagement tracking to make smarter collection decisions. The conversation also highlights how unstructured data can reveal hidden consumer signals that improve engagement and recovery performance.
If you're looking for best practices for collections data management and practical ways to improve collection outcomes with AI, this conversation is for you.
Listen now and discover what your data might be trying to tell you.
Applying AI Podcast:
https://receivablesinfo.com/applying-ai/signals-across-data-silos-walsh-yakimenko
EXL Website:
https://www.exlservice.com/
Daniel Yakimenko LinkedIn:
https://www.linkedin.com/in/daniel-yakimenko-343b3b16/
Mike Walsh LinkedIn:
https://www.linkedin.com/in/mike-walsh-b88b271/
data silos in collections,
behavioral data for debt collection,
AI-driven collection strategy,
real-time collection decisioning,
unstructured data in receivables management,
collection data management,
digital engagement tracking,
debt collection technology,
collections analytics,
consumer engagement strategy
#DataSilosInCollections #DanielYakimenko #AICollectionStrategy