Every day at Prodigal we talk with consumer finance companies looking to do more with less while improving compliance and customer satisfaction.
That's a tall order, but it's exactly what we do. We support consumer finance teams - lending and borrowing, healthcare revenue cycle management, auto finance servicing, collections, and accounts receivables management - with solutions designed specifically for what you do.
How do we do that?
Why AI Matters to consumer finance
Folks who come to us aren't looking for AI - or even for software. They're looking to do their jobs better and increase revenue.
In the past, you might have used (or tried to) a speech analytics tool to support your call center team. We do something better - we use AI to analyze and learn from financial conversations, so we understand not just the words in a conversation, but the context.
Speech analytics providers frequently toss out numbers like “75% accurate,” “80% accurate,” and so on. The thing is, the definition of “accuracy” is wildly inconsistent.
Taking words at face value doesn’t cut it
Here’s a scenario: It’s mid-July in Arizona – a toasty 102 degrees – and the sun is beating down on your running group. A friend turns to you, panting, and says, “Jeesh, I’m on fire!”
Do you panic, call 911, and run for a fire extinguisher? No, that’d be ridiculous.
Even though you heard every word your friend said (100% accuracy), you’re a human that knows better than to take those words literally. You consider context and sentiment too, so you understand that your friend was just expressing that she felt overheated.
Put simply, as a human being, you innately understand the meaning and intention behind the words people say.
That’s exactly what Prodigal’s AI does too.
Including context to rival human understanding
Prodigal’s real-time agent assistance and post-call solutions are powered by a first-of-its-kind AI Intent Engine.
Rather than focusing on the literal words someone says, our AI Intent Engine simultaneously considers account data, word choice, and emotional cues – like pitch and tone – and evaluates everything in the greater context of the conversation.
So, if our AI was out with you on that midsummer desert jog, it would be smart enough to offer your friend a bottle of water, instead of spraying her in the face with a fire extinguisher.
That’s because Prodigal’s AI grasps the meaning and intention behind people’s words – just like you.
Legacy definitions of AI accuracy fall short
When old-fashioned speech analytics providers talk about accuracy, they mean the percentage of time their software can accurately transcribe spoken words to written words. To them, if their software can write down 85% of the words someone said, then it’s 85% accurate.
But that's not good enough for what you're doing.
Let's say you're QA manager for a loan servicer and you see a call transcript that says, “I’m just done with everything. I want to do more with my life. And you won’t get my new address. I’m unlisted!” That definitely sounds like someone who doesn’t plan on repaying their loan.
The catch is, you don’t know the context or sentiment. Also, that transcript is only about 85% correct.
In this version of the transcript, by changing just three similar sounding words, we get a 100% accurate voice-to-text transcription: “I’m just done with Evanstown. I want to do more with my life. And you won’t guess my new address. I’m enlisted!” Well, this sheds new light on the situation.
If you also knew that this particular customer had used a cheerful tone during the call, has always talked about joining the military, and consistently paid their loan installments early, you wouldn’t waste a QA manager’s time by asking them to review this conversation.
It turns out that only correctly hearing 85% of what someone says and having no understanding of context is actually pretty terrible.
Prodigal is redefining AI accuracy
When we say “accuracy” at Prodigal we mean something else entirely.
Prodigal’s Definition of AI Accuracy:
How often AI can correctly understand the meaning and intention behind the words people say.
More than 90% of the time, Prodigal’s AI can comprehend the significance of conversations at a level of consistency that beats even the best human agents.
When we hold other AI providers to Prodigal’s definition of accuracy, it’s challenging to find even one that can deliver more than 50% accuracy. Yikes.
You deserve better.