As AI adoption accelerates across credit and accounts receivable, organizations face a critical decision: should they build their own AI capabilities or deploy pre-trained solutions? While both approaches offer advantages, the wrong choice can lead to unnecessary cost, increased risk, and delayed ROI.
This session provides a practical framework for evaluating “build vs. buy” decisions in credit operations, grounded in real-world use cases such as collections prioritization, risk assessment, and dispute management. It also introduces an emerging third path—configurable AI built on pre-trained foundations—that enables organizations to balance speed, control, and scalability.
Key Takeaways
- A clear framework to evaluate Build vs. Buy decisions in credit and AR
- Where DIY AI makes sense, and where it creates unnecessary complexity
- How pre-trained AI agents accelerate ROI in collections and operations
- The hidden costs and risks of building internally
- Why a third approach called configurable AI is emerging as a practical middle ground
- How to align AI strategy with risk, governance, and business outcomes
Speaker:
Elaine Nowak, Global VP of Product Marketing, Sidetrade