2024
FinanceOps AI
financeops.ai
Background
How can we trust the AI — was a feedback we got very often, especially during our demo calls. Most of our clients and users are people with little to no tech background and thus, AI seemed like both a magical wand as well as a wild mushroom you didnt know if it was safe to eat or not. In short, AI was a black box for them, something they wanted to understand and trust but couldn’t. They wanted control. Our clients would frequently come to us with requests like
“Can you ASK your AI agent to not use words like “consequence” or “collections team”.
Our data science team would then program their rule engine accordingly.
But we needed a solution, one that would that would empower our users and give them control.
Designing a Solution
Collections teams face the constant pressure of managing high-volume, repetitive workflows — sending reminders, invoices, and follow-ups across multiple channels — while trying to maintain accuracy, compliance, and a personal touch.
At the same time, introducing AI into this process brings its own challenges.
While AI promises to streamline operations and increase efficiency, it can feel like a black box to users who want to understand and control its behavior.
How do we solve for this?
Our goal was simple: give collections teams the power of AI without the mystery, letting them automate workflows, personalize messages, and stay in control.
Build, schedule, and run multi-step workflows for reminders, invoices, and follow-ups without manual effort.
Personalize at Scale: Use AI to craft messages for cohorts, control tone, insert variables, or draft custom messages — all tailored to each customer segment.
Track workflow progress, see live updates, and measure performance to make smarter, faster decisions.
Create cohorts, add delays between actions, and run workflows on-demand or on a schedule, keeping users empowered and confident.
With these goals, we aimed to turn AI from a black box into a trusted teammate, helping teams work smarter, not harder, while improving collections outcomes and customer engagement.
Results and Impact
1. Increased Trust in AI
The Workflow Builder gave users control and transparency over AI-generated messages and workflows, significantly reducing the time spent monitoring agents and building confidence in the system.
2. Higher Recall Post-Sales Call
Its unique strategy-building capabilities set us apart from competitors, creating strong recall and leaving a lasting impression during later stages of the sales cycle.
3. Increased Engagement on the Platform
Before the Workflow Builder, user interactions were limited. After its introduction, users returned frequently to test new strategies, tweak workflows, and monitor performance, driving deeper engagement.
Read Full Case Study