Tencent Cloud Automotive China Translated from Chinese

Dongfeng Nissan (东风日产)

Risk Management · Security and Compliance

Dongfeng Nissan needed to strengthen finance-leasing risk models and process management while coping with hybrid-cloud complexity, connected-vehicle and user-data security exposure, and tighter cybersecurity and privacy regulations across the automotive sector.

POC-stage overall risk-control-engine precision improved by more than 30%.
The first phase had been live for more than 4 months.
The first phase supported about RMB 300 million in total business volume.

Reported impact

Business outcome

Tencent Cloud helped Dongfeng Nissan Finance Leasing improve approval accuracy and case pass rates, lower bad-debt rates, support about RMB 300 million in business within a little over four months of phase-one go-live, and put a stronger security and compliance framework around automotive digital operations.

  • Compliance
  • Productivity Improvement
  • Risk Reduction

Solution

Dongfeng Nissan used Tencent Cloud to combine finance-leasing risk control with automotive security and compliance on a shared cloud architecture. Tencent Financial Cloud provided compute, network, storage, database, security, and middleware services so the automaker could run risk workloads on elastic, reliable infrastructure. A big data platform and real-time multidimensional analysis turned accumulated business data into data-driven risk decisions, while NLP, speech recognition, and OCR added AI signals for verification and workflow innovation. For Dongfeng Nissan Finance Leasing, Tencent tailored a localized risk-control engine around the customer's scenarios and business processes. The broader solution also included an integrated security protection model spanning public-cloud controls, SOC-led private-cloud operations, zero-trust access, vehicle-security testing, and data-security governance, so risk, compliance, and automotive digital operations could be managed in one program.

Data flow

Finance-leasing application and operational data run on Tencent Financial Cloud and accumulate in the big data platform, where real-time multidimensional analysis and AI services such as NLP, speech recognition, and OCR enrich risk signals. The localized risk-control engine applies those signals to Dongfeng Nissan's approval and risk workflows, while the integrated security protection solution governs cloud, data, and user-journey security.

Solution architecture

6 components · 5 layers
  1. Compute
    • real-time multidimensional analysis Analyzes finance and operational data in real time to support risk decisions and process management.
    • NLP, speech recognition, and OCR capabilities Adds AI-driven recognition and workflow signals to Dongfeng Nissan's finance and security scenarios.
  2. Storage
    • big data platform Consolidates accumulated business data so risk control and decisioning can run on a shared data foundation.
  3. Serving
    • localized risk-control engine Executes the customer-specific risk models and approval logic tailored to Dongfeng Nissan Finance Leasing.
  4. Orchestration
    • Tencent Financial Cloud Provides the elastic compute, network, storage, database, security, and middleware foundation for Dongfeng Nissan's finance-leasing risk workloads.
  5. Governance
    • integrated security protection solution Applies defense-in-depth controls and compliance governance across cloud, data, user-journey, and vehicle-lifecycle security.

Architecture clues

  • POC validation combined historical data with model testing before phase-one launch.
  • Tencent Financial Cloud is described as supplying compute, network, storage, database, security, and middleware services for the solution.
  • Tencent customized the risk-control engine after mapping the customer's business scenarios and processes.
  • The page frames automotive security as a layered model across public-cloud controls, SOC-led private-cloud operations, zero-trust office access, vehicle-security testing, data security, and business security.

Evidence from the source

After reviewing the customer's scenarios and business processes, Tencent customized a localized risk-control engine and process; in the POC stage overall precision improved by more than 30%, and after more than 4 months of phase-one go-live the solution had supported about RMB 300 million in business (original: 在与东风日产融资租赁的合作中,通过对客户场景与业务流程的梳理,借助金融云的能力,我们为客户量身定制本地化的风控引擎及风控流程。这大大提升案件通过率,同时降低了坏账率,企业经济效应显著好转。POC 阶段,结合历史数据及模型测试,整体风控引擎精准度较之前提升30%以上。截止到目前,一期上线4个多月,支持整体业务金额达3亿元左右,经济效益大幅提升。)
For Dongfeng Nissan Finance Leasing's business needs, Tencent Financial Cloud used cloud computing, big data, and AI to improve core capabilities such as financial risk-control models and process management (original: 针对东风日产融资租赁的业务需求,腾讯金融云在云计算、大数据、AI 等各方面助其提升金融风控模型和流程管理等核心能力。)
Tencent Financial Cloud provides mature compute, network, storage, database, security, and middleware services, giving customers elastic, secure, and reliable cloud capabilities (original: 腾讯金融云计算方面:提供计算/网络/存储/数据库/安全/中间件等成熟的产品及服务;为客户提供弹性扩展、安全、可靠的云计算能力。)
Tencent provides NLP, speech recognition, and OCR capabilities to drive business-scenario innovation (original: AI 方面:基于腾讯20年的技术发展与沉淀,提供 NLP、语音识别、OCR 等能力,助力业务场景创新。)
Tencent's big data platform uses accumulated data and real-time multidimensional analysis so financial enterprises can form data-driven risk control and decision making (original: 大数据方面:依托丰富的数据沉淀,运用大数据平台的能力、实时多维分析能力等,金融企业可快速构建这些能力并应用于业务,形成数据驱动的风控和决策。)
Tencent's integrated security protection solution provides defense-in-depth protection, expert security services, and a closed-loop security-operations model that safeguards the full user journey and vehicle lifecycle (original: 腾讯一体化安全防护解决方案提供了覆盖云端的纵深安全防护体系,以及专家级的安全服务和安全运营闭环,全面保障用户旅程和车辆全生命周期的安全。)
Transparency Evidence & methodology 90/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Tencent Cloud

    Dongfeng Nissan (东风日产) customer story

    First-party
    https://cloud.tencent.com/customer/nissan
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.