Pop quiz:

‍What’s the best way to identify and capture complaints?

A. Customer service representatives during customer interactions

B. General keyword and phrase-search technology

C. Artificial intelligence trained on consumer finance information

Actual customer complaints

Before you answer that question, take a look at these comments from actual customers and guess whether each of those choices would identify any of these as a complaint:

 "I'd rather beg on the streets than ever take out a loan with your company again."

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"Why doesn't it recognize my number when I type it in?"

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“I was really hoping to be able to get on track here.”

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“It’s ridiculous that I can’t see my balance.”

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“That interest rate is robbery!”

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“This is a great way to make a lot of people angry.”

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None of those has the word “complaint” in it. None of the customers says “I’m unhappy,” or “This is a problem.”

But they are unhappy and these are problems, which mean these are all complaints.

‍Options for complaints management identification

So let’s go back and look at our options again.

A. Customer service representatives

Customer service representatives can do a good job with complaints identification, but there are a few problems they run into:

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1. They’re busy. In dealing with a customer with a problem, their primary goal is to manage the problem, not manage a series of drop-down menus to identify, categorize, rank, and document it.
2. They are only as good as their guidelines. Is sarcasm (as with that last customer example) a complaint? What about a simple question (Why doesn’t it recognize my number?)?
3. They’re…well, human. That plays out in multiple ways, but one big issue can be if they are penalized if their customer contacts show too many complaints. That can discourage them from reporting.

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B. General keyword and phrase-search technology ‍

This was supposed to be “The Answer,” and lenders and banks jumped on the chance to hand this task over to technology. But it hasn’t quite delivered. Here are the issues:

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1. Keyword and phrase-search technology relies on transcriptions, which are often faulty.
2. It’s impossible for humans to create a complete list of keywords and phrases to look for. Scroll back to that list of examples. Which phrases would you have known to include in the list of flags?
3. Relying on faulty transcriptions and the limits of searching produces so many false positives and false negatives that many banks just gave up and went back to relying on the customer service representatives (and they have enough on their plates!).

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C. Artificial intelligence trained on consumer finance information

Now here’s something different.

There are lots of general purpose AI solutions and white-labeled versions of ChatGPT that you might hear about, but they’re not going to deliver what you need here.

What you need is AI that is built for and trained on consumer finance conversations so it understands not only individual words but complete conversations.

‍How AI is different

Prodigal built our AI Intent Engine to use both machine learning (ML) and natural language processing (NLP) to sift through the subtleties and nuances of your customer conversations. 

It’s not limited by focus or stress, like people.

It’s not reliant on transcription or lists of phrases to search for.

In fact, it understands both the content and the context of the conversation.

It's like having a pair of high-tech goggles that can see through words and capture true emotions.

What is a complaint?

Let’s talk about what makes a complaint. A complaint doesn’t require the customer to say, “I complain!” A complaint simply means that a situation is unsatisfactory or unacceptable.

So let’s go back to that sample customer complaint above: "Why doesn't it recognize my number when I type it in?" 

An old-school transcription-dependent tool and a customer service representative might not register that question as a complaint. But Prodigal’s model does. The customer can’t access the information they need - that’s an unsatisfactory or unacceptable situation.

And in this case, we’re not talking about ordering socks from a catalog. We’re talking about people’s financial lives.

So Prodigal’s AI identifies this as a frustration with high severity and turns it into a beacon for immediate attention.

Prodigal blends ML capability and consumer finance industry-specific intelligence to tailor solutions that cater to your unique business needs and challenges. We're your partner in enhancing customer satisfaction, one conversation at a time. 

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