Interview: How Banks Are Turning Corporate Channels from Funding Pipes into Business Partners

1. Stock Competition: Three Variables Redefine Corporate Channel Logic, Four Dilemmas Force a Breakthrough

Chinese commercial banks have evolved their channel architecture through distinct stages—from post‑1990 counter‑based electronic access, to PC and early mobile extensions, to unified mobile platforms, to middle‑platform integration, and now to a "new digital‑intelligent" era driven by big data and AI. Duan notes that many banks remain unevenly advanced, with legacy systems, siloed "chimney" architectures, and poor cross‑channel coordination.

The transformation hinges on three inter‑related variables:

Technology : Embedding AI safely and compliantly, avoiding "backend toys" that do not deliver client value.

Organization : Overcoming complex, cross‑departmental coordination by establishing agile, unified governance for front‑, middle‑ and back‑office lines.

Data : Turning fragmented data from hundreds of IT systems into a real‑time, standardized data flywheel that fuels intelligent marketing, risk control, and service personalization.

Four structural challenges impede progress: homogeneous retail services, heavy legacy system baggage, high AI‑to‑client integration barriers, and fragmented data‑platform ecosystems that prevent a closed‑loop data flywheel.

2. Lingyan’s Proposition: Rebuilding the Digital Channel with "Full‑Channel, Strong Middle‑Platform, Solid Technical Base"

Lingyan Technology leverages a "full‑channel layout × three middle‑platforms × unified technical foundation" to help banks create a unified, intelligent channel operating hub centered on customer management. The solution covers corporate internet banking, mobile banking, direct connections, retail channels, and client‑manager tools, forming a funnel‑style customer‑layered operating loop.

The three middle‑platforms are:

Business Middle‑Platform : A set of capability centers and data domains that continuously innovate business scenarios.

Data Middle‑Platform : Provides bank‑wide data consolidation, sub‑second computation, and real‑time transaction streams for intelligent marketing and risk control.

AI Middle‑Platform : A large‑model application platform that supplies AI capabilities to upgrade channel intelligence.

These are built on a "three‑level engine" architecture: a foundational technical engine, a capability engine (the three middle‑platforms), and a business engine (front‑end channel applications). This architecture is designed to support 5‑10 years of channel evolution without repeated patchwork.

3. From Functional Delivery to Value Operations: Three Paths to Corporate Channel Transformation

Enriching the Channel Ecosystem : Moving from a single financial service to a "finance + industry" platform that embeds banking services into enterprise logistics, supply‑chain, travel, procurement, and employee‑welfare processes.

AI‑First Strategy : Turning unstructured data (e.g., invoices, customs documents) into actionable signals via large‑model analysis, automating document recognition, and enabling intelligent financing and risk assessment.

Expanding Service Boundaries : Extending beyond pure funding to become an "enterprise operating partner" that offers SaaS‑style HR, finance, and administration tools, thereby increasing client stickiness and platform activity.

Examples include a payroll‑service platform that integrates onboarding, smart payslips, social‑security data, wealth‑management, and employee benefits, as well as supply‑chain financing that leverages AI‑derived risk scores to offer differentiated loans.

4. Future Landscape: The Ecological Leap of Corporate Channels

The ultimate goal is to shift the channel from a "cost centre" to a "value centre"—a strategic ecosystem hub that drives customer acquisition, retention, AUM growth, and ecosystem stickiness. Lingyan outlines three ecological pillars for a partner bank:

Chain Ecosystem : Deep supply‑chain integration enabling "custom‑per‑point + scale‑replication" solutions across industries.

Finance Ecosystem : AI‑enhanced international business services that automate document processing and achieve up to 90% automation for cross‑border transactions.

e‑Ecosystem : Non‑financial SaaS services (HR, accounting, admin) delivered through the bank’s channel, creating a "finance + non‑finance" one‑stop enterprise platform.

Case studies include a state‑owned joint‑stock bank that has built a "chain‑finance‑e" ecosystem, and a city‑commercial bank that launched a fourth‑generation corporate mobile banking platform, integrating the four flows (information, product, capital, logistics) and AI‑driven intelligent assistants for acquisition, content generation, and decision support.

According to Duan, the transformation is not a mere technical patch but a deep revolution spanning strategy, organization, and service scope. Only by completing the leap from "funds conduit" to "value ecosystem hub" can banks become true "digital intelligence partners" for enterprises.