Asset finance enters 2026 in a position that is, on the surface, reassuring. Global equipment and automotive finance markets continue to grow, and demand for financing remains resilient across most regions. Yet beneath this stability sits a more complex reality. Volatility has not disappeared; it has simply changed shape. Over the past year, asset finance organizations have had to contend with macroeconomic uncertainty, persistent inflation in some markets, shifting interest rate environments, supply chain disruption, rising cyber risk and increasingly assertive regulation. At the same time, technology capabilities, particularly in data, artificial intelligence and platform integration, have matured rapidly. What was experimental only a few years ago is now expected to operate at scale, under regulatory scrutiny and with measurable business impact.
This report explores how these forces are converging in 2026. It looks back at what 2025 revealed in practice, examines how regional dynamics are evolving and focuses on the strategic capabilities that will increasingly separate resilient asset finance organizations from vulnerable ones. The goal is not to predict the future with certainty, but to clarify where leaders should focus attention, investment and execution in the year ahead.
Looking back to move forward: What 2025 taught us
At the beginning of 2025, we published a similar report, looking ahead to the coming year. Our aim was to identify where digital and operational investments could deliver the greatest value. As the months unfolded, several of those themes were validated, while also exposing gaps between ambition and execution. One clear lesson was the growing importance of real-time data and dynamic decisioning. Organizations that invested in faster access to operational and portfolio data were consistently better positioned to identify risk earlier and respond to customer needs. This advantage extended beyond risk management into customer experience: faster decisions, clearer communications and more proactive servicing contributed to stronger loyalty and operational efficiency.
Another area that gained momentum was auditing and risk oversight, increasingly supported by advances in AI. Rather than relying solely on retrospective controls, leading firms began to embed continuous monitoring and automated checks into day-to-day operations. This shift reduced manual effort while improving transparency and governance. At the same time, growth remained steady. Equipment finance markets expanded by approximately 11%, while automotive finance grew by around 7%. Yet this growth occurred against a backdrop of turbulence. High interest rates in some regions, supply chain volatility, and geopolitical uncertainty created uneven conditions across markets and asset classes.
The key takeaway from 2025 is that growth alone is no longer a sufficient indicator of health. The organizations that performed best were those that combined scale with adaptability, using technology not simply to digitize existing processes, but to rethink how decisions are made and risks are managed.
Asset finance in 2026: What to expect
In 2026, the global asset finance industry will continue to balance growth opportunities against persistent structural headwinds. Demand remains supported by infrastructure investment, fleet renewal and the continued expansion of digital and used-asset financing. In several emerging markets, manufacturing relocation and industrial investment are driving increased demand for equipment and fleet finance, reinforcing the long-term role of asset finance in enabling real-economy growth.
At the same time, macroeconomic and geopolitical pressures are reshaping operating conditions. High interest rates, inflationary cost pressure and supply-chain disruption are increasing the cost of capital and extending delivery timelines for financed assets. Trade policy and tariff volatility continue to influence asset pricing, residual value assumptions and contract structures, particularly for cross-border transactions. As a result, growth in 2026 is expected to be uneven, with greater emphasis on disciplined execution rather than headline volume expansion.
Against this backdrop, many asset finance organizations are shifting focus from scale to resilience. In more mature markets, where demand growth is steadier, technology and automation are increasingly used to protect margins, improve decision quality and reduce operational friction rather than simply to drive origination volumes. Investments in workflow automation, data integration and analytics are helping firms respond faster to portfolio risk and operational disruption.
Risk management and funding strategy are also rising priorities. Firms are refining underwriting models, stress-testing portfolios against macro and supply-chain shocks and exploring alternative funding structures to improve balance-sheet flexibility. At the same time, customer expectations continue to evolve. Across regions, asset finance providers are expanding value-added services, such as fleet management, servicing and lifecycle support, to strengthen relationships and differentiate beyond price.
Overall, what to expect in 2026 is not a return to stability, but a more deliberate operating environment. Asset finance leaders will be required to navigate uncertainty with greater precision, combining selective growth with operational discipline, stronger risk frameworks and technology capabilities designed to manage complexity rather than assume uniform conditions.
Data as the operating system of asset finance
Data is increasingly becoming the foundation upon which almost every strategic capability is built. OEMs, captives, banks and specialist lenders have accumulated decades of data across origination, servicing, asset management and remarketing. Yet much of this data remains fragmented, locked in legacy systems, used primarily for hindsight rather than foresight.
More and more industry leaders are recognising that the challenge is not data availability, but data usability. Legacy architectures, inconsistent data models and poor integration are among the biggest barriers to improving decision intelligence.
Wholesale and floor plan asset finance providers typically hold five categories of high-value data:
- Contract and structural data, including contract terms, pricing curves, amortization schedules, collateral descriptions, residual assumptions and covenant structures
- Performance and servicing data, such as payment histories, delinquency patterns, restructurings, charge-offs, repossessions and recovery proceeds
- Customer and counterparty data, covering legal entity hierarchies, guarantors, sector classifications, credit scores, KYC artifacts and behavioral payment indicators
- Asset telemetry and lifecycle data, including telematics, IoT usage logs, utilization hours, maintenance records, condition reports and refurbishment outcomes
- Market and external signals, such as macroeconomic indicators, sector demand indices, secondary market pricing, auction results and used asset sale prices
Individually, these datasets offer limited insight. Combined, they enable predictive analytics, early-warning systems, and more accurate pricing and exposure management.
For wholesale and floor plan asset finance providers, translating this potential into results requires a clear focus on execution. This starts with prioritising the data sources that matter most across core operations, particularly origination and servicing, rather than attempting to integrate everything at once. Fragmented datasets should be consolidated into a governed, cloud-based platform capable of supporting analytics at scale.
On this foundation, firms should develop a small number of high-impact models, notably early portfolio risk-warning indicators and residual value predictors. Critically, these insights must be embedded directly into operational workflows through alerts, dashboards and triggers, enabling proactive intervention rather than retrospective analysis.
The impact of this approach is measurable. Predictive analytics have been shown to improve forecast accuracy by 20–25%, while data-driven automation initiatives have dramatically reduced governance and control testing time in mature implementations.
In asset finance in 2026, the strategic use of data is no longer optional. It is foundational to resilience, profitability and competitive relevance.
Personalization at scale: Monetising intelligence
As data foundations mature, asset finance organizations are moving beyond efficiency gains toward personalization as a source of differentiation and value creation. Historically, many lenders have relied on standardized products and pricing. While simple to manage, this approach increasingly fails to meet customer expectations and leaves value on the table. The long-standing industry benchmark of 80% customer satisfaction is now widely viewed as insufficient, as it implies that one in five customers is underserved and at risk of churn.
With a unified view of customer behavior, asset usage and contract history, organizations can move from “one-size-fits-all” to tailored experiences across the asset lifecycle.
Personalization is emerging across three dimensions in the asset finance industry:
- Contract renewals, refinancing and behavioral triggers. Near end-of-term, data can identify low-risk, high-loyalty customers and trigger targeted renewal or refinancing offers. Conversely, higher-risk customers can be deprioritized, reducing unprofitable retention efforts. Historical remarketing data and asset condition information enable more accurate residual assumptions and tailored end-of-term options.
- Tailored engagement and servicing. Pricing, fees and service bundles can be dynamically adjusted based on risk profile, asset type and customer behavior. Digital interactions, such as portal usage or quote requests, can trigger timely, relevant offers rather than generic campaigns. Communication channels and content can be aligned with customer preferences and lifecycle stage.
- Asset-centric personalization. Telemetry and maintenance data allow lenders to detect under-utilized or ageing assets and proactively propose upgrades, extensions or service packages. These interactions are grounded in asset reality rather than static assumptions.
The results speak for themselves. Organizations using personalized offers and recommendation engines report 20–30% higher engagement than generic approaches, alongside improvements in satisfaction, retention and margin.
In 2026, personalization is no longer a marketing concept. It is a commercial and risk management lever that turns data intelligence into measurable financial outcomes.
Cybersecurity and operational resilience as balance-sheet risks
The past year underscored how cyber incidents can cascade across supply chains, disrupting manufacturers, dealers, service providers and the financiers that support them. A series of high-profile attacks on shared technology platforms and critical service providers demonstrated how a single breach can halt operations across entire ecosystems, even where individual firms were not directly targeted. These events have shifted cybersecurity from a technical concern to a strategic and financial risk, with implications for business continuity, third-party concentration and regulatory scrutiny.
Regulators have responded by strengthening expectations around operational resilience, third-party oversight and incident response. In 2026, asset finance organizations can expect greater scrutiny of vendor contracts, concentration risk, recovery planning and governance frameworks. Incident reporting timelines are tightening, and boards are increasingly expected to demonstrate active oversight of cyber posture.
Safeguarding priorities now extend well beyond perimeter defenses. They include:
- Robust third-party and vendor risk management
- Clear continuity planning and recovery time objectives
- Network segmentation and zero-trust architectures
- 24/7 monitoring, incident response playbooks and crisis communications
- Regular testing of recovery processes and data encryption
- Reassessment of cyber insurance coverage
- Board-level cyber KPIs and governance
The financial stakes are significant. The global average cost of a data breach remains in the millions, with even higher impacts in certain regions. Beyond direct costs, reputational damage can erode trust quickly and persist long after systems are restored.
In asset finance in 2026, cybersecurity investment should be viewed not as a cost center, but as insurance against existential risk. Resilient organizations will be those that treat operational continuity as a core component of financial performance.
AI moves from advantage to necessity
Artificial intelligence is no longer experimental in asset finance. In 2026, it is becoming a fundamental capability that reshapes credit assessment, portfolio monitoring and operational efficiency.
AI adoption is concentrating in three high-impact domains:
- Credit decisioning. AI models now ingest unstructured data, financial statements, invoices, contracts, and extract signals that traditional scorecards miss. This reduces time to decision while improving accuracy, particularly in complex commercial cases.
- Predictive analytics. Static risk models are giving way to continuously recalibrated approaches that combine behavioral, operational and macroeconomic data. These models support dynamic pricing, provisioning and exposure management at contract and portfolio levels.
- Dealer and fleet scoring. AI enables counterparty-level risk views by combining sales volumes, charge-off history, telematics, OEM health indicators and market data. This allows differentiated limits and pricing, reducing concentration risk.
At the same time, regulatory scrutiny is increasing. Frameworks such as the EU AI Act emphasize explainability, transparency and governance. Organizations are responding by formalising AI governance, maintaining model inventories, monitoring model drift, and ensuring human oversight of high-impact decisions to preserve trust with customers and regulators.
By the end of 2026, the question will no longer be whether to adopt AI, but how effectively it is governed and embedded into daily operations. The firms that succeed will be those that combine advanced models with strong data foundations, clear accountability and AI systems designed to support, rather than replace, human judgement.
“The challenge is not data availability, but data usability, bringing siloed data together in a way that enables explainable, secured, sovereign AI insights and action, under full human control.”
Hani Hagras, Chief Science Officer and Global Head of AI at SBS, speaking at the 2025 SBS Summit
Technology platforms: Integration beats consolidation
Technology consolidation will continue to reshape the asset finance ecosystem in 2026. Vendor acquisitions are reducing choice and, in some cases, forcing lenders onto unified platforms they did not originally select. Research shows that many CIOs are actively consolidating their technology estates to reduce complexity and cost, with 20% saying they are looking to reduce the number of suppliers they work with.
The primary concern is untested platform convergence. Large end-to-end platforms often promise simplification, but can dilute specialist wholesale and floorplan functionality, slow innovation and reduce responsiveness to regulatory change. For firms operating across multiple asset classes and geographies, migrations driven by vendor roadmaps rather than business need remain a persistent risk.
As a result, many organizations are questioning whether platform scale alone delivers resilience. Proven integrations between specialist providers are increasingly viewed as a more durable alternative. Mature partnerships allow lenders to modernize incrementally, integrate advanced capabilities such as analytics and AI and adapt to market change without committing to wholesale platform replacement. When integrations are well governed, this approach preserves flexibility while still delivering operational efficiency.
Cloud-native architectures support this shift by enabling scalability, resilience and faster deployment of new functionality. However, cloud adoption does not eliminate complexity on its own. Managing multiple vendors requires strong architectural discipline, clear data ownership, and explicit exit and portability provisions in vendor contracts. Without this, composable architectures can introduce risks similar to the monolithic platforms they aim to replace.
In 2026, the technology challenge is not choosing between consolidation and flexibility, but balancing the two deliberately, simplifying where scale adds value while retaining the ability to adapt as market conditions change.
Collaboration over consolidation
SBS and Vero Technologies’ partnership illustrates how proven integrations can offer an alternative to large-scale platform replacement in wholesale finance. Rather than converging multiple functions into a single monolithic system, the integrated solution combines SBS’s wholesale finance capabilities with Vero’s digital front end.
Together, the platforms support dealer onboarding, credit evaluation, funding, inventory auditing and risk monitoring through a modular architecture. For small and mid-sized lenders, this approach demonstrates how organizations can modernize and scale core operations incrementally, while avoiding the disruption and execution risk associated with untested platform consolidation. Learn more about the collaboration between SBS and Vero Technologies.
Cross-border capabilities
Cross-border origination and portfolio expansion are expected to accelerate through 2026, driven by supply-chain realignment, nearshoring and uneven regional growth. Markets such as India and Mexico continue to attract manufacturing investment, increasing demand for equipment and fleet finance. At the same time, geopolitical fragmentation is reshaping cross-border risk, with tariffs and export controls affecting asset costs and delivery timelines.
Recent tariff actions in major economies have pushed import duties to levels not seen in decades, with some sectors experiencing sub-component cost inflation of 15–30%. These pressures directly affect pricing, residual assumptions and deal economics. Increasingly, assets are sourced in one jurisdiction, deployed in another and remarketed elsewhere, amplifying legal and operational complexity.
As a result, cross-border considerations are moving earlier in the credit lifecycle and becoming embedded across core operating processes:
- Originations. Underwriting models are evolving to reflect landed-cost inflation, delivery lead-time risk, supplier concentration and the practical mobility of collateral across borders.
- Collateral and asset lifecycle. Firms are placing greater emphasis on monitoring secondary markets across jurisdictions and understanding repossession, enforcement, and regulatory constraints that may affect recovery and remarketing outcomes.
- Contract design. Cross-border agreements increasingly include multi-country security structures, clear governing-law provisions, multilingual documentation where required, currency and hedging clauses, and flexibility to shift remarketing markets if conditions change.
- Pricing and structuring. Many organizations are building buffers for tariff volatility and supply-chain disruption, shortening tenors, increasing down payments, or reassessing residual values more frequently to protect margins.
- Partner network and platforms. Global remarketing networks, cross-border servicing partners, logistics providers, and digital platforms that provide asset location and condition visibility are becoming critical enablers of scalable cross-border activity.
- Risk monitoring. Leading firms are developing geopolitical and trade-policy dashboards, stress-testing portfolios for tariff shocks or supply-chain rerouting scenarios, and tracking exposure concentrations by geography, supplier and asset type.
Taken together, these shifts signal a change in how cross-border activity is approached. Rather than extending domestic lending models into new markets, asset finance organizations are increasingly designing cross-border capability deliberately, aligning underwriting, structuring, asset management and partner ecosystems from the outset.
As assets move more frequently across borders over their lifecycle, visibility and control become critical. Firms that lack clarity on asset location, recovery options or remarketing routes risk margin erosion when conditions change.
In 2026, cross-border capability is less about expansion and more about maintaining control under persistent uncertainty.
Executing with control in modern asset finance
As asset finance moves into 2026, the defining challenge for industry leaders is no longer whether growth opportunities exist, but how consistently and safely they can be executed. Volatility has not disappeared; it has become more fragmented, more interconnected and more difficult to manage through traditional, siloed operating models.
Across data, AI, cybersecurity, technology platforms and cross-border activity, a common requirement is emerging: asset finance organizations need integrated, governed foundations that allow them to respond quickly without sacrificing control. Capabilities that once sat at the edge of operations, advanced analytics, automated decisioning, real-time risk monitoring, must now be embedded into day-to-day workflows if they are to deliver sustained value.
This shift places renewed emphasis on core platforms. Fragmented systems and bespoke integrations make it difficult to scale intelligence, enforce governance or adapt operating models as conditions change. By contrast, platforms designed to support multiple asset classes, geographies and business models within a single, coherent framework can help organizations simplify complexity while preserving flexibility.
SBS Financing Platform reflects the direction the industry is moving: toward modular, cloud-based foundations that unify data, processes and controls across the asset finance lifecycle. The relevance of such platforms lies not in technology alone, but in their ability to support disciplined execution, enabling organizations to embed intelligence into operations, govern advanced models responsibly and manage risk across increasingly interconnected ecosystems.
Ultimately, 2026 will reward asset finance leaders who invest with intent. Those that align strategy, governance and technology around a clear operating model will be better positioned to navigate uncertainty, protect portfolio performance and convert complexity into a durable competitive advantage.
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