The rapid advancement of financial technology (fintech) and the deepening digital transformation of financial institutions have led to an increased focus on the user experience of financial productsTraditionally, the design processes for financial product interfaces typically stretched over weeks or even months, which made it challenging to meet the fast-paced demands of innovationEnter the era of large model-assisted design, which merges artificial intelligence techniques like deep learning, computer vision, and natural language processing with conventional design methodsThis innovative approach stands to markedly enhance design efficiency and reduce costsThis article introduces a groundbreaking "4I" application framework aimed at providing insights on how large model-assisted design can transform the financial sector.

Financial institutions grapple with a multitude of challenges including diverse user demands, complex business scenarios, and stringent regulatory requirements

Despite employing various specialized UI/prototyping tools for their information systems, financial institutions continue to face critical issuesFirst, design efficiency often falls short of the rapid innovation needed within the industryThe conventional design process, with its myriad phases—from demand research to feedback and multiple iterations—cannot keep pace with swiftly evolving needsThis inefficiency is further exacerbated by the scarcity of talented designers, leading to a growing supply-demand conflict in the talent market.

Secondly, the costs associated with design remain persistently highFinancial institutions must invest in various design tools and resource materialsMoreover, due to misunderstandings in requirements and a lack of standardized design principles, the results often necessitate repeated revisions, further inflating costs.

Next, the challenge of unifying design standards persists

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There are noticeable variations in design styles among different teams within the same institutionAlthough many have established design guidelines, execution discrepancies result in inconsistent user experiencesThis problem only intensifies as product lines expand, leading to increasingly complicated design asset management.

Lastly, the absence of transformative innovation is glaringTraditional design methods rely heavily on individual designer experience, which makes breakthrough innovations difficult to achieveThe lengthy process required for new design concepts—from proposal to final validation—further stifles creativity and innovation.

Tackling these challenges is crucial for the product innovation and user experience enhancements at financial institutionsThe exploration of large model-assisted design offers promising solutions for these pressing issues.

This article introduces the "4I" application framework for large model-assisted design in financial institutions, covering four critical components: Interface Design, Image Design, Inspiration of Design, and Integration of Design

This framework aims to offer methodological guidance for the application of large model-assisted design within the financial industry.

1. **Interface Design**: The implementation of large model-assisted interface design encompasses demand analysis, layout generation, style generation, and system integration and deploymentDuring the analysis phase, a language model based on the Transformer architecture interprets user inputs in natural language, applying named entity recognition and relationship extraction to distill key informationThis is further enhanced by a specialized knowledge base built from financial industry expertise, enriching insights into professional jargon and workflowsThe layout generation phase utilizes a model trained on a robust dataset of financial UI designs—including screenshots and style guidelines—to produce preliminary layout templates that adhere to established design standards

In generating visual styles, computer vision techniques identify essential design elements, enabling automatic creation of structured design filesFinally, during the integration and deployment phase, a microservices architecture separates functions for easier maintenance; container technologies are employed for rapid deployment, while an API gateway secures service interface managementThe culmination of these techniques results in a powerful and efficient interface design system that significantly enhances the quality and productivity of financial product interfaces.

2. **Image Design**: Large model-assisted image design notably involves intelligent icon generation and illustration creationFor intelligent icon generation, a customized model based on Stable Diffusion is fine-tuned on a vast dataset of financial icons, allowing for precise interpretations of financial terminology and visual aesthetics

A natural language processing module helps translate complex icon requests into understandable prompts for the modelIn terms of illustration creation, techniques like ControlNet enable precise control from text to image generation, while multiple customized models are trained based on existing artworks to align with brand aestheticsAdditionally, reinforcement learning algorithms provide intelligent cropping while maintaining essential content integrityThese actions, coupled with seamless integration into popular design software via APIs, create a robust workflow that supports the visual representation of financial products.

3. **Inspiration of Design**: This aspect focuses on intelligent component recommendations, reference case matching, and design trend analysisBy leveraging embedding technology, a database connects design components to user requirements, allowing for enhanced matching and scene-specific suggestions

The reference case matching employs multi-dimensional retrieval models to classify and index design examples, facilitating intelligent recommendations and analyses that inspire designersFinally, through mining user behavior data, trend analysis predicts shifts in user preferences and assesses the acceptance of design proposals, thus fueling innovation and design breakthroughs.

4. **Integration of Design**: This includes knowledge base integration, component library integration, project conversion integration, and process integrationBy setting up a smart asset management system—incorporating design knowledge graphs and embedding techniques—assets become more accessible and retrievableThe component library fosters smart calls based on unified standards, ensuring consistency in design practicesThe project conversion aspect automates frontend code generation while ensuring quality across multiple frameworks

Moreover, a focus on smart upgrades across all design processes encapsulates the entire design flow, ensuring the efficient completion of projects.

The large model-assisted design applications built upon the "4I" framework have begun to take root in financial institutions, showcasing numerous advantages over traditional methodsTraditional approaches often relied on pre-set component libraries arranged to create design interfaces, which, while somewhat quick and straightforward, lacked the flexibility and stylistic variety needed for rapid innovationIn contrast, large model-assisted designs provide dynamic generation of design elements that are directly aligned with real business scenarios and user needs.

In practical applications, large model-assisted design has realized improvements in efficiency, nearly tripling design outputs while considerably shortening project timelines and decreasing revision rates

In terms of cost management, the investment in design tools and new employee training has decreased, alongside enhanced asset management and operational efficienciesThe adherence to design standards seen through improved component usage regulations, consistent visual styles, and standardized interaction modes further underscore the value of this innovative approach.

In conclusion, the exploration of large model-assisted design within the financial sector has led to the development of the innovative "4I" application framework, providing a theoretical foundation for deeper applications in this fieldAs financial institutions continue their digital evolution, large model-assisted design is poised to become a key driver of product innovation, aiding in lowering design costs and enhancing design efficiencyThis, in turn, greatly contributes to the elevated standards of financial services and the ongoing digital transformation within the industry.