The financial technology sector is witnessing a significant shift as legacy infrastructure faces the disruptive pressure of generative artificial intelligence. Fuse, a startup developing an AI-native loan origination system (LOS), announced on Monday that it has successfully raised $25 million in a Series A funding round. The investment was led by Footwork, with participation from Primary Venture Partners, NextView Ventures, and Commerce Ventures. This capital infusion marks a pivotal moment for the company as it seeks to overhaul the aging technological foundations of the American credit union industry, which has long been hampered by inflexible and expensive software solutions.

Founded by Andres Klaric, a Bolivian entrepreneur, and Marc Escapa, an immigrant from Spain, Fuse represents a strategic pivot from the duo’s previous venture. For three years, the co-founders operated an automotive lending startup, an experience that provided them with a front-row seat to the inefficiencies of traditional lending software. They realized that the true bottleneck in the industry was not the lack of capital or demand, but the antiquated systems of record—the loan origination systems—that manage the lifecycle of a loan from application to disbursement.

The Critical Role of Loan Origination Systems in Modern Finance

To understand the impact of Fuse’s entrance into the market, one must first understand the central role of a Loan Origination System (LOS). In the banking and credit union sectors, the LOS is the primary system of record. It is the digital engine that handles every step of the lending process: intake of borrower information, credit pulls, debt-to-income calculations, underwriting, compliance checks, and the final approval or denial of credit.

Despite their importance, traditional LOS platforms are often cited as the greatest source of friction for financial institutions. Legacy systems, such as those provided by publicly traded nCino or private-equity-backed MeridianLink, often require extensive manual data entry and are built on rigid architectures. According to Andres Klaric, integrating these legacy systems can take upwards of a year, and they typically involve multi-year contracts that are prohibitively expensive for smaller institutions. This "vendor lock-in" has historically prevented credit unions from adopting more agile, modern technologies, leaving them at a disadvantage compared to large national banks and digital-first fintech lenders.

A Strategic Shift: From Automotive Lending to AI Infrastructure

The journey of Fuse began in 2023 when Klaric and Escapa recognized that Large Language Models (LLMs) had reached a level of sophistication that could solve the specific pain points of the lending industry. Their previous venture in automotive lending had exposed them to the frustrations of working within the constraints of legacy software. They saw an opportunity to build a "clean sheet" solution—a system designed from the ground up to leverage the capabilities of AI rather than simply layering AI on top of old code.

By transitioning to an AI-native architecture, Fuse aims to automate the most labor-intensive parts of the lending process. Traditional underwriting involves a human loan officer manually reviewing pay stubs, tax returns, and bank statements to verify income and assets. Fuse’s platform uses AI agents to ingest and analyze this unstructured data in seconds, significantly reducing the time it takes to reach a credit decision. This efficiency allows lenders to process higher volumes of loans without a corresponding increase in headcount, effectively lowering the operational cost per loan.

The Five Million Dollar Rescue Fund and Market Entry Strategy

One of the most significant barriers to entry in the LOS market is the prevalence of long-term contracts. Many credit unions are currently tied to legacy providers through agreements that have years remaining. To address this, Fuse has launched a bold market strategy: a $5 million "rescue fund."

This program is designed to facilitate the transition for credit unions that are dissatisfied with their current providers but cannot afford to pay double for software during a transition period. Fuse is offering the first 50 qualifying institutions free access to its platform until their existing contracts with legacy vendors expire. Klaric has emphasized that this is not a mere marketing gimmick but a necessary intervention to break the cycle of technological stagnation. By subsidizing the "switchover" period, Fuse is lowering the financial risk for credit unions to modernize their stacks.

This strategy targets a massive but underserved segment of the financial market. Currently, there are over 4,000 credit unions in the United States, serving millions of members, particularly within the middle class. These institutions often possess strong local brand loyalty and physical branch networks but lack the digital tools to compete with the seamless user experiences offered by "Big Tech" finance.

Investor Perspectives and the ERP Comparison

The Series A round was driven by the conviction that the LOS is the "operating system" of the credit union. Nikhil Basu Trivedi, a co-founder and general partner at Footwork, noted that the technology used by these institutions is long overdue for a comprehensive overhaul. He compared the LOS to an Enterprise Resource Planning (ERP) system or a Customer Relationship Management (CRM) tool, noting that it is just as vital to daily operations.

"We know the credit unions are really hurting and want to adopt AI, but have no idea how to do it," Basu Trivedi told TechCrunch. The investment thesis relies on the belief that while swapping out a core system of record is traditionally difficult, the speed and ease of integration offered by Fuse’s AI-native platform change the equation. This follows a broader trend in the venture capital landscape where "AI-first" replacements for traditional ERP and general ledger systems—such as the startup Rillet—are attracting significant funding by promising to automate complex back-office functions.

Competitive Landscape and Industry Implications

Fuse enters a competitive field where it must contend with both established giants and emerging startups. Its primary targets for displacement are nCino and MeridianLink, companies that have dominated the market for years. However, Fuse is not alone in its quest to modernize lending. Other startups, such as Casca and Glide, are also developing AI-enhanced loan origination tools.

The differentiation for Fuse lies in its deep focus on the credit union sector and its mission-driven approach. Klaric has expressed a strong commitment to helping these institutions reduce costs, arguing that credit unions are uniquely positioned to win if they are given the right tools. Because they are member-owned and focused on local communities, they often provide better member experiences than large commercial banks. Modernizing their technology allows them to maintain that personal touch while offering the speed and convenience that modern consumers expect.

Technological Foundations: How AI Transforms Underwriting

The core of Fuse’s value proposition is its use of LLMs to handle the "unstructured" portion of a loan application. In a traditional setting, a loan application is a mix of structured data (credit scores, social security numbers) and unstructured data (scanned documents, employer letters, explanations of credit dings). Legacy systems struggle with the latter, requiring human intervention to bridge the gap.

Fuse’s AI agents are trained to interpret these documents with high accuracy, identifying anomalies and verifying data against third-party sources. This doesn’t just speed up the process; it also improves the quality of underwriting. By analyzing a broader set of data points more consistently than a tired human loan officer might, the system can help credit unions identify creditworthy borrowers who might have been overlooked by rigid, traditional scoring models.

Broader Economic Impact and Future Outlook

The modernization of the credit union sector has implications that extend beyond the balance sheets of fintech startups. Credit unions are a vital source of credit for the American middle class, providing mortgages, auto loans, and personal lines of credit. When these institutions operate more efficiently, they can offer more competitive interest rates and expand access to credit for their members.

As interest rates remain a central focus of the global economy, the ability of lenders to operate with lower overhead becomes a competitive necessity. The $25 million raised by Fuse will be used to scale its engineering team, expand its customer support for the "rescue fund" participants, and continue refining its AI models.

In the long term, the success of Fuse could signal a broader trend of "vertical AI" replacing general-purpose legacy software. By focusing on a specific, highly regulated, and technologically underserved niche, Fuse is positioning itself as a critical infrastructure provider for the next generation of community banking. The transition from legacy systems to AI-native platforms is no longer a matter of "if" but "when," and with its new capital and aggressive market strategy, Fuse is aiming to lead that transition.