The Industry Is Changing Fast
The debt collection industry is experiencing its biggest transformation since the Fair Debt Collection Practices Act (FDCPA) was signed into law. For decades, agencies relied on rule-based systems, manual follow-ups, and clunky “AI” scripts that were about as flexible as a rotary phone.
Now, large language models (LLMs)—the technology powering Generative AI (Gen AI)—are reshaping the landscape. Agencies using LLM-powered platforms like Aktos are optimizing recovery rates, automating repetitive tasks, and improving regulatory compliance in real-time. Meanwhile, legacy debt collections providers like Finvi, and even other AI Phone Agent providers like Skit.ai, Floatbot.ai, and Kore.ai are struggling to adapt to the new world of conversational AI and machine learning.
Let’s break down why they’re falling behind and what forward-thinking collection agencies are doing differently.
The Myth of “AI” in Legacy Debt Collection Software
For years, legacy vendors have claimed to offer “AI-powered” debt recovery solutions. But what most agencies got instead were glorified bots: rigid automation scripts that couldn’t learn, adapt, or converse.
Take Finvi, for example. Finvi markets “AI” features, but under the hood, these systems rely on rule-based logic, not true artificial intelligence. They follow a static script: “If borrower says X, respond with Y.”
Finvi’s products like FACS and CUBS are still server-based, inflexible, and require costly developer intervention for even minor workflow changes.
In today’s environment, those systems can’t compete with true LLM-driven conversational AI.
Legacy Systems Can’t Support Modern AI
Running an AI agent requires more than a clever script: it demands cloud-native infrastructure, real-time data processing, and access to large datasets that train models to improve over time.
Legacy vendors like Finvi were built decades ago, long before predictive analytics or natural language processing (NLP) became standard in fintech. They simply can’t scale to handle the data volume and compute power that modern LLMs require.
For example:
- Finvi’s products depend on outdated database structures that limit how quickly they can process or segment borrower data.
- Even Finvi’s “new” cloud product, Velosidy, lacks core compliance and automation modules that agencies need to scale their outreach and maintain FDCPA/TCPA compliance.
In short, you can’t just bolt an AI chatbot onto a 1990s system and call it innovation.
How LLM-Powered Platforms Like Aktos Are Rewriting the Playbook
Unlike legacy systems, LLM-native platforms like Aktos were built for real-world debt collection use cases from day one. These platforms use large language models, machine learning, and predictive analytics to continuously improve both compliance and performance.
Here’s what makes the new generation of AI debt collection so powerful:
1. Conversational AI That Sounds (and Think) Like a Collector
Instead of canned chatbots, AI phone agents powered by LLMs can actually understand intent, tone, and emotion. They can carry on natural, compliant conversations that sound human, complete with empathy, escalation triggers, and mini-Miranda disclosures.
They handle routine tasks like payment reminders, follow-ups, and missed calls automatically, freeing up human agents for more complex repayment discussions.
2. Compliance Built Into Every Conversation
Regulations like FDCPA, Regulation F, and TCPA are complex and breaking them can be costly. Aktos uses AI-driven compliance logic that automatically applies contact limits (“7-in-7” federally, or stricter state rules like Washington’s “3-in-7” and Massachusetts’ “2-in-7”) based on each consumer’s location.
This means no manual tracking, no compliance guesswork, and no risk of over-contacting a borrower.
3. Smarter Segmentation and Decision-Making
Legacy systems require admins to manually segment accounts by balance or delinquency. LLM-based platforms do it automatically using datasets of payment history, demographics, and communication metrics.
The result:
- Optimized collection strategies
- Higher success rates
- Lower operational costs
- Improved recovery process and overall collection efficiency
4. End-to-End Automation and Omnichannel Outreach
True LLM systems integrate SMS, email, voicemail drops, phone calls, and client portals, all managed from one dashboard. Every interaction is logged in real-time for auditability and compliance.
So when a borrower sets up a payment plan or responds to a text, the AI instantly updates their account, syncs data with your CRM, and adjusts future outreach sequences automatically.
That’s end-to-end automation without human intervention.
Learn more: Winning with AI in Debt Collection
Why “Generic AI” Vendors Like Skit.ai, Floatbot.ai, and Kore.ai Can’t Compete
Many so-called “AI” vendors have entered the fintech and call center market, but their tools weren’t designed for debt collection workflows.
Skit.ai
Marketed as an “AI voicebot,” but lacks built-in regulatory compliance, debt recovery logic, and workflow automation. Their AI handles generic CX calls, not FDCPA-regulated repayment discussions.
Floatbot.ai
Geared toward BFSI chatbots, not collections. It lacks debt collection strategy templates, dispute management, and payment integrations, forcing agencies into manual processes.
Kore.ai
Powerful for general customer support, but it’s a developer-heavy platform that requires custom coding and has no built-in support for FDCPA or TCPA restrictions.
Compare that to Aktos, where an operations leader can deploy a compliant AI phone agent in hours, no engineering required.
Real-World Results of Gen AI in Debt Collection
LLM-driven platforms like Aktos are delivering measurable results for small and mid-sized agencies:
- 30–50% increase in recovery rates from automated follow-ups and smarter segmentation.
- 50–70% reduction in manual intervention, freeing collectors to handle high-value cases.
- Faster repayment cycles driven by real-time SMS and omnichannel reminders.
- Improved customer satisfaction, since consumers can self-serve and resolve accounts on their own time.
AI agents don’t replace human collectors—they make them exponentially more efficient by automating repetitive tasks, improving compliance, and personalizing outreach.
The Future of Debt Collection Is Gen AI
LLM-based automation isn’t just a technology upgrade: it’s a competitive moat.
Legacy vendors like Finvi built on outdated frameworks can’t simply “add” Gen AI to their products. Their architectures can’t process real-time datasets, enforce compliance dynamically, or scale without massive redevelopment.
That’s why forward-thinking collection agencies are migrating to platforms like Aktos: built with AI-first DNA, cloud scalability, and compliance automation baked in.
The result? Faster recovery, happier clients, and lower operational costs, all while keeping every call and message within FDCPA and TCPA boundaries.
Legacy AI Is Dying, and That’s a Good Thing
The next generation of AI debt collection isn’t about replacing people: it’s about giving them tools that learn, adapt, and optimize every day.
Legacy vendors tried to rebrand old automation as “AI.” But as the LLM era unfolds, agencies can finally see the difference between bots that follow rules and AI agents that make smart decisions.
Aktos isn’t just another software vendor. It’s the new operating system for modern debt recovery.
Ready to see what true AI debt collection looks like?
Book a demo with Aktos and discover how automation, compliance, and Gen AI-powered outreach can transform your agency’s recovery process.
