Problem
“How can I quickly visualise the data to combat financial criminal activity?”
Apate
Apate is a company that detects, combats and monitors financial criminal activities by harnessing the power of data. They want to develop a tool that will provide a visualization of data patterns as a means to more quickly detect and stop these unwanted activities and protect businesses using their services. Their focus is to ship out a minimal viable product.
Project details:
My Role: UX/UI Designer and Researcher
My team: Product Manager, 2 Back-End Dev, 1 Front-End Dev and myself as UX Designer
Tools: Sketch, Figma, Pen&Paper, Google Forms
Deliverables: UX Research Report, Wireframes & Prototypes
Have a closer look at the prototype here.
Interviews in the office
I started by shadowing our target users – analysts. This allowed me to observe their work flows and review their key performance indicators so I could better identify opportunities to incorporate our tool in their workflow. I also uncovered some interesting tools that they had used in the past and translated them into requirements for the new tool.
Key takeaway: Most analysts use around 5 tools to detect patterns, take action and summarise their investigation per assigned ticket.
Opportunity: By reducing the amount spent investigating in each tool, we could dramatically improve their KPIs.
Align on project requirements and constraints
Once I had summarised my research, I shared my findings with the Product team and we translated these insights into opportunities. We then prioritised the requirements needed for the MVP which aligned with business goals, user needs and engineering capacity.
Explore possible interface structures
Based on the requirements as well as research into similar interfaces, I brainstormed ideas while keeping in mind industry standards. By working closely with the product team, and with continuous rounds of feedback, we were able to define what interface was possible to build within the given time-frame.
Validate usability of interface
Before launching the product, I created a prototype based on the components from the design system for easy handover and decided to run usability testing. I observed how analysts incorporated the tool in their workflow. I then made multiple iterations based on their feedback (exporting options, label info, accessibility) and some of these features were implemented for the MVP.
Result: slow adoption but high interest
Although there was a high interest for this new tool, only around 25% of analysts actually incorporated the tool in their workflow since the launch. Users required more features and support to transition away from other tools. All in all, it was a successful product in regards to validating the calculation of node points, the engaged users did detect fraudulent behavior 5 times faster and improve their KPIs, and it set in motion further iterations with added features.
Learnings & challenges
Being flexible was important to gain the trust from the product-team as unforeseen time and resource constraints meant constant change of requirements.
Involving the end users more in the process would have created more engagement and buy-in to use the tool.
Raising the company’s awareness about UX in order to manage their expectations was important.