EY
Project Outline
An exciting opportunity presented itself when we were tasked with helping EY and their TAS teams design a predictive financial platform that can identify companies looking to be acquired within the next 3 years. As part of a Moonshot team consisting of like-minded engineers, data scientists, and guided by EY's Global Innovation leaders.
We started by conducting thorough user interviews to gather requirements and define the scope of the product. Using this information, we prioritised each feature and delivered a custom platform identified as a unique proposition within EY's ecosystem of products, with its own identity and functionality. From wireframes to high-fidelity designs, we created a product that exceeded expectations and made a lasting impact.
Outcome
We were thrilled to deliver an Alpha version of our product to the EY internal teams. Our solution draws from the extensive S&P 500 data source and enables their teams to query a web interface to identify companies that are most likely to be acquired within the next three years.
To create this game-changing platform, we started by conducting user interviews to identify their requirements and define the scope of the product. We then prioritized each feature and defined deliverables, always ensuring they aligned with EY’s workflow.
From Lo-Fidelity wireframes to Hi-Fidelity designs, we worked tirelessly to deliver a custom platform that would stand out as a unique proposition within EY's ecosystem of products, with its own identity and unparalleled functionality. The result was a cutting-edge solution that provided EY teams with an innovative tool that revolutionised their acquisition analysis process.
Key Challenges
Create a custom design language for ML’s output
Aggregating data patterns from multiple sources
Working with complex internal team structures
Requirements changing every 2 sprints
Fast-paced environment