Banking Industry
Many years of experience in the banking sector include working on both client-face applications and large back-office systems used by analysts from the world's largest banks. Among them, advanced risk management tools using machine learning.
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The value of polish export exceeded 200 billion euro in 2018. This platform offers assistance in access to necessary information on foreign markets as well as in obtaining financing for company’s activities.
Creating an export support platform was a team effort and involved months of work, regular meetings with bank representatives and analysis of the competition. The solution developed allowed for creating a background for expanding the bank's offer with support products for entrepreneurs trading with foreign entities.
Mobile App
Client Scoring Tool
Thanks to the use of artificial intelligence and predictive analysis, the bank can better assess risk and adapt credit offers to the client's profile, while ensuring compliance with financial regulations. This is an advanced tool supporting the assessment of the creditworthiness of the bank's clients based on the analysis of their transaction history, demographics and financial behavior. The system enables customer segmentation, credit risk prediction and optimization of financial offers.
Scalability
The tool is designed to easily accommodate new modules and functionalities, as well as support additional data sources.
Customization
The interface allows to configure visual identity elements and dynamically manage active modules based on business needs.
Integration
Adaptation to any environment thanks to the use of containers, which enables rapid implementation in various infrastructures.
Segmenting customers into four risk levels automatically proposes available financing options. Each level defines the maximum loan amount, repayment terms and additional requirements, such as guarantees or higher interest rates.
Made with:
User Journey
A key aspect of our work was maintaining a consistent layout, interaction style and navigation patterns.
Our approach not only improved the user experience, but also resulted in higher conversions and better engagement rates. Through iterative testing and data analysis, we managed to create a consistent, transparent and effective user process.
KYC Process
The UX project concerned a back-office system for screening customers (KYC), which automates the analysis process thanks to bots scraping the network in search of information. Data collected by bots is then presented to a bank analyst, who makes the final decision on customer verification.
The design process was based on the UCD (User-Centered Design) approach, and the work began with interviews with bank analysts to thoroughly understand their needs and challenges. On this basis, UX prototypes were created, which were iteratively tested and improved. Then, the UI interface was developed, focusing on data readability and user efficiency. After the tool was implemented, usability tests were conducted with analysts, which allowed for the refinement of key functions. The final system significantly speeds up and simplifies the analyst's work, eliminating manual search for information and increasing the accuracy of decisions. Automation allows for faster risk detection and compliance with KYC regulations. Thanks to this, the bank gained an efficient, intuitive tool that optimizes the work time of the analytical team.
