MessagePay signs 400th lender as it adds new tools

MessagePay has signed its 400th financial institution customer, a milestone that comes as it adds two products for credit unions and community banks.

The Utah-based payments and communications platform has launched MessagePay Direct, a two-way texting tool for payment issues, and AI Pay+, a predictive analytics tool for collections teams. It has added 86 credit union and community bank customers since the start of 2026 and is on pace to process more than USD $1.2 billion in payment volume this year.

The expansion reflects a broader push by smaller financial institutions to move borrower communication away from branches and call centres and toward mobile channels. MessagePay's system lets borrowers make payments by text message, web, phone, and email, including through a secure link or by replying to a text without downloading an app.

The model targets credit unions and community banks, which often have smaller collections teams than larger banking groups. For those institutions, the appeal is the potential to reduce missed payments and cut manual collections calls.

"When borrowers can pay with a tap instead of a phone call or a trip to the branch, they actually pay on time," said Greg Pesci, President and CEO of MessagePay.

"That's what's driving adoption - institutions are seeing delinquencies drop and payment volume climb, and borrowers like the convenience," Pesci said.

New tools

AI Pay+ is designed to analyse borrower payment behaviour and predict when and how a borrower is likely to pay. That gives collections teams another layer of segmentation beyond standard delinquency categories, which sort overdue accounts by how late a borrower is on repayment.

The tool is meant to help staff distinguish between borrowers likely to settle on their own and those who may need direct outreach. MessagePay Direct, launched alongside it, adds a direct texting channel for payment discussions instead of routing those conversations through a call centre.

Brandon Alletto, SVP of Sales at MessagePay, said customers had already been seeing results with the core platform.

"AI Pay+ and MessagePay Direct give their teams something more specific: a way to prioritize which accounts need a human touch and which ones don't," Alletto said.

Customer mix

MessagePay's customer base ranges from credit unions with USD $10 million in assets to banks with more than USD $20 billion. Those institutions are spread across the US, from Hawaii to Florida, suggesting the platform's appeal is not limited to one region or one tier of lender.

The company supports more than 30 core and third-party integrations, including Fiserv, Jack Henry, Corelation, CU Answers, and Flex, which are widely used processing or core banking systems among community financial institutions.

Access to those systems matters because small and mid-sized lenders often rely on established core platforms that can be difficult for outside software providers to connect with. A new integration with Fiserv banking cores has widened MessagePay's addressable market by allowing community banks to use the platform for the first time, according to the company.

The move is notable because community banks and credit unions tend to buy software differently from larger national lenders. Instead of building custom tools internally, they are more likely to rely on specialist vendors that can work within existing banking infrastructure with limited internal technology resources.

Collections focus

The addition of predictive analytics also points to a broader trend in consumer finance technology, with lenders using data tools to decide when staff intervention is necessary. In collections, that can mean focusing limited staff time on borrowers who are less likely to pay without contact while allowing others to resolve accounts through self-service channels.

For community lenders, the economics can be especially important. Rising delinquencies can create pressure to hire more collections staff, while manual phone outreach remains relatively expensive compared with digital communication. Text-led payment tools and prediction models are being positioned to address that gap by changing the cost of servicing overdue accounts.

Pesci said the spread of customers by size suggests the model is moving beyond early adoption.

"The range of institutions we work with, from small community financial institutions to billion-dollar ones, tells us this isn't a niche solution," Pesci said.

"It's becoming a standard part of how financial institutions communicate with the people they serve," he said.