“The real impact of Artificial Intelligence on the financial sector does not depend on how sophisticated the algorithm is, but on the technology architecture it is deployed on. Financial institutions that move their platforms to API-first, modular models will be the only ones able to use AI at predictive scale; otherwise, the investment will be diluted in isolated efforts.” – Ignacio Olivera, Country Manager, Basikon

Mexico's leasing boom calls for new technology platforms to make the most of AI

Article by Ignacio Olivera, Country Manager at Basikon, published in Spanish in Crevolution Magazine (year 6, issue 4, September 2026, page 46).

The steady growth of the leasing and vehicle leasing market in Mexico is making operations more complex for financial institutions. Data-driven technology modernization is the key to keeping up.

Leasing in Mexico is establishing itself as one of the most dynamic engines of asset finance and business mobility. According to consolidated data from the Mexican Association of Automotive Distributors (AMDA) and the Mexican Association of Vehicle Lessors (AMAVe), leasing of new light vehicles grew by a solid 24.4%, making operating leases a force that already accounts for 16.1% of the country's total fleet market.

The shift towards sustainability has also picked up pace: in the first quarter of 2026, acquisitions of hybrid and electric vehicles under leasing models rose by a record 65.2%. This momentum puts the Mexican car leasing market on track for annualized growth of close to 6.5% over the next decade.

• 24.4%: growth in leasing of new light vehicles (2025 vs. 2024)
• 16.1%: share of Mexico's total fleet market
• 65.2%: growth in acquisitions of hybrid and electric vehicles (Q1 2026 vs. Q1 2025)

This fast growth, however, translates directly into greater operational complexity. Traditional portfolio management platforms no longer just process payments; they now have to connect vehicles, users, insurers, telematics systems, GPS devices and funders in a single, real-time operating environment. Manual workflows and disconnected legacy systems quickly become bottlenecks that raise operational risk, limit portfolio scalability and slow down response times in origination and collections.

AI as a catalyst for efficiency in portfolio management

Artificial Intelligence brings unprecedented capabilities to automate workflows, monitor assets in real time and support decision-making in high-volume portfolios. In credit and leasing, generative AI and predictive models make it possible to deliver:

• Hyper-personalized interactions: improve customer service and early-stage collections through automated digital channels.
• Risk mitigation: reduce the administrative workload through intelligent reading of contracts, financial statements and identity verification (KYC).
• Predictive behavior models: anticipate claim patterns or late payments by cross-referencing asset usage data with macroeconomic variables.

Despite these advantages, for AI to move from an informational tool to a force for execution, it needs a unified and reliable data environment. If AI models are not connected to core operating systems and up-to-date databases, they cannot trigger autonomous workflows or resolve operational issues as they arise.

API-based architecture: flexibility and risk mitigation

To meet the challenges of the Mexican market, modernizing the core systems of leasing companies can no longer wait. Financial institutions can no longer operate with information silos where data is scattered across private clouds and local servers, blocking access to key metrics in real time.

The move to 100% API, modular and low-code platforms breaks down these barriers. This open-architecture approach makes native integration with advanced analytics tools easier and simplifies adding AI agents dedicated to automating collections or monitoring vehicles technically. A clear example of this model in high-growth markets shows that API-connected platforms let finance companies scale their lending volume within months, while keeping precise control over their customers' payment behavior and the physical condition of their productive assets.

Where should industry leaders aim?

Future-ready leasing companies in the region are already designing their technology strategies around open connectivity protocols for AI (such as the Model Context Protocol, or MCP). This structured and secure approach connects language models natively to the institution's internal portfolio data.

The advantage of API-first systems is their modularity: they allow a progressive transformation. Finance companies do not need to replace their entire core system overnight, a process that usually creates a lot of operational friction. The change can start by automating critical processes with immediate high value, such as preventive collections workflows, digital origination or automated regulatory reporting.

Technology is evolving faster and faster in LATAM. The strategic priority for Mexican lessors today is to make sure their operating platforms are connected, standardized and ready for large data flows before deciding which AI software to buy. Otherwise, trying to implement Artificial Intelligence on an obsolete system is like buying a latest-generation vehicle without the electronic key to start it.

This logic of progressive modernization is already a reality in other markets: platforms such as Basikon, with a 100% API and modular core, let leasing institutions integrate AI agents on a unified database without replacing their core systems all at once. This experience offers a concrete reference for Mexican lessors to move towards the same connectivity standard the industry now demands.

In line with this, Basikon has real use cases in leasing and vehicle leasing where customers have natively connected their AI models (under standards such as MCP) without having to replace their core system overnight. This lets them move forward progressively, starting with the processes that have the most immediate impact, and reduce their operating costs.

Read the full issue Crevolution Magazine, September 2026 (digital edition, PDF, in Spanish): the article is on page 46.

Sources (in Spanish)

• Asociación Mexicana de Distribuidores de Automotores [AMDA]. (9 February 2026). Arrendamiento vehicular de ligeros subió 24.4% y pesados bajó 16.6% durante 2025. AMDA Notas de Prensa.
• Asociación Mexicana de Distribuidores de Automotores [AMDA] and Asociación Mexicana de Arrendadoras de Vehículos [AMAVe]. (2026). Avance de 65.2% en la compra de vehículos ligeros híbridos y eléctricos nuevos como activos por arrendadoras al primer trimestre de 2026. Reporte de Comercialización y Arrendamiento.

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