Intelligent Drive of DeepSeek-R1: Empowering Regulatory Technology Innovation Practice with Large Language Models
Recently, in order to provide customers with more large model options while meeting the core data security requirements of financial institutions, RIKING's self-developed financial supervision large model, the "IntelliReg Intelligent Supervision Report Solution," has completed an important technological upgrade. On the basis of the original technological framework, it innovatively integrates the DeepSeek-R1 engine and supports private deployment solutions. This upgrade, driven by the dual engines of private deployment capabilities and AI technology, has achieved a deep integration of artificial intelligence technology in areas such as report generation and knowledge interpretation and inheritance. It has accelerated the digital and intelligent transformation of the financial industry and achieved three major breakthroughs.
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Security and Controllability
Supports localized deployment architecture to ensure sensitive data is processed in a closed environment throughout the entire process. In compliance scenarios, the solution is equipped with a "Dual-Closed-Loop Risk Control System": In the security closed-loop direction, it follows the "Financial Data Security Classification Guide" and the "Personal Financial Information Protection Technical Specification" to achieve field-level dynamic desensitization, national cryptographic algorithm transmission encryption, and full-chain operation auditing, meeting the requirements of Level 3 information security protection and cross-border data security. In the intelligent closed-loop aspect, based on the real-time interpretation capability of regulatory rules by the large model (such as 1104 reports and EAST 5.0), it automatically checks for data logic conflicts and generates a compliance governance knowledge graph, reducing the error rate by 95% compared to traditional manual verification.
Report generation efficiency is increased by 40%, and the accuracy rate of interpreting complex regulatory knowledge reaches 98.7%. For example, RIKING uses natural language instruction parsing to perform real-time intent analysis of report requirements, automatically linking to enterprise business system data sources to generate SQL queries or API calls. It also pre-configures over 30 standardized APIs and database drivers for enterprise systems, using the large model to automatically generate compatible code, reducing integration costs. Meanwhile, IntelliReg is equipped with a regulatory compliance knowledge base, enabling automatic data logic verification for regulatory reports and generating compliance risk alerts and correction suggestions.
Relying on its self-developed IntelliReg "Intelligent Ecosystem Adaptation Engine," RIKING's solution deeply integrates with the existing IT architecture of financial institutions (including core banking systems, credit management platforms, and regulatory reporting applications). With a "zero-intrusion connection + modular plug-and-play" design, it supports multi-mode integration through APIs, SDKs, and file exchanges, seamlessly integrating into the bank's technical ecosystem and reducing the cost of intelligent transformation by more than 80%.
Technological Leap: Cross-Generational Upgrade of Intelligent Supervision Report System
For a long time, RIKING has closely followed the cutting-edge trends in the field of artificial intelligence and rapidly adapted the latest advanced technologies, such as the DeepSeek large model, to the iterative upgrades of "IntelliReg." This continuous enhancement of the product's intelligence level and performance ensures that the most advanced and efficient solutions are always provided to customers.
As a professional service provider in the field of financial regulatory technology, RIKING has accelerated the "Smart Supervision" strategic transformation since 2022, innovatively constructing the large model-based intelligent supervision report solution – IntelliReg. This solution deeply integrates a knowledge base system with five core technical modules: Retrieval-Augmented Generation (RAG), Intelligent Agent module, model training and fine-tuning framework, Text2SQL semantic parsing engine, and Large Language Model (LLM). It uses an intelligent technology matrix to achieve precise mapping and dynamic parsing of regulatory data. Since 2024, RIKING has relied on its self-developed model training platform to complete the vertical domain deep training of the open-source Qianwen large model. Through parameter optimization, domain knowledge injection, and compliance reinforcement learning, the model has significantly improved semantic understanding accuracy in financial regulatory scenarios compared to the open-source version, verifying the team's technical accumulation in complex model engineering implementation. Currently, this solution has created a full-cycle intelligent processing closed loop for regulatory authorities, greatly improving the efficiency of regulatory report generation.
Core Functional Advantages of IntelliReg
Intelligent Report Assistant: Enhances user experience through intelligent technology, making report processing more efficient and intuitive.
Automated Report Generation: The automation process significantly increases work efficiency, reduces manual intervention, and ensures the timeliness and accuracy of reports.
Flexible Report Customization: The system supports personalized report customization to meet the specific needs of different users, enhancing the applicability and flexibility of reports.
Powerful Data Analysis Capability: The system has the ability to deeply mine data value, helping financial institutions extract key information from massive amounts of data to support decision-making.
Innovative Practice: Empowering Regulatory Technology with Large Models for Full-Scenario Penetration
RIKING, with the core principles of "intelligence-driven, scenario-integrated, and efficiency-revolutionized," strives to create a comprehensive intelligent solution for financial institutions that covers the entire life cycle and all scenarios of report development. From real-time access to multi-source heterogeneous data to AI-powered automatic modeling and intelligent data cleansing; from dynamic indicator dashboard generation through natural language interaction to predictive analytics-driven decision-making suggestions; from automated parsing of complex business logic to adaptive report visualization — RIKING leverages its integrated capabilities of "data + algorithms + scenarios" to support the full-spectrum needs of financial institutions, ranging from basic reporting to advanced analytics. Whether it is the intelligent upgrade of traditional fixed reports or complex scenarios such as real-time analysis, mobile BI, and regulatory reporting, RIKING can achieve a 70% improvement in development efficiency through its AI engine, truly making data insights a "zero-time-difference engine" for business growth.
Relying on the continuous refinement of large model technology, RIKING has further expanded artificial intelligence technology beyond "IntelliReg" to several key links in regulatory business, continuously promoting the deep integration of large model technology with financial services and achieving a series of innovative results.
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Indicator Development and Construction
In response to the challenge of numerous and frequently updated regulatory indicators, RIKING has built an efficient indicator development and management system based on large models and intelligent analysis technology. This system can intelligently process and analyze indicator data. By combining a rich indicator knowledge base with data warehouses and other databases, the large model can intelligently parse and automatically call relevant information to quickly generate accurate and efficient SQL query statements.
Example of the Indicator Generation Interface
To build a digital R & D governance system, RIKING has taken the lead in incorporating AI code intelligent review into the enterprise-level quality control process. By establishing a triple control mechanism of "intelligent detection - automatic distribution - closed-loop tracking", RIKING has innovatively developed an automated code auditing platform and deeply integrated it into the SDL framework (Secure Development Life Cycle). Based on the large model's neural network learning algorithm, a feature library of 23 types of code defects has been built, and a static analysis engine is used to scan submitted code in real time. Meanwhile, a DingTalk robot early warning center has been set up to establish a graded alert and instant push mechanism. After developers submit code, the review results can reach development and testing personnel within 1 minute, and program bugs and high-risk vulnerabilities can be reported to technical leaders and the quality committee within 3 minutes. Daily reports summarize program quality and problem resolution. This system has transformed the code review model from "manual sampling" to "process governance", increasing the code admission qualification rate to 98% and reducing the vulnerability rate of key systems by 67%, forming a traceable and quantifiable intelligent protection network for R & D quality.
Example of Code AI Review Results
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Regulatory System AI Interpretation
Faced with the increasingly complex regulatory systems, RIKING has innovatively used the large model's natural language processing capabilities combined with its own business accumulation to achieve intelligent interpretation of policy documents through the knowledge base Agent. This not only helps users quickly understand and grasp regulatory requirements but also improves the efficiency and accuracy of compliance work.
Looking to the future, RIKING will continue to deepen the integration and innovation of artificial intelligence technology in regulatory reporting scenarios. Externally, it will empower the digital transformation of financial institutions through intelligent compliance engines. Internally, it will refine its digital capabilities and create a dual-driven system of data governance hub and intelligent Agent factory. By building a shared and quantified mechanism for innovative achievements, RIKING is committed to achieving a two-way cycle of technical capability accumulation and business value transformation, and continuously promoting the intelligent upgrading of financial compliance with an innovative ecosystem of internal and external collaboration.
