恒实信用左丽：以算法模型与大数据驱动，搭建中美企业信用互联新生态

【中美创新时报2025年5月19日波士顿讯】（记者温友平）近日，值此赴美考察投资市场之际，恒实信用管理有限公司（以下简称“恒实信用”）创始人左丽应邀接受了美国新锐华文媒体《中美创新时报》记者专访，从恒实征信V3.0系统的技术创新，到助力中外企业跨境布局，再到对中美经贸合作的前瞻性思考，左丽详解了恒实信用在国际化道路上的“算法模型＋大数据＋国际化战略”创新路径。

创始人左丽是国际注册会计师、中国国家一级信用管理师、税务师、理财规划师，现为中国国家人才库财会专家、河北省财政厅、工信厅、发改委等入库专家、雄安股权交易所股份有限公司风控委员、征询专家。

她从事多种行业财务管理工作30多年，精通互联网、大数据、人工智能、金融科技领域，尤其精通多领域ERP，注重培训指导，服务过的单位财务基础、经济效益均比以前提升数倍，多年来应邀为多家集团公司做过财税指导培训、上市辅导工作等。

恒实征信V3.0系统：多维算法模型构筑权威风控体系

据介绍，恒实信用是一家以算法模型为核心的大数据风控公司，拥有央行企业征信资质。左丽特别强调说，恒实信用的目前最大创新成果集中体现在集合了多种模型的V3.0系统：

一是恒实云瞳风控模型：全流程监测企业风险触点；

二是纳税大模型、税务预警模型、纳税自检模型：精准洞察税务合规风险；

三是供应链分析模型、财务分析模型：从链条与财务双维度评估企业健康；

四是企业偿债能力与授信额度模型：为银行与金融机构提供授信参考。

同时，恒实信用还自主研发了面向企业复杂行为统计与“能耗数据”提取的算法模型，帮助客户在绿色合规与节能降耗方面抢占先机。”

左丽进一步指出，算法模型是解决特定问题的数学框架，如排序、压缩等，而AI模型（如神经网络、强化学习）则是依赖大规模数据驱动的智能算法子集。恒实的算法模型则侧重于可解释性与场景定制，能与行业规则、政策要求深度结合。

左丽介绍，恒实信用V3.0系统所依托的算法模型，是一套面向特定金融场景的数学框架，具有以下显著优势：

结果唯一性：即同一输入条件下，只会产生一致且可复现的风险评分与决策建议；

高精度与可解释性：基于行业规则和政策要素，输出结果可追溯到关键参数，便于合规审计和监管沟通；

左丽指出，相比之下，典型的AI模型（如深度神经网络、强化学习）因依赖大规模数据驱动，虽可生成多样化预测，却在样本敏感性与“黑箱”特征上存在真假不确定风险。左丽强调：“我们的算法模型与AI模型并非对立，而是互补——前者擅长规则明确、可解释的风控场景，后者可在复杂模式识别中提供辅助洞见。”

此外，恒实信用携手京津冀国家技术创新中心河北中心等，多方共建国创河北中心数政研究院，左丽本人亦为京津冀国家技术创新中心事业合伙人，推动产学研用协同创新和深度融合。

吸引外资入华：“零资料”风控服务促精准决策

“对看好中国市场的美国及其他外资企业，他们最关注的是：如何快速、客观地了解目标公司真实风控状况？恒实信用开发了‘零资料’风控报告服务——外资方仅提供目标企业名称与注册信息，我们即能整合工商、司法、财税、供应链等多源数据，输出详实的企业风险与发展潜力分析。”左丽介绍说。

这一模式不仅降低了外资尽调门槛，更让投资方能精准评估项目，不会因资料不全产生误判。左丽强调，这也正是恒实信用助推“外资入华”的重要抓手。

据了解，对于想要进入中国市场的美国及其他外资企业，传统路径通常是：聘请顶级咨询公司，耗时数月，投入数十万至上百万美元，完成市场分析、监管研究以及合规评估。对此，左丽表示：“恒实信用提供的‘零资料风控报告’具有三大创新优势：

速度：5至45分钟内即可完成全量数据整合与报告出具；

成本：仅为传统咨询服务费用的1%–3%；

精准度：依托央行资质数据与实时工商、税务、司法信息，数据库更新频率实时，确保风险点无遗漏。”

左丽说：“外资方只要提供目标企业名称与注册信息并通知目标企业授权许可，我们即可输出详实的风控报告，帮助其以最短时间、最低成本完成投资决策。” 

通过这种模式，外资方不仅能迅速掌握目标企业的运营健康度，还能将更多资源投入到市场开拓与本地化运营上，从根本上优化投资决策流程。 

权威“信用通行证”：助力中国企业“出海”投资护航

“截至目前，恒实信用已为逾50万家中国企业——涵盖制造、科技、服务等多个行业——输出了央行资质的权威信用报告。”左丽透露，依托庞大客户基础，恒实信用正将原有国内报告升级为面向国际市场的“信用通行证”，主要内容包括：

多维度信用画像：法人资质、税务合规、司法诉讼、供应链关联风险等全景展现；

国际对标评分：基于全球同业样本库，提供国际化信用评级与风险等级；

动态预警与整改建议：帮助企业自检风险并制定精准整改方案；

一报告多向通行：兼容美国、欧盟及亚太地区金融机构和政府部门的尽调需求。

这种“信用通行证”服务，不仅能为中国企业在美国、欧盟等国际市场获得“信用通行证”式的信任背书，还能大幅提升海外融资与市场准入效率。

“对于正加速‘走出去’的中国企业，最关键的是赢得当地监管与合作伙伴的信任。恒实信用凭借央行资质与行业口碑，能快速出具符合美国、欧盟等多国要求的权威信用报告，包括法人背景、经营状况、关联交易及潜在诉讼风险等核心信息，为中企开拓美国市场提供‘信用通行证’。”左丽总结道。

据介绍，企业只需授权查询基本信息，无需反复提供繁琐资料，恒实信用报告即可覆盖行业对接、市场准入等所需信用指标，极大提升海外尽调效率。 

国际化蓝图：打造中美双向流通的信用生态

面对目前乃至今后的中美贸易关系发展，左丽认为：“中美经贸合作是两国关系的基石。恒实信用未来要做的不仅是单向赋能，而是构建双向流通的‘信用互联’信用生态。”她还进一步介绍了这种信用生态的具体内涵：

一是自检预警：为中外企业提供“风险自检＋动态预警”工具，帮助及时发现并化解潜在问题；

二是全向赋能：持续升级国内“信用通行证”并丰富外资“零资料风控报告”产品线，实现双向信用流通；

三是数据互认：推进与海内外监管机构、央行征信局及行业联盟的数据共享与互认机制；

四是创新实验室：依托京津冀国创中心等平台，联合打造“国际信用创新实验室”，孵化更多算法落地场景。

很显然，构建中美“信用互联”是恒实信用国际化蓝图的重要举措。谈及国际化战略，左丽表示，恒实信用将要布局北美、欧洲与东南亚三大市场，以“本土化研发中心＋全球合作伙伴”为架构，推动算法模型迭代升级，并计划在两年内完成多语种V4.0系统的发布，全面支撑中美企业在全球范围内的信用信息透明与风险管控。

着眼未来国际化布局，左丽提出了“三步走”战略：

全球数据中心建设：在北美、欧洲及东南亚设立数据节点，采集当地工商、税务、司法及行业协会数据，丰富算法模型的国际样本库；

跨境合作机制：与海内外监管机构、央行征信处、行业联盟共建数据共享平台，实现信用信息互认与交叉验证；

多语种系统升级：计划于2026年发布V4.0系统，支持英语、法语、德语、西班牙语等多语种界面与报告模板，全面支撑中外企业跨境信用应用。

“只有不断夯实国际大数据基础，优化算法模型，我们才能在全球范围内提供既精准又具本地化洞察的风控服务。”左丽如是总结。

题图：2025年5月，恒实信用创始人左丽在考察美国华尔街金融市场。（受访者供图）

Hengshi Credit’s Zuo Li: Building a New Sino-US Corporate Credit Interconnection Ecosystem Driven by Algorithmic Models and Big Data

Sino–US Innovation Times, Boston, May 19, 2025 (Reporter Youping Wen) — Recently, on the occasion of her visit to the United States to study the investment market, Zuo Li, founder of Hengshi Credit Management Co., Ltd. (hereinafter “Hengshi Credit”), granted an exclusive interview to Youping Wen of the emerging Chinese-language media Sino–US Innovation Times, detailing Hengshi Credit’s innovative pathway of “algorithmic models + big data + internationalization strategy” on its road to globalization—from the technological innovations of the Hengshi Credit V3.0 system to assisting domestic and foreign enterprises in cross-border expansion, and to forward-looking reflections on Sino-US economic and trade cooperation.

Founder Zuo Li is an Internationally Certified Public Accountant, a China National First-Class Credit Manager, a Tax Advisor, and a Financial Planner, and currently serves as a financial and accounting expert in the China National Talent Pool, as well as an enrolled expert for the Hebei Provincial Department of Finance, the Hebei Department of Industry and Information Technology, and the Development and Reform Commission. She also sits on the risk control committee and acts as a consulting expert for Xiong’an Equity Exchange Co., Ltd.

She has engaged in financial management work across various industries for over 30 years, is proficient in internet, big data, artificial intelligence, and fintech domains—particularly in multi-domain ERP—and places strong emphasis on training and guidance; organizations she has served have seen their financial foundations and economic efficiencies improve several‐fold. Over the years, she has been invited by numerous corporate groups to provide fiscal and tax guidance training and listing counseling.

Hengshi Credit V3.0 System: A Multidimensional Algorithmic Framework for Authoritative Risk Control

According to company information, Hengshi Credit is a big-data risk control firm built around algorithmic models and holds corporate credit reporting qualifications from the People’s Bank of China. Zuo Li emphasized that Hengshi Credit’s greatest current innovation lies in its V3.0 system, which integrates multiple models:

Hengshi Yuntong Risk Control Model: Monitors enterprise risk touchpoints across the entire process.

Tax Compliance Models: Including the Tax Big-Data Model, Tax Early-Warning Model, and Tax Self-Inspection Model, which deliver precise insights into tax compliance risks.

Supply Chain and Financial Analysis Models: Evaluate enterprise health from both supply-chain and financial perspectives.

Solvency and Credit Limit Model: Provides credit reference for banks and financial institutions.

Simultaneously, Hengshi Credit has independently developed algorithmic models for analyzing complex corporate behaviors and extracting “energy-consumption data,” helping clients seize early opportunities in green compliance and energy conservation.

Zuo Li further pointed out that algorithmic models are mathematical frameworks for solving specific problems—such as sorting or compression—whereas AI models (e.g., neural networks, reinforcement learning) are data-driven subsets of intelligent algorithms. Hengshi’s algorithmic models prioritize interpretability and scenario customization, enabling deep integration with industry rules and policy requirements.

She explained that the algorithmic models underpinning the Hengshi Credit V3.0 system constitute a mathematical framework tailored to specific financial scenarios, offering two key advantages:

Deterministic Output: Under identical input conditions, the system produces consistent and reproducible risk scores and decision recommendations.

High Precision and Interpretability: Results are based on industry rules and policy elements and can be traced back to critical parameters, facilitating compliance audits and regulatory communication.

By contrast, Zuo Li noted, typical AI models (such as deep neural networks and reinforcement learning) depend on large-scale data and can generate diverse predictions but carry risks of uncertainty due to sample sensitivity and “black-box” characteristics. She emphasized, “Our algorithmic models and AI models are not adversarial but complementary—the former excel in rule-defined, interpretable risk-control scenarios, while the latter can provide auxiliary insights in complex pattern recognition.”

Moreover, Hengshi Credit has partnered with the Hebei Center of the Beijing–Tianjin–Hebei National Technology Innovation Center and others to co-build the National Innovation Hebei Center’s Digital Governance Research Institute. Zuo Li herself serves as a venture partner at the Beijing–Tianjin–Hebei National Technology Innovation Center, promoting collaborative innovation and deep integration across industry, academia, research, and application.

Attracting Foreign Investment: “Zero-Documentation” Risk Control Service for Precise Decision-Making

“For American and other foreign companies optimistic about the Chinese market, their primary concern is how to quickly and objectively understand the true risk-control status of a target company,” Zuo Li explained. “Hengshi Credit has developed a ‘zero-documentation’ risk control report service—foreign investors only need to provide the target company’s name and registration details, and we integrate multi-source data from industrial and commercial, judicial, fiscal and tax, and supply-chain channels to produce a comprehensive analysis of corporate risks and development potential.”

This model not only lowers the due-diligence threshold for foreign investors but also enables them to accurately assess projects without misjudgment due to incomplete information. Zuo Li stressed that this is a key lever for Hengshi Credit to support foreign investment into China.

Traditionally, foreign enterprises wishing to enter the Chinese market engage top consulting firms, a process that takes months and costs hundreds of thousands to over a million U.S. dollars to complete market analysis, regulatory research, and compliance assessment. In response, Zuo Li said, “Hengshi Credit’s ‘zero-documentation risk control report’ offers three innovative advantages:

Speed: Full data integration and report generation in 5 to 45 minutes.

Cost: Only 1%–3% of the fees for traditional consulting services.

Accuracy: Based on People’s Bank of China–qualified data and real-time industrial, tax, and judicial information, with a database update frequency that ensures no risk points are overlooked.

“Foreign investors need only supply the target company’s name, registration information, and authorization, and we can deliver a detailed risk-control report to help them complete investment decisions in the shortest time and at the lowest cost,” Zuo Li said.

Through this model, foreign investors can quickly grasp a target company’s operational health and allocate more resources to market development and local operations, fundamentally optimizing their investment decision processes.

Authoritative “Credit Pass”: Safeguarding Chinese Enterprises’ Overseas Investments

“To date, Hengshi Credit has issued People’s Bank–qualified authoritative credit reports for over 500,000 Chinese companies across manufacturing, technology, services, and other industries,” Zuo Li revealed. Leveraging this large client base, Hengshi Credit is upgrading its domestic reports into an international “Credit Pass,” which includes:

Multidimensional Credit Profiles: A panoramic display of corporate credentials, tax compliance, judicial litigation, and supply-chain–related risks.

International Benchmark Ratings: Global, peer-based credit ratings and risk levels drawn from an international sample library.

Dynamic Alerts and Remediation Recommendations: Tools to help enterprises self-inspect risks and implement precise corrective actions.

One Report, Multiple Usages: Compatibility with due-diligence requirements of financial institutions and government agencies in the U.S., EU, and Asia-Pacific regions.

This “Credit Pass” service not only provides a trust endorsement akin to a passport for Chinese enterprises in international markets such as the U.S. and EU but also significantly improves their overseas financing and market entry efficiency.

“For Chinese companies accelerating their ‘going global’ efforts, the most critical thing is to earn the trust of local regulators and partners. With its central bank qualifications and industry reputation, Hengshi Credit can rapidly produce authoritative credit reports that meet the requirements of the U.S., EU, and other countries—covering core information such as corporate background, operational status, related-party transactions, and potential litigation risks—to provide a ‘Credit Pass’ for Chinese enterprises entering the U.S. market,” Zuo Li concluded.

According to the company, enterprises only need to authorize the query of basic information without repeatedly supplying cumbersome documents. Hengshi Credit’s reports cover all necessary credit indicators for industry alignment and market access, greatly enhancing the efficiency of overseas due diligence.

Internationalization Blueprint: Creating a Bidirectional Sino-US Credit Ecosystem

Facing current and future developments in Sino-US trade relations, Zuo Li believes, “Sino-US economic and trade cooperation is the cornerstone of bilateral relations. In the future, Hengshi Credit’s goal is not merely one-way enablement but to build a bidirectionally flowing ‘credit interconnection’ ecosystem.” She further described the concrete components of this ecosystem:

Self-Inspection and Early Warning: Providing “risk self-inspection + dynamic alert” tools for Chinese and foreign companies to help them identify and resolve potential issues promptly.

Omnidirectional Enablement: Continuously upgrading the domestic “Credit Pass” and enriching the foreign “zero-documentation risk control report” product line to realize bidirectional credit flows.

Data Mutual Recognition: Promoting data-sharing and mutual recognition mechanisms with domestic and overseas regulators, central bank credit bureaus, and industry alliances.

Innovation Laboratory: Partnering with platforms such as the Beijing–Tianjin–Hebei National Innovation Center to jointly establish an “International Credit Innovation Laboratory” to incubate more algorithm-driven application scenarios.

“Clearly, building a Sino-US ‘credit interconnection’ is a key initiative in Hengshi Credit’s internationalization blueprint,” Zuo Li stated. Regarding its international strategy, she said that Hengshi Credit plans to expand into North America, Europe, and Southeast Asia, using a “localized R&D center + global partner” structure to drive iterative upgrades of its algorithmic models, and aims to release a multilingual V4.0 system within two years to fully support global transparency of credit information and risk control for Sino-US enterprises.

Looking ahead to its international deployment, Zuo Li outlined a “three-step” strategy:

Global Data Center Construction: Establish data nodes in North America, Europe, and Southeast Asia to collect local industrial, tax, judicial, and industry-association data, enriching the international sample library for algorithmic models.

Cross-Border Cooperation Mechanism: Collaborate with domestic and overseas regulators, central bank credit bureaus, and industry alliances to build data-sharing platforms, achieving mutual recognition and cross-validation of credit information.

Multilingual System Upgrade: Plan to launch the V4.0 system in 2026, supporting interfaces and report templates in English, French, German, Spanish, and other languages to fully underpin cross-border credit applications for domestic and foreign enterprises.

“Only by continuously strengthening the international big-data foundation and optimizing algorithmic models can we provide risk-control services worldwide that are both precise and locally insightful,” Zuo Li concluded.