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AI Testing Agent

Intelligent Automation, Uncompromised Quality – The Future of software .

Pain Points

Pain point 1: Vicious Cycle of Test Resource Consumption


• ​Scenario Dilemma

Cross-border financial institutions face a relentless "demand surge-human expansion-efficiency stagnation" cycle. Despite round-the-clock testing operations, teams struggle to keep pace with release cycles, forcing critical business validations to be deprioritized.


• ​Typical Scene:

Test teams work through nights and weekends to meet go-live deadlines, yet consistently miss mission-critical defects under time pressure; new hires require ​lengthy onboarding to master core business workflows.


• ​Talent Gap:

Chronic attrition among ​hybrid finance/test professionals creates a "brain drain" crisis. Mid-sized firms rely on "apprenticeship" models to sustain basic testing capabilities, resulting in inconsistent validation quality. 


Pain point 2:Fatal Flaws in Validation Architectures


• ​Regulatory Pitfalls:

Dynamic regulatory environments expose gaps in ​static testing frameworks. Institutions have suffered compliance breaches and reputational damage due to unaddressed rule changes.


• ​Real-World Fallout:

Core system upgrades triggered ​critical transaction failures on launch day due to untested edge-case scenarios.


• ​Technical Debt Crisis:

Manual test script maintenance becomes ​unsustainable overhead. Minor code changes (e.g., UI updates) trigger widespread test case invalidation, forcing teams to abandon legacy assets.

 

Pain point 3:Agile Transformation Bottlenecks

 

• ​Efficiency Collapse:

Frequent requirement changes trigger ​exponential rework cycles. Teams lose weeks rewriting scripts for each iteration, severely hampering delivery speed.

 

• ​Policy Whiplash:

Regulatory shifts force urgent script overhauls, overwhelming automation maintenance capacity.

 

• ​Go-Live Delays:

Manual verification timelines exceed critical thresholds, causing organizations to miss high-stakes market opportunities.

 

• ​Credibility Erosion:

Hybrid testing strategies spark internal debates about "true digital maturity", eroding executive confidence in transformation roadmaps.

 

Product Overview

Gientech AI Testing Agent built specifically for financial institutions, replacing repetitive human work through AI automation and significantly reducing annual testing costs. The product is pre-built with banking business logic libraries, supporting full-link verification from core transaction systems to digital channels. Test datasets are intelligently generated to meet multi-region regulatory requirements to ensure business compliance. Intelligent regression testing modules significantly reduce maintenance workload during version iteration and accelerates product iteration speed.

 

Application Scenarios
  • Manual Generation of Test Cases | Visual debugging interface reduces time spent on case building by 75%, and intelligent batch entry capability makes step creation 3x more efficient. Manual fine-tuning channels are preserved to ensure business-critical validation accuracy up to financial-grade standards.

  • Automatic Generation of Test Scripts | Business experts can generate executable test scripts without coding and automate execution with 80% less human intervention. Extensive pre-built financial business templates reduce automation implementation cycle to 3 days.

  • Requirement Generation of Test Cases | Automatically transform product requirements into executable use cases with 60% more coverage than traditional models. Save 40+ man-days of requirements analysis per iteration cycle, accelerating time-to-market.

  • Requirement Generation of Test Data | Intelligently generates test data that meets multi-region regulatory requirements, eliminating manually constructed compliance risks. Dynamically adapts to changes in business rules, ensuring real-time synchronization between data and system evolution. The validation system automatically captures anomalous patterns, providing decision makers with a trusted benchmark for quality assessment.

  • Data-driven Testing | Intelligent optimization of test resource allocation, focusing on in-depth verification of core business links. Significantly reduces redundant testing inputs and improves the efficiency of intercepting critical defects through dynamic priority adjustment mechanism. Continuously tracking business trends to ensure real-time synchronization between testing strategies and market demands.

Business Value
Significantly improve testing efficiency and speed

Reconstructing the enterprise R&D performance curve, the intelligent test orchestrator makes the function iteration speed break through the industry standard. By establishing a positive feedback mechanism between testing time and business value, it helps enterprises maintain a first-mover advantage in market competition. Dynamic priority engine ensures that 80% of testing resources focus on 20% of core business flows, maximizing the input-output ratio.

Reduce testing costs and resource consumption

Establish the marginal decreasing model of test cost with business scale expansion, breaking the growth shackle of traditional linear cost curve. Through the exponential increase of automation substitution rate, the cost of single iteration testing is stabilized at less than 30% of the industry benchmark value, forming a sustainable cost competitive advantage.

Improve software quality and reliability

Shift-Left Testing:Bringing the defect repair cost curve forward to the development stage reduces post-production troubleshooting costs to 1/8th of the traditional model, which translates directly into increased market value for the company by modelling the strong correlation between quality metrics and customer retention rates.

Expanding Test Coverage and Scenario Adaptability

Builds infinite scalability of testing capabilities, enabling business scenario coverage to exceed the theoretical upper bound of traditional methods. Ensure that enterprises always have a validation capability first-mover advantage in emerging market exploration by fostering the synchronized growth of test assets and business innovation.

Contact GienTech to get your customized solutions Consult expert
Online Trial

中电金信鲸Bot RPA是一款面向金融行业客户的机器人流程自动化的开发平台。

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    鲸Bot设计器集成了浏览器自动化组件,office办公自动化组件,数据库组件,文件处理组件、邮件组件等多种类型组件,通过全栈自动识别技术,自动识别目标元素,使开发过程所见即所得,降低了RPA开发门槛,让业务人员也可以方便地进行业务流程的开发。

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    通过手动执行、定时执行、控制台远程调用的方式运行自动化流程,配合控制台对外提供API接口,供外部程序调用。通过特有的视觉反馈技术提供统一的异常处理机制,极大降低开发和运维成本,让RPA流程运行更加稳定,而解决金融行业因技术人员产能不足难以支持其业务发展的问题。

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