Finomnia, the EU-based banking software group formed in January 2026, is embedding AI agents directly into its lending platforms to automate underwriting, back-office workflows, and compliance monitoring. The company, which generates €200 million in annual revenue and powers more than 60% of Italy's consumer credit turnover, now plans to take that AI-driven model to Latin America, with Mexico as its primary target.
From fragmented units to a unified brand
The consolidation under the Finomnia name followed a strategic investment cycle launched in 2023 by majority investor Apax funds. After carving out a dedicated banking software division from Lutech and acquiring several companies across the lending value chain - OCS, Finwave, Quid, altermAind, and Alvantia - the group unified operations in January 2026. "This allowed us to reinforce our presence as a premier EU software provider and establish a cohesive identity to accelerate our expansion across the European Union and the Americas," said CEO Andrea Pettinelli.
Finomnia now operates through four core business units and a specialized AI joint venture, altermAind, established with Italian digital bank illimity. Its platforms handle consumer finance, factoring, corporate lending, mortgages, leasing, and non-performing loan management. The corporate lending unit runs on a cloud-native platform already adopted by two of the EU's largest banking groups.
Mexico's fintech surge creates software demand
Pettinelli described Latin America as both a natural evolution and a strategic imperative. The earlier acquisition of Alvantia provided an operational bridge and shared language capabilities with Spanish banking groups active in the region. Mexico's GDP, he said, approaches that of major EU nations, but unlike the mature European market, it offers greenfield expansion. "Rapidly growing financial institutions in Mexico require scalable, enterprise-grade platforms to navigate their next stage of development," he said, "making the region exceptionally receptive to core technology modernization."
The capital flows support that view. In the first half of 2026, Mexico surpassed Brazil in fintech investment for the first time in a decade. Pettinelli said the surge is driving demand from two segments: agile fintech entrants that need flexible, debt-free core software, and traditional banks shifting budgets away from legacy IT maintenance toward AI initiatives.
AI agents and the "agentification" roadmap
Finomnia commits roughly €20 million annually to R&D. Its current product strategy centers on building a layer of AI agents on top of its existing software suite. One co-development project with a major EU financial institution is deploying AI agents to automate manual back-office tasks in personal loan underwriting and management. The company is also integrating conversational AI assistants across its platforms for natural language navigation of system documentation, training materials, and database queries.
On the regulatory side, Finomnia has built governance software that monitors compliance with the European Union AI Act and provides tools to track generative AI compute costs. Internally, the company is embedding AI across its entire software development lifecycle - from business requirements analysis through coding, testing, and application management - targeting a 15% efficiency gain over the next 18 months. For banks integrating these tools alongside legacy systems, Finomnia uses microservices and standard APIs, plus a connection layer built on the Model Context Protocol (MCP) that lets client-developed AI agents communicate directly with core applications.
Profitability shifts technology priorities
As fintechs pivot from user growth to profitability, Pettinelli said technology spending must tie directly to P&L impact. "CEOs and CFOs no longer support technology investments purely for modernization; every initiative must demonstrate clear top-line expansion or operational cost reduction." That means prioritizing core business systems over non-essential administrative platforms.
Finomnia's software manages the full credit lifecycle - automated underwriting, loan administration, debt collection, and non-performing loan management. Pettinelli argued that improving risk decisioning directly boosts portfolio margins, while automated back-office workflows cut operational costs per loan. This focus on core banking functions, rather than internal support tools, positions the company for the efficiency-driven environment he described.
On workforce preparation, Pettinelli recommended that executives dismantle technological silos and create rotational talent pools where developers work across diverse technologies and projects. "This cultural shift must be backed by tangible corporate investments in professional development and modern tools, including enterprise AI licenses," he said.
Why this matters for finance professionals
When a software provider that handles 60% of a major EU country's consumer credit volume shifts its product strategy toward AI Agents & Automation, the operational benchmarks for lending institutions change. Finance leaders evaluating core system upgrades should expect vendors to show how AI layers deliver measurable cost reduction - not just feature announcements. The Mexico expansion also signals where infrastructure spending is concentrating, as traditional banks reallocate budgets from legacy maintenance to AI-driven core modernization. For teams working in credit operations, underwriting, or compliance, the message is direct: manual back-office workflows are becoming a competitive liability.
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