PryvX. Collaborative Fraud Prevention Platform

Pryvx

is platform helps organisations to combat fraud and cybercrime through collaborative efforts by leveraging privacy enhancing technologies, such as federated learning.

In today's increasingly digital world, cybersecurity has become essential for individuals, businesses, and governments alike. As we rely more and more on technology and the internet, our personal information, financial data, and critical infrastructure are all at risk from cyberattacks.The issue is that each telco and bank is trying to tackle this independently.

is to pioneer a collaborative and secure frontier in the battle against cybercrime. A world where organizations unite their strengths, share insights, and leverage collaborative learning to stay one step ahead of attackers.

Research:
✱ Competitor analyses.
✱ The application audit.
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UX Design:
✱ User flow, architecture and structure of the interface.
✱ Wireframing.
✱ Prototyping.
✱ Testing.

UI Design:
✱ Development of design system:
Creation of new advanced components, merging and optimization of current components.
✱ Integration of APIs and collaboration hub, improving the flow of creating a new project.
✱ Communication with the development department and design iteration.

PROBLEM

My role

Mission

Design Process

I aimed to follow a classic iterative design process for the platform.
However, I took a more flexible approach for certain features, potentially skipping prototyping, testing, or sketching if they already had a proven user pattern and didn't require further refinement.
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Platform Architecture

The platform architecture map clearly illustrates that the primary end user action is to use APIs. There are several ways to get to the API. It is API itself, Shared database, Projects.
In addition, the user has the opportunity to collaborate with others, combine data to improve the quality of cyber security

Creating new project flow

Initially, the creation of a new project was presented as one large form. After competitor research and testing, it was found that dividing into steps would help users fill out the form faster by focusing on specific inputs.

Step 1. Define project

The user interface allows users to name their projects, assign tasks, and select algorithms. To make the tasks more understandable, they are visually represented using illustrated cards.

Step 2. Configure ML settings

The system comes with pre-configured settings as a starting point. Nevertheless, users have the flexibility to personalize these settings to tailor the algorithm's training process and achieve their desired outcomes.

Step 3. Import dataset

The user has the flexibility to choose a specific date from the preloaded database to begin training and can customize the output by selecting the desired categories.

Step 4. Collabaration

The platform allows users to invite other registered users to collaborate and contribute to improving the accuracy of machine learning outcomes.

CollabRATION HUB

The collaboration hub functions as a secure environment for sharing information. It is segmented into two distinct chat channels: an alert room and a standard chat. The alert room is a dedicated channel equipped with a reporting form for flagging suspicious spam. The standard chat is designed for general communication and information sharing.

Fraud detection APIs

APIs serve as the primary function of the platform. Various APIs types are supported. To facilitate navigation, a basic word search and a filter are included (popular APIs are displayed as filter bubbles beneath the search bar). Users can choose to view APIs as a grid or list layout.

PryvX.Collaborative Fraud Prevention Platform.

PryvX.
Collaborative Fraud Prevention Platform.