If your firm is hasn’t yet incorporated machine learning to its strategy, the first question might be why AI in the first place?
Immediate Scale and Speed
Putting aside the hype around AI as the hottest new tech, legitimate studies have shown that financial services who’ve committed to AI early and comprehensively have seen a 19% increase in revenue, whereas slower adopters see lifts around 12%. Pair those results with Pairity’s own case studies — where implementation of our AI can drive a revenue increase of 20%, an increase in contacts of 38%, and decrease in labor hours by 24% — and today’s buzziest tech seems more like a sure thing.
Transparency and Compliance
Traditional AI (yes, we’re that far along with new technology that many AI products are dated) could be brilliant, but its opacity could be a huge risk to firms. If you can’t see, explain, or control your data inputs, algorithms, and granular decision making, machine learning is of little use to any regulated industry.
Pairity is a leader in transparent, customizable, and explainable AI because we know that technology is only as good as its flexibility and ability to translate complex processes. Pairity uses multiple unconventional data points (what the CFPB calls “alternative data”) to make layered and nuanced decisions for lenders and collectors that are automatically recorded for compliance. Each individual action is backed up with the data points used, the weights and values assigned to those data, and what bearing they have on a final decision. Pairity also translates its models into clear, graphical reports that can be handed off to regulators for quicker comprehension.
A Consumer-First Approach That’s Better for Business
Another benefit of alternative data that you can’t get from traditional scoring models is a more comprehensive view of your consumer. On the lending side, alternative data has actually increased access to credit for many protected classes and credit “invisibles” (which the CFPB lauded in a recent No-Action Letter.)
With a wider set of data points and continual machine learning, lending firms get more than simple “yes or no” decisions. Consumers can be matched with products that are most appropriate for them instead of being turned away completely when they don’t qualify for the product to which they originally applied.
On the collections side, Pairity AI can identify and increase collectable accounts by looking at a more complex range of factors than what had deemed a consumer difficult to contact and collect on previously. Records such as employment status, relocation, and other publicly available data is considered before categorizing your consumer contacts.
And for the consumer on both sides, this means the first contact and approach can be tailored to their specific profile, increasing the likelihood of engagement, agreement, and long-term consumer satisfaction. Learn more about Pairity’s Data Science as a Service.