AI Assisted Trading App, Based On Conversational-AI Trading System | For Analystika CA

UX Design & Research / Done in: 2019-2020 / For Analystika CA
For privacy and NDA I can not share final and high fidelity/ details of this project.

Project Overview

The Client

Analystika (Development in progress)

The Challenge

To create a user friendly trading app that works like a bot but uses AI and and uses users input to deal with the risks

Outcome

A series of social features and interactive wizards were designed, based on gathered data, target group feedback and surveys

Roles:

UX Designer (research, interaction design, visual design)

Responsible for redesign, animation, wire frames, prototyping, discovery and ideation, user research, interaction design input

Personas

Persona creation for auto trader app

I used all of the data i gathered during the research process to create a main centric target persona. Since the auto trading mainly 2-sided service, meaning it is used by more than one user type, I wanted to capture reflection of both types of users through my main persona the Newbie John because it covers both. In this case “Newbie trader” lets cal him John, is the target. But who is john?

John is interested in trading while has no knowledge in trading TA or fundamentals of trading. So we only ask him how much he wants to invest and how much risk he is willing to take.

Designing for traders of all levels

Design Priorities

A high-level list of app features was created to further define and guide the vision for the product. Prioritizing the features with supporting research created a clear order of execution.

Interaction Design

I completed a task flow and user flow to imagine the ways a user might /should navigate through the service using the feature to achieve their goals we implemented.

Wireframes: Low & Mid Fidelity

I began the process of wireframing with sketches and considering some precedents in our studies to use user knowledge and make it more intuitive. During this process, I thought about how the layout and content could be structured to satisfy user and business goals in a technically feasible way. The sketches I chose served as a guide for my digital wireframes and then the prototypes.

Colors and Branding

Next, I created a UI Kit, a comprehensive collection of all components and UI patterns used on the platform. I used branding guidelines of the graphics the platform already had as the starting point and added components such as buttons and navigations bars as well as new icons I had created for the social feature.

What Is A Smart Trading App?

The App is to deliver a consumer experience in auto trading applications. There is not much of a precedent for the actual use of AI in trading if there is it is not a public platform and there is certainly no precedent for the design of such an app for consumers.

The trading app or what they are traditionally called, “bots”, are usually lines of code for mainly commercial usages and they don’t really have an interface. They are made to make smart day trading and they do all the job with no need to be modified by users.

Analystika is currently working on a project to bring the concept to consumer level and give the option to use data and AI to trade. The codes are still being worked on in 2020. The current design is the result of a research and design process to bring such unfamiliar system for people to consumer level.

Assets Portfolio Page

Here is a glimpse of the Signal wizard

The architecture behind the conversation

For the Conversation to be shaped and going smoothly and dynamically a very comprehensive architecture was designed, and also to map the possibilities of the conversation to be reflected intuitively into the interface.

Signal making and starting to control

The Signal wizard is to get as much as possible info to create an auto trade. Each trade can be unique based on many variables that the underling AI has as input. So the current you see in the prototype is not final and the main info are confidential. But to show the wizard workflow there are placeholders in the UX design.

After the information is gathered the signal is made and user goes to a page that the app suggests all the confirmed or potential trades that he can enter. In semi mode, the user has the ability to modify the ongoing trade so a bit more complex comparing to the full auto mode.