The rise of AI in debt collection is no longer theoretical. 

Virtual agents, AI-powered systems handling conversations via voice, text, email, and chat, are already shaping how organizations communicate at scale.

But innovation in a regulated industry comes with high stakes. 

Choosing the wrong tool can mean compliance headaches, reputational damage, and wasted spend.

The right one? 

It can significantly lower costs, increase liquidation rates, and free up agent bandwidth.

This guide will help you understand the landscape, avoid pitfalls, and evaluate virtual agents through the lens of regulation, ROI, and real-world readiness.

*Please note that Abstrakt does NOT currently offer virtual AI agents. However, with the landscape changing so quickly, it’s important to stay on top of industry trends as they shape our roadmap for future developments. 

What Is a Virtual Agent?

A virtual agent is software that interacts with consumers via natural language, through phone calls, text messages, email, or chat, without human involvement. 

Some are rules-based (think: if/then flows), while others leverage machine learning or large language models (LLMs) to interpret, respond, and adapt mid-conversation dynamically.

Both types serve a purpose, but not all are suitable for the compliance-heavy world of debt collection.

Rule-Based Bots vs. Agentic AI

There’s a critical distinction between:

• Rule-based bots: Hard-coded logic trees. Predictable. Easy to audit. Limited in scope.
• Agentic AI: Learns from data, reacts to signals, adapts in real time. Offers more power, but requires more guardrails.

Many collections teams gravitate toward rule-based tools at first, as they’re more familiar and less legally risky. 

But as the technology matures, expect more movement toward agentic systems for complex use cases like objection handling, payment negotiations, and multilingual support.

Why Collections Teams Are Exploring Virtual Agents Now

Collections organizations face an evolving set of pressures:

• Rising account volumes and delinquencies
• Increased costs to collect
• Shortage of experienced agents
• Growing compliance scrutiny and enforcement

Virtual agents promise a path forward: 24/7 scalability, script adherence, data consistency, and cost savings.

What’s the ROI?

While results vary, here are directional benchmarks from early adopters and related case studies:

• 20–30% reduction in cost-to-collect when replacing low-complexity calls with AI-driven voicebots (source: McKinsey, 2023)
• Up to 40% containment of routine inbound calls via virtual agents in financial services (source: Quantiphi)
• 15–25% improvement in agent handle time when pairing live agents with AI assistants (source: CXtoday.com)

For collections, the potential is significant, but only if solutions are chosen and deployed wisely.

The Questions You Need to Be Asking

Virtual agents don’t just touch consumer data – they speak it, log it, store it, and sometimes even route it to third-party systems.

Before selecting a vendor, dig into:

• Privacy Impact Assessments (PIAs): What personal data is captured? Where is it processed? Who has access?
• Third-party risk: Are there downstream tools (LLMs, APIs, storage providers) involved that you can’t directly audit?
• Data ownership and usage: Will your call data be used to train someone else’s model?
• Model transparency: Can the vendor explain how their system makes decisions, handles edge cases, and ensures auditability?

The difference between a secure, compliant vendor and a risky one often lies in the layers of their tech stack, not just the front-end interface.

How to Categorize Vendors

When evaluating virtual agent vendors, use this quadrant model:

Axis 1: Collections Focus

• Niche vendors with debt collection specialization
• Generalist AI platforms serving multiple industries

Axis 2: Maturity

• Early-stage or emerging providers
• Established platforms with proven deployments

The hard part with something like this is that MOST vendors are “emerging” with this type of tech. You need to find the one that aligns best with your goals.

Knowing where a vendor falls helps you tailor due diligence and pilot design. 

Don’t just look for a slick UI, ask who their clients are, what compliance requirements they’ve met, and how they’ve handled edge cases in production.

Pricing Models

Many vendors charge based on usage, per minute, per message, or per call. 

But this can create sticker shock if pricing doesn’t align with outcomes.

Consider asking:

• How does pricing scale with performance improvements?
• Are there flat-rate or value-based models available?
• What ROI have similar clients seen after 6-12 months?

And always request proof, not just projections.

Now, where do you start?

Jumping in too fast is a mistake, even if the demo looked great.

Start with a contained pilot:

• Route a specific IVR branch or call type through the virtual agent
• Test with a small outbound campaign or a simple inbound inquiry
• Track KPIs like containment rate, average handle time, compliance adherence, and consumer satisfaction

Bring compliance, IT, and operations into the room early. The pilot should prove not just the tech, but the readiness of your team to support and scale it.

What We’re Learning from the Market

Across the industry, RFPs are becoming more sophisticated. 

Teams are asking sharper questions about:

• Vendor tech stacks and LLM usage
• Ability to support Reg F, call disclosures, and required scripting
• Performance in real-world pilots – not just test environments

Some vendors have built proprietary models. 

Others are duct-taping third-party tools. 

A few specialize in collections. 

Many do not. 

This variability is exactly why a standardized approach to vendor selection matters.

Common FAQs

Q: Are virtual agents allowed under current collections regulations?

Yes, but disclosures, consent, and auditability still apply. 

You’ll need a vendor that understands Reg F and the FDCPA inside and out.

Q: Can a virtual agent replace a live agent?
In low-complexity tasks like payment reminders, ID verification, or balance inquiries, absolutely. 

For escalations or nuanced disputes? Not yet.

Q: What if a bot says the wrong thing?

That’s why pilots, overrides, and conversation routing rules are critical. 

Good vendors offer full transcript logs, scoring, and error handling.

Final Thoughts: Don’t Wait, But Don’t Wing It

Virtual agents have the potential to unlock real efficiency, compliance consistency, and consumer experience improvements. 

But this is still an emerging space. 

The wrong move could expose you to reputational or regulatory risk.

To move forward:

• Start small
• Ask the right questions
• Include compliance and IT early
• Focus on results, not just features
• Compare vendors using frameworks, not just gut instinct

ARMTech Advisors is a great resource as they’ve worked with industry experts to create RFPs that can be used to evaluate vendors for specific needs like AI virtual agents.