Trawler: Resilient AI-driven financial data extractor
Trawler is a mobile financial engine that uses artificial vision and async architecture to extract and enrich data across platforms, enabling scalable, real-time acquisition for the Open Finance ecosystem..
Trawler is an advanced digital solution designed to automate the extraction, verification, and analysis of financial data within the Open Finance ecosystem. Unlike traditional scraping tools, Trawler uses computer vision to interpret financial documents and interfaces, making it highly adaptable to frequent design changes across banking and fintech platforms without compromising accuracy or performance.
Powered by an asynchronous architecture, Trawler runs parallel workflows that enable real-time, large-scale data processing with high reliability. Its core features include:
App Features
- Unified account aggregation
- Instant balance and account ownership verification
- Financial data enrichment
- Customer behavior analytics and segmentation
- Personalized financial insights
Challenges
The development of Trawler presented several strategic and technical challenges due to the complexity of the financial data landscape and the evolving requirements of Open Finance. The client was seeking a robust, future-proof solution capable of extracting and processing financial data reliably across a wide variety of platforms, each with its own interface, structure, and update cycle. These were the main challenges we encountered:
These challenges required us to rethink traditional approaches and build a resilient, scalable infrastructure that combined AI, asynchronous architecture, and advanced data processing to meet the demands of modern fintech operations.
- Fragility of Traditional Scraping Methods
Most existing tools relied on HTML-based scraping, which proved highly fragile. Every minor UI update or structural change in a target platform could break the data extraction process, resulting in high maintenance costs, delayed data acquisition, and system instability. The client needed a solution that could adapt dynamically to interface changes without constant reconfiguration or manual intervention. - Need for Instant, Non-Disruptive Account and Balance VerificationsMany financial operations—such as fraud prevention, payment processing, and onboarding—require real-time verification of account ownership and balance. Traditional methods were too slow or error-prone to meet these operational demands. The client required a solution that could provide accurate verifications within seconds, at scale, without interrupting the user experience or increasing operational risk.
- Lack of Context in Raw Financial Data
Raw transactional data retrieved from financial institutions is often cryptic and difficult to interpret. Without enrichment or categorization, this data lacked the context needed for decision-making, user personalization, or business intelligence. This posed a significant challenge for the client, who needed to transform raw financial feeds into structured, meaningful information. - No Visual Tools for Real-Time Data Analysis
Given the volume and complexity of financial data being processed, the client lacked visual tools to explore, segment, and analyze the information effectively. There was a strong need for dynamic dashboards and real-time analytics that could consolidate enriched data and extract actionable insights—both for internal operations and to offer end users a clearer understanding of their financial behavior.
These challenges required us to rethink traditional approaches and build a resilient, scalable infrastructure that combined AI, asynchronous architecture, and advanced data processing to meet the demands of modern fintech operations.
Need for Instant, Non-Disruptive Account and Balance Verifications
Many financial operations—such as fraud prevention, payment processing, and onboarding—require real-time verification of account ownership and balance. Traditional methods were too slow or error-prone to meet these operational demands. The client required a solution that could provide accurate verifications within seconds, at scale, without interrupting the user experience or increasing operational risk.
Solution
Trawler combines computer vision, async workflows, and Open Finance standards to deliver scalable, resilient financial data automation with enriched insights and real-time processing.
Solutions we delivered
To address these challenges, the development team built an innovative architecture based on three technological pillars:
- Computer Vision, enabling the system to visually interpret interfaces instead of relying on fragile HTML layouts—ensuring resilience to design updates
- Asynchronous Orchestration, allowing high-throughput parallel processing, optimizing performance even under heavy request loads
- Open Finance Approach, ensuring scalability and integration readiness with fintechs and regulated data providers
Additionally, pre-built dashboards and data enhancement tools were developed to transform raw financial data into actionable insights that help personalize financial products and reduce operational risk.
Trawler not only overcame the limitations of traditional scraping, but also delivered a future-proof, intelligent solution for data acquisition in the evolving digital finance landscape.
Services & tech stack
Services
Product strategy
Product design
Web app development
Product strategy
Technologies
Open Finance
Asynchronous Architecture
Open Finance
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