For community banks and credit unions, collecting a loan payment can still depend on a borrower opening an app, signing into online banking or calling the institution. MessagePay is betting that a simpler interaction—sending a text—can change that workflow. The digital payments company has now reached 400 financial institution customers while adding AI-powered predictive analytics designed to help collections teams decide which borrowers require attention and when.

MessagePay Expands Conversational Payments With AI-Powered Collections

MessagePay has signed its 400th financial institution customer, marking a growth milestone for the payments technology provider focused on credit unions and community banks.

The company said it added 86 new credit unions and community banks through August 2026. More significant from a technology perspective, however, is the expansion of its platform into two areas that are increasingly converging across financial services: conversational payments and AI-assisted collections.

MessagePay’s core platform allows financial institutions to communicate with borrowers and collect payments through text messaging, web, phone and email. Borrowers can use a secure payment link or respond directly within a text conversation rather than downloading a dedicated application or logging into online banking.

That approach puts payment functionality into an existing communication channel instead of asking consumers to navigate another banking interface.

The company has also expanded its two-way messaging capabilities through MessagePay Direct, which is designed to give financial institutions a more direct way to resolve payment issues with borrowers over text.

The larger development is AI Pay+, an AI-powered predictive analytics capability aimed at asset-recovery and collections teams.

Rather than treating every delinquent account according to the same traditional delinquency bucket, AI Pay+ analyzes borrower behavior to forecast when and how a borrower is likely to make a payment. Collections teams can then use those predictions to segment portfolios and prioritize accounts that may require human intervention.

In practical terms, the technology is attempting to answer a familiar banking question: which account should a collections employee contact next?

That distinction is important. AI in financial services is increasingly moving away from standalone experimentation and toward workflow-specific applications where predictive models can influence operational decisions. Collections is one such area because financial institutions already have large volumes of historical payment and borrower data that can potentially be used to identify patterns.

MessagePay’s model is also different from the consumer-facing payment apps that dominate much of the digital-payments conversation. The company is selling infrastructure to financial institutions rather than attempting to become another destination wallet or banking application.

Its customer base ranges from credit unions with about $10 million in assets to banks managing more than $20 billion, according to the company. MessagePay says its platform supports more than 30 core and third-party integrations, including Fiserv, Jack Henry, Corelation, CU Answers and Flex.

That integration layer could be particularly important for smaller institutions.

Replacing a core banking system is expensive and disruptive, while adding a specialized payment or communications layer can be a more manageable technology investment. MessagePay’s integration strategy therefore reflects a broader fintech pattern: specialized vendors are building around established banking cores rather than trying to displace them.

The company said its Fiserv integrations have also enabled community banks to connect to MessagePay during 2026. For institutions already operating on a major core platform, integration availability can be as important as the capabilities of the fintech product itself.

Why Conversational Payments Matter

The move toward conversational payments is part of a larger shift in digital financial services. Payment experiences are increasingly being embedded into software, messaging channels and other environments where customers already spend time.

The Federal Reserve’s latest payments study found that U.S. consumers and businesses made 236.6 billion noncash payments in 2024, more than three times the volume recorded in 2000. Cards represented more than three-quarters of those payments by number, while ACH accounted for almost three-quarters by value.

The data illustrates the scale of the underlying transition: payments are no longer confined to traditional banking interactions. Financial institutions are competing to make transactions faster, easier and less dependent on manual processes.

For community banks and credit unions, the challenge is often resources. Large institutions can build sophisticated digital experiences internally or through multiple technology vendors. Smaller institutions need solutions that work with existing infrastructure and can demonstrate a clear operational benefit.

MessagePay is targeting that gap.

The company’s combination of borrower communications, payment collection and predictive analytics creates a workflow that extends from customer contact to payment execution to collections prioritization.

That does not necessarily make the platform unique. Banks and credit unions can assemble comparable capabilities from payment processors, digital-banking providers, customer-communications platforms and analytics vendors. Larger institutions may also have the resources to build proprietary predictive collections systems.

MessagePay’s potential advantage is integration: putting those functions into a single specialized platform designed around community financial institutions.

What Banks Should Consider Before Adoption

For enterprise teams evaluating AI-enabled collections technology, the important question is not simply whether a model can predict payment behavior.

Financial institutions also need to understand what data the system uses, how predictions are generated, how borrower communications are governed and where human review remains necessary.

That is particularly relevant when AI influences collections activity. A predictive model that determines which borrowers receive additional outreach can affect customer treatment, operational priorities and potentially regulatory risk.

Data security, consent for text communications, auditability, model governance and integration with existing loan-servicing systems should therefore be part of any procurement process.

MessagePay’s 400-customer milestone suggests demand for technology that makes payments more convenient without requiring institutions to rebuild their banking infrastructure. Its AI expansion points to the next stage: using the same digital payment infrastructure to make back-office financial operations more predictive.

For community financial institutions, that combination may ultimately be more consequential than the payment link itself.

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Market Landscape

The U.S. payments market is becoming increasingly fragmented across cards, ACH, instant payments, digital wallets and embedded payment experiences. McKinsey expects global payments revenue to reach approximately $3 trillion by 2029, while highlighting pressure from lower-cost account-to-account transfers, digital wallets and platform-driven payment experiences.

The infrastructure supporting U.S. financial institutions is changing as well. The Federal Reserve reported that 1,192 institutions—including large banks, community banks and credit unions—had joined FedNow by the end of 2024, up 33.5% from the previous year.

This creates a competitive environment in which banks increasingly need to support multiple payment experiences while maintaining existing core systems.

AI adds another layer. McKinsey estimates that fintech companies generated approximately $650 billion in global revenue in 2025, with payments remaining one of the industry’s largest verticals while AI-enabled fintech becomes an increasingly important growth category.

MessagePay’s positioning sits at that intersection: specialized fintech infrastructure connecting payments, borrower communications and AI-powered operational analytics.

Top Insights

• MessagePay has reached 400 financial institution customers while expanding conversational payments and AI-driven collections technology for community banks and credit unions.
• AI Pay+ analyzes borrower behavior to predict payment patterns, helping collections teams prioritize accounts requiring human intervention instead of relying solely on delinquency categories.
• MessagePay Direct extends two-way borrower communication through text, connecting payment resolution with digital customer-service workflows for financial institutions.
• More than 30 core and third-party integrations position MessagePay as an infrastructure layer that works alongside established banking systems rather than replacing them.
• The platform reflects fintech’s shift toward embedded payment experiences and specialized AI workflows as banks modernize customer-facing and operational financial processes.

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