Intelligent Risk Management

Background

Analysts at AIG scan hundreds of news articles daily to predict changes in the value of their investments.

To support these analysts, the Data Science team at AIG had a vision to build an AI-driven solution that could digest large amounts of new, unstructured data through cutting-edge machine learning to provide analysts at AIG with early and actionable insights.

Challenge

When Beyond was first consulted for the project, AIG's Data Science team had already created their machine learning algorithm and a basic user interface, called Intelligent Risk Management (IRM). With IRM, AIG was able to aggregate important investment news sources into a personalized feed based on an analysts portfolio.

However, the Data Science team at AIG found that analysts were uninterested in adopting a new tool—they believed that new products and processes would only slow them down in their daily tasks. To engage their analysts, AIG needed IRM to introduce as little friction as possible in their analysts day-to-day lives.

Our approach

At the start of this project, our team rapidly immersed themselves in existing research and technology currently developed for IRM by AIG.

From there, we conducted user interviews with analysts at AIG to identify core user needs. Additionally, we completed a UX audit of the existing platform (alongside competing data platforms) to identify potential quick wins. Once our initial recommendations were in place, we developed a roadmap to ensure priority alignment between our team and the client team.

Outcomes

We partnered with AIG to run a dual-track agile workstream, testing concepts while designing and developing a working prototype.

Additionally, we were able to partner with the Data Science team at AIG regularly to ensure our designs allowed user behavior to feed directly into the machine learning algorithm, increasing the accuracy of IRM over time.

In the end, we were able to develop a fully engineered, clickable prototype integrated with AIG’s IRM API using their coding standards.

Before the engagement ended, our design team also developed a system of components and high-fidelity designs for each future screen on IRM.

Project samples & additional details

While most modern websites focus on smooth, simple experiences, analysts at AIG want as much information at their disposal as possible.

User feedback often included the question, “Can we add another column here?”

Through user research, we learned that analysts typically managed a maximum of 3 portfolios at one time.

They felt that a successful dashboard would, for example, allow them to view all 3 of their portfolios at the same time.

Prior to launching IRM, analysts would use lists of articles within spreadsheets to track news that affected their investments.

By including this info directly within the platform, we were able to keep analysts on a single platform. Additionally, we could use IRM’s AI-powered backend to include predictions on which accounts may be affected by that specific news.