Dissecting the "Galaxy" system in CITIC Bank's annual report: a digital gamble to reshape the corporate banking business DNA

The full-scale commissioning of the “Galaxy” system has pushed CITIC Bank’s annual technology spending—nearly RMB 10 billion—into the dock of value judgment. In this high-stakes bet aimed at reshaping the genetic code of corporate banking, do the costs and returns actually match?

By | Huamao Rong Finance Content Team

Produced by | Trade Finance

When CITIC Bank invests nearly RMB 10 billion in technology expenses every year, the sharpest question from the market is always: What exactly does this money buy? The bank’s 2025 annual report provides a concrete answer—“Galaxy,” the largest enterprise-wide corporate banking system group, built over three and a half years and commissioned in October of the same year. This set of systems covers all corporate banking lines. Its goal is to reconstruct rather than optimize processes. In this context, its commissioning is essentially a “gene surgery” targeting the underlying logic of corporate banking; its success or failure will directly answer the value proposition behind nearly RMB 10 billion in technology spending.

The annual report shows that the bank’s total assets surpassed RMB 10 trillion in 2025, attributable net profit was RMB 70.618 billion, and the non-performing loan ratio has declined for seven consecutive years to 1.15%. Supporting these results is an information technology investment as high as RMB 9.641 billion.

The focal point of this massive investment, “Galaxy,” does not exist in isolation. Together with the “Xiaotianyuan” platform embedded into customer scenarios and the upgraded “Tianyuan Treasury,” it forms a set of coordinated moves. Its ultimate aim is to help the bank shift from the “process-driven” credit factory model to the paradigm of a “capability-driven” integrated service provider.

Process reshaping: decouple credit granting workflows and strengthen the data foundation

The campaign of the “Galaxy” system begins with a fundamental dissection of the corporate credit granting process. It is not simple automation; instead, it breaks down the fixed linear workflow and reorganizes it into intelligent business components that can be flexibly orchestrated.

Project data shows that in the post-lending review stage, the system automatically processes 642 out of 806 basic indicators, representing 79.7%. In the credit usage stage, it optimizes 382 error prompts and deletes 103 invalid rules.

This is not only an efficiency improvement—it also frees customer managers from tedious tasks and produces more structured, timely data. It lays the groundwork for developing more precise risk-pricing models going forward.

The core of its technological path is “decoupling” and “componentization.” The logic behind choosing this approach is that only by breaking down rigid processes into business capability units that can be flexibly called can the status quo of “people adapting to the system” be fundamentally changed.

Its goal is to shift to a working mode of “the system actively adapting to and empowering people.” This is, in essence, a reshuffling of assignment authority.

Data extraction: entering through ecosystem services to rebuild the risk view

If “Galaxy” optimizes the internal decision flow, then the “Xiaotianyuan” platform aims to obtain brand-new decision inputs. Serving more than 100,000 small and medium-sized enterprises with a model of “free SaaS + ecosystem integration,” its business logic is not based on direct charging.

By embedding into enterprise operating scenarios through tools such as payroll and tax management, purchase/sales/inventory management, it accumulates transaction frequency, supply-chain relationships, and asset dynamic data that traditional financial reports cannot reflect.

Its value has been verified through tangible improvements in customer operation metrics. For example, one connected apparel e-commerce business improved its inventory turnover from 4 times to 7 times. The asset inventory audit time of a manufacturing enterprise was reduced from 3 days to 4 hours.

These real efficiency changes arising from high-frequency business operations are, in themselves, leading indicators reflecting the health of enterprise operations and cash flow conditions. They enable banks to build a dynamic, forward-looking view of enterprise risks and financing needs beyond static financial reports—providing an “ecosystem data” channel that traditional methods cannot easily access.

Risk pricing can thus move from static financial analysis to dynamic assessment of operational health. However, the long-term sustainability of the free model and the compliance boundaries for data application are questions that this model must continuously answer.

Value validation: financial returns on technology investment

The financial returns of large-scale technology investment are directly reflected in both cost and revenue. Against the backdrop of the banking industry’s net interest margin pressure to 1.42% in 2025, CITIC Bank’s interest margin advantage of 1.63% is partly due to digital-driven precision pricing and optimization of liability costs.

More direct is that in 2025, operational costs were reduced by RMB 2.25 billion, and the cost-to-income ratio fell by 0.88 percentage points, demonstrating the direct contribution of the “Galaxy” system in improving efficiency and reducing costs.

At the same time, scenario-based and embedded customer acquisition represented by “Xiaotianyuan” has helped the share of non-interest net income rise to 32.01%, including a 5.58% increase in net fee and commission income.

The return path of technology investment is becoming clearer: one side reduces operational costs, while the other side leverages growth in non-interest income. But it must be acknowledged that these returns have a lag and a long tail; they are far from immediate.

The essence of the high-stakes bet: the ultimate melting furnace of organizational transformation

The real bet goes far beyond the realm of technology. Vice President Gu Lingyun proposed “making AI permeate every business decision within two years,” pointing to a profound organizational transformation.

In 2025, the proportion of CITIC Bank’s technology personnel reached 8.79%. Domain silos and integrated teams are attempts at organizational adaptation.

However, turning the capabilities of “Galaxy” and “Xiaotianyuan” into frontline combat strength requires breaking down departmental walls, reshaping performance evaluation orientations, and replacing empiricism with a data culture.

The key bottleneck lies in whether and how frontline business staff can take the system’s data conclusions and translate them into substantive business judgments and actions—rather than viewing them as an additional burden.

This transformation concerns entrenched interests and organizational inertia; its difficulty and uncertainty are far beyond technology development itself. This is the melting furnace that determines the final success or failure of this digital high-stakes bet.

CITIC Bank’s “Galaxy” high-stakes bet ultimately hinges on whether the “genetic code of corporate banking” can be successfully reconstructed. It seeks to force-catalyze business from a stable state driven by “process” to a new state driven by “data and intelligence” through a precise technical architecture and ecosystem platforms.

At a preliminary glance, this transformation has already shown business value beyond mere technical trial and error.

But a true paradox emerges: when technology systems shift from supportive roles to a driving core, will the bank’s traditional organizational structure and talent composition become, instead of a transformation engine, the biggest obstacle?

CITIC Bank’s exploration ultimately questions how the entire banking industry defines its identity in the deep waters of digital transformation and rebuilds its core capabilities.

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