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# fintech

a fintech app for individuals investing on the stock market

Django REST Framework
Information Architecture
High-fidelity wireframes incl. data visualization
UX analysis
UX design
UI design
Style guide
Custom illustrations
Functional Testing
Non-functional load testing


excel rows as basis for 1 usable mobile app


firms updated in 75 seconds (stocks, EPS and Price & Value)


concurrent requests handled by the API


different types of charts used for data visualization

problems to solve

Increased participation of investors in the capital market brings to the fore the problem of knowledge inequality. Institutional investors have models and an abundance of data to make informed investment decisions. At the same time, individual investors often lack such actionable information when choosing particular stocks.

Yowlo fills the information gap that individual investors suffer from when making their stock trading decisions. With this mobile app, they can finally take advantage of the vast knowledge available.


The client approached us with a preliminary vision for the mobile application and low-fidelity wireframes. The stakeholders planned to present the final product to around 1,000 people at an industry conference. Considering their outsourcing needs, the client chose to collaborate with Merixstudio on product development while providing the Product Owner on their side. We started off with online workshops that helped lay out the business context necessary to implement the client's vision.

The new product would aggregate information about the market capitalization of stock trading companies and the financial prognosis for their future stock market standing. The means for gathering these insights is a complex algorithm — the result of 10-year long academic research of the app's creator.

The client’s extensive domain knowledge helped a great deal in shaping the future product. We also had discussions with the stakeholders to keep the information flow going and justify the product decisions made. Such a well-reasoned approach allowed us to implement the most user-friendly ideas and facilitated the product’s gradual development.

We started by developing a Proof of Concept (PoC) by implementing the financial algorithms delivered by the client. We relied on the Scrum and Kanban methodologies throughout the product evolution process to facilitate the development work. Online meetings with the client across two time zones allowed us to tailor the scope and requirements to the client's current needs.

The scope of the works included:

  • Conducting workshops to establish the requirements and scope of works
  • Developing a brand new mobile app
  • Designing the UI and UX of the application (including high-fidelity wireframes and illustrations)
  • Performing the mobile and backend development works
  • Translating complex Excel algorithms into a highly-usable mobile app
  • Visualizing API-delivered data using charts
  • Executing Quality Assurance works
  • Ensuring the app’s optimal performance thanks to load testing in a staging environment
  • Conducting DevOps works

The core of the mobile application is based on Flutter, a highly performant Google-backed cross-platform toolkit utilizing a single code base. Firebase helped achieve the desired app quality, monitor its performance, and run tests. The resulting quick build deployment and fast accessibility of new accretions for testers' eyes significantly accelerated our workflows.

Django Rest Framework (DRF) served as the backend for the app. We also used PostgreSQL for CRUD operations. The API handled stock market data, keeping it up-to-date and useful. To reap performance benefits, we used the Redis message broker along with Celery for easy integration.

The team executed a containerized setup in the cloud using Docker and Elastic Container Service (ECS) to provide independent services. We also used the GitLab tool to run tests on CI/CD and deploy the app to AWS. Additionally, we stored data using AWS S3, which offers high availability at a relatively low cost. To avoid time-consuming commit management, we relied on decentralized feature branch workflows.

The team executed optimization works designed to accommodate the heavy traffic load on the API. We utilized K6 for creating and executing test scripts and Sentry for application health monitoring and reporting. Additionally, we conducted manual functional and interface testing on mobile phones and tablets with Android and iOS systems.

The implemented functionalities maximize users' knowledge necessary to make sensible investment decisions. To that end, the app combines users' industry insights with real-time market data to produce valuable forecasts. The tricky part about this complex data world was fitting nuanced financial insights in a digestible form on a tiny mobile screen.

Our intuitive visuals successfully supply the target audience with the necessary information while keeping the intricacy hidden underneath the app's neat looks away from users' eyes. We made the best out of Flutter, using the Canvas class for customized, animated widgets, and Flutter Charts and Google Charts to create powerful data visualizations. We also utilized an API that feeds the current and past financial values onto the charts. This way, the user can see important developments affecting their stock-related decisions. Additionally, we created custom-made illustrations to facilitate effective user onboarding upon first access to the app.

The end product won the hearts of target users during a presentation at an industry conference. Achieving this success wouldn't be possible without close collaboration with the client. By engaging our experts in meetings with the stakeholders, we could create a business analysis and action plan that were instrumental in creating a fully functional product. As a result, the app lives up to its promise of providing equitable access to advanced financial knowledge for stock market investment enthusiasts.

view examples

key features

  • earnings per share (EPS)

    this functionality displays the evolution of the EPS forecast. The panel presents a plot that summarizes actuals and market forecasts. Having that available combined with specific industry knowledge, users can modify the predicted sales and margin values to check their effect on EPS

  • market briefing

    in this feature, users have three subsequent sliders: Market Overview, Up Movers, and Down Movers. The Market Overview displays the current Exchange-Traded Funds (ETFs) editable from the admin panel. The Up Movers feature allows the user to see five charts with the stock-listed companies demonstrating the most significant stock value increase in the last 24 hours. On the other hand, the Down Movers functionality features the stock-listed firms with the most severe stock value loss since the day before

  • price & value

    the feature forecasts the stock price during the subsequent ten years. An essential part of this functionality involves the user changing the predicted sales value and margin to affect the final forecast. This way, the target audience can create their stock projections based on the available information

  • stock market API integration

    the feature allows for presenting the New York Stock Exchange data within the mobile app. The presented charts change in real-time, helping the user establish if anything happened that the forecast did not cover

other works

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