Urgent context: why lending is facing a structural break
Lending is approaching an inflection point that feels less like a technology upgrade and more like a redistribution of power. Origination economics are moving to whoever owns the customer moment and the best decision signals. Embedded distribution is pulling credit inside platforms and enterprise workflows at scale, with the embedded finance market projected to grow from about US$146.17B (2025) to about US$690.39B (2030). At the same time, digital platforms are expanding the addressable origination surface, while regulators and market infrastructures are pushing consent-led portability and stronger customer data rights.
For bankers, the urgency is direct: lending is no longer “won” only through balance sheet scale, branch reach, or pricing power. It is increasingly won where data is fresh, journeys are native, and risk can be priced and controlled in near real time. Our perspective below outlines how lending in 2026 is being reshaped by a set of reinforcing shifts across underwriting, distribution, data rights, and product design, and what banks must do to protect control, economics, and risk stewardship as credit moves deeper into digital ecosystems.
Authors:
Vani Vangala, Product Business Manager, Infosys Finacle
Pushkal Kapila, Senior Member - Marketing, Infosys Finacle
Embedded Lending and Orchestration
Embedded lending is becoming a primary distribution battleground as origination shifts into commerce ecosystems. Marketplaces, payment processors, logistics platforms, and ERPs can surface credit at the point of need and underwrite using operating signals such as sales velocity, fulfilment reliability, disputes, and inventory turns. For banks, the choice is clear: participate as the regulated risk steward within these ecosystems or cede origination ownership to players that control workflow and data. Winning requires bank-grade governance embedded into partner journeys - explicit consent, accountable decision logic, and consistent risk standards.
As lending becomes increasingly ecosystem-driven, differentiation shifts from managing integrations to delivering end-to-end orchestration. Banks must coordinate data ingestion, underwriting, product rules, documentation, fraud checks, disbursement, servicing, and collections across systems and partners while maintaining compliance and auditability. Most failures occur in exceptions - disputes, retries, reconciliations, and control breaks. Orchestration is therefore both capability and discipline: workflow and decision orchestration, policy-as-code, standardized decision data with consent-led ingestion, unified observability, and closed-loop feedback from outcomes into models and rules. Banks that build this layer scale faster, with fewer control surprises and stronger unit economics.
Working Capital as the Growth Engine
Working capital is moving from a product segment to a growth engine as platform-native workflows expand across procurement, invoicing, logistics, and treasury. For lending, the near-term opportunity is working-capital finance, with supply chain finance increasingly acting as a scalable vehicle because it links credit to verified transaction events across buyers, suppliers, and platforms. As invoices, receivables, and supply-chain milestones digitize, credit can be triggered, resized, and secured closer to real economic activity. This includes payables finance anchored on approved invoices, receivables finance linked to shipment and acceptance signals, and inventory-backed structures tied to logistics visibility, improving speed and reducing friction.
Programmable finance infrastructure strengthens this shift. Concepts such as unified ledgers and tokenised assets point to a future where collateral and settlement are more verifiable and machine-actionable, enabling contingent execution and smoother settlement. Banks do not need to commit to a single tokenization model. They do need readiness for programmable working-capital and supply chain credit patterns: event-driven posting, clean collateral lineage across receivables and inventory, tighter fraud and duplicate-financing controls, and architectures that support real-time triggers and multi-party workflows.
AI Augmenting Credit Decisioning and Underwriting Models
By 2030, leading credit engines will behave less like periodic assessment factories and more like always-on risk systems. GenAI and agentic AI compress evidence gathering, analysis, and decision workflows, while improving early-warning detection and portfolio surveillance. McKinsey’s 2025 research with IACPM found 52% of institutions had positioned GenAI adoption as a priority, with use cases spanning credit decisioning, early warning systems, and credit memo drafting.
The 2026 pivot is moving from pilots to an AI-enabled underwriting model that is measurable and defensible. Banks will need clear policy guardrails, model risk controls, explainability and audit trails, and defined human checkpoints for accountability. The winners will not simply approve faster. They will price more precisely, detect deterioration earlier, and continuously steer portfolio growth without weakening governance.
Product Catalog to Product Factory
As distribution shifts, lending products must be configured in the context of the customer journey, not selected from a static catalog. In embedded channels and partner ecosystems, terms and pricing increasingly need to be co-created within bank-defined guardrails. This includes tenure, repayment calendars, EMI amounts, repayment days aligned to cash-flow cycles, and constructs like EMI holidays, all tailored to context without eroding risk discipline.
This demands a product factory capability: Modular product components, policy-as-code, real-time decisioning, and pricing that can be versioned, tested, and deployed safely at speed because embedded partners will not tolerate quarterly release cycles. Microservices-based architectures are already being used to compress time-to-market from months to weeks, aligning product iteration to ecosystem cadence.
Conclusion
The next phase of lending will not be decided by who digitizes faster, but by who protects decision quality, economics, and risk stewardship as origination shifts outward into ecosystems. The window for banks to shape this market is narrowing. Once platforms normalize credit as a native feature and underwriting logic is tuned to their data advantage, banks risk being relegated to commoditized balance-sheet providers, absorbing risk while ceding pricing power and customer relevance.
The 2026 imperative is therefore to act with intent: design lending for native journeys, govern partner-led distribution with the same rigor as core channels, and institutionalize the ability to adapt products and decisions at digital speed without weakening controls. In lending, momentum compounds. Those who set the rules early will scale sustainably; those who follow will finance someone else’s franchise. The discipline is governance - fairness controls, audit trails for rules/models, continuous monitoring, and partner-level risk limits, so that personalization does not become opaque risk-taking.
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