Debt Collection
Prodigal Alternatives in 2026: 5 Options for Teams That Want a Voice-First Agent
The best Prodigal alternative for teams that want a voice-first collections agent is Vodex. Prodigal is a broad platform.
Why RPC is stuck around 26%, what thousands of calls taught us, and how voice AI plus smart workflows can lift contact rates without burning out your collectors

If you run a collections team, you already know this: you only get paid when you talk to the right person.
Yet across the industry, Right Party Contact (RPC) rates still hover around 26%, and roughly one in four contact centers sit below 20%, meaning three out of four outbound calls never reach someone who can actually resolve the debt.
Dialing harder has stopped working. Consumers screen unknown numbers, carriers label high‑volume lines as spam, and your collectors are exhausted.
At Vodex, we’ve spent the last couple of years working with U.S. agencies and analyzing thousands of calls and campaigns while building our voice AI stack. This article shares what we learned: why RPC is stuck, what actually moved it, and how voice AI plus a better outreach design can finally push you past that 30–40% band.
New to the metric? Start with our guide to calculating and raising your right-party contact rate.
Industry benchmarks say the average RPC rate for collections sits at about 26%, with 23% of contact centers under 20%. On paper, it looks like “that’s just the new normal.
But when we looked inside real campaigns, we saw something else: RPC wasn’t low because one thing was broken—it was low because five small problems stacked together:
Outdated or wrong numbers: Skip‑tracing or enrichment hadn’t been run in months. In many portfolios, 10–25% of numbers were disconnected or clearly wrong, but still being dialed every day.
Voice‑only, single‑channel strategy: The playbook was still “more calls, more often,” even though modern data shows digital channels like SMS get far higher open and response rates than email or cold calls alone.
Bad timing: Calls were concentrated during mid‑morning work hours, not when specific consumer segments were actually free to talk, even though studies and operations data show time‑of‑day has a clear impact on contact and answer rates.
“Spam likely” caller ID: High volumes from a small pool of numbers triggered carrier spam filters. Once your numbers show up as “Spam” or “Scam Likely,” answer rates drop, even on good data
High friction after first contact: Even when agencies did reach the right person, the experience was often stressful and rigid: no self‑service options, no digital follow‑up paths. Many consumers decided “never again” and stopped picking up future calls.
Voice AI alone cannot fix all of that. But paired with better workflows, it can attack several of those problems at once.
Before we get into Vodex specifically, it is worth grounding in the broader numbers:
The pattern is clear:
RPC is no longer just a dialer metric. It’s a whole‑system outcome of data quality, channels, timing, and friction.
Where does voice AI fit in? By sitting in the middle of that system, doing the repetitive, high‑volume contact work that humans shouldn’t be doing manually.
A 20‑collector agency in the Midwest came to us with a familiar problem: RPC stuck around 22% on outbound campaigns. They were working a mix of healthcare and utilities portfolios.
Their instinct was “we need a stronger script and more dials.” Here’s what we did instead, together:
Cleaned the data first
Introduced SMS + email as soft first touches
Brought Vodex voice AI in for high‑volume, lower‑balance accounts
Reserved human collectors for complex, high‑value conversations
Agents focused on:
Voice AI didn’t magically “fix” RPC. But it made it cheap and scalable to reach out at the right times, on the right numbers, with the right context and then pass real conversations to humans.
A California agency focused on retail and BNPL portfolios was hovering at 24–25% RPC. They had decent agents and had tried multiple scripts, but nothing moved the needle.
What we saw in their campaigns:
Together, we set up a simple structure:
Day 0 – Digital + AI First
SMS + email with a portal link went out automatically for new placements.
For certain low‑balance bands, Vodex began making short, compliant calls:
Day 2–3 – Human Focus on Warm Accounts
Human collectors’ daily queues prioritized:
Ongoing – AI for Follow‑ups, Humans for Edge Cases
From these and other projects, here’s how we now think about it.
Our philosophy at Vodex is simple:
Use AI to clear the noise and repetitive work so humans can spend more time on the conversations that actually require humans.
Even if you never use our stack, you can apply the same thinking:
Clean your data quarterly: Run skip‑tracing and enrichment for phone and email, remove dead numbers.
Go digital‑first for context and self‑service: Use SMS and email to explain who you are and offer a secure portal before calling.
Reserve human calls for high‑intent and high‑value accounts: Prioritize those who opened, clicked, or partially paid
Use automation (or voice AI) for the long tail: Let a system handle scheduled reminders, long‑tail follow‑ups, and predictable flow
Measure RPC by segment, channel, and time window: Don’t just look at global RPC. Break it down by list type, time of day, and outreach pattern.
Vodex simply makes this approach faster, more consistent, and more scalable.
In many deployments, Vodex is paired with DROS (opens in a new tab), an operating system for collections teams. DROS centralizes dialer, CRM, SMS/email, payments, and workflows in one place; Vodex sits on top as the voice automation layer.
You don’t need both to start improving RPC. but together, they let you design outreach around the reality of modern consumers, not the habits of legacy dialers.
That is the change we are building for with Vodex. If you want to see how this could look on your portfolios, we are always happy to walk through a few real examples from your shop.
In most shops we’ve seen, low RPC is not a dialer problem, it’s a system problem. The biggest drivers tend to be dirty or outdated data, voice‑only outreach, calling at the wrong times, poor caller ID reputation, and a high‑friction experience when you finally reach the debtor. Until you address those together (data hygiene, channel mix, timing, and experience design), simply swapping dialers or tweaking scripts rarely moves RPC in a durable way.
SMS hurts RPC when it’s used to “warn” people you’re going to call (“we will call you at 2 PM”), but it helps when used to provide context and self‑service options. In practice, high‑performing teams use SMS to explain who they are and offer a secure portal link first; this resolves a chunk of accounts without any call and warms up the rest, which then see higher contact and payment rates than voice‑only campaigns. Opt‑outs happen, but they usually remove unproductive numbers you were wasting dials on anyway.
A more modern way is to look at “right‑party engagement” across channels, not just calls answered. That means tracking: RPC on voice (calls where you confirm identity), SMS/email responses or authenticated portal logins, and payments or arrangements that followed any of these touches. This gives you a truer picture of how many right parties you are actually reaching and moving, and it lets you see which mix of channels (e.g., SMS‑first + targeted calls) is lifting outcomes, not just dialer KPIs
For most small and mid‑sized agencies, a quarterly data refresh on active portfolios is a strong baseline; waiting a full year leaves you dialing a lot of dead numbers. At a minimum, you want to: (1) push new placements plus older, high‑value segments through a modern skip‑tracing or enrichment provider, (2) remove or deprioritize obviously wrong/disconnected numbers, and (3) normalize phone types so mobile vs landline can be treated differently. This kind of hygiene alone often recovers 10–20% of wasted dial attempts.
The key is to treat voice AI as a structured Tier‑1 outreach layer, not a free‑for‑all auto‑dialer. In well‑designed deployments, AI agents handle first touches, reminders, and simple conversations using pre‑approved language, enforce time‑of‑day and frequency rules, log and honor opt‑outs, and escalate complex or emotional situations to humans. Agencies using this pattern report higher connection and recovery rates at lower cost per interaction while staying within FDCPA/TCPA guardrails and maintaining audit trails.