The current state of a financial institution’s risk profile may impact the interest rates it’s able to offer for new credit/loan accounts as it looks to mitigate/minimize its risk. Since the financial crisis in 2007, CPM teams have relied more heavily on data to keep up with evolving regulations. Changes to federal regulations mandating certain levels of capital and liquidity have forced drastic changes within organizations to achieve compliance, and to have higher visibility into how clients’ risk profiles are changing. These teams need tools to help them effectively explore their data and proactively make decisions.

The client needed a high-level view of their overall risk profile over time. Understanding their current level of risk exposure, and their industry comparison, may play a large part in making credit and lending decisions.

In the upper left corner of the dashboard, 3 composite risk categories are introduced and defined as many users may not have a good understanding of what distinguishes a good vs. bad score. This tile also shows basic metrics – ‘# of Accounts’ and ‘Avg. $ Owing’ – for the 3 categories along with links that will guide users directly to a list of accounts for each.

Large font key performance indicators (KPIs) and gauges paired with trend charts compare client’s scores to the industry average for both delinquency and bankruptcy risk, which quickly shows they are currently taking on more risk than most companies (and have been for over a year and a half!).

The bubble chart shows the majority of accounts are classified as ‘Category 1: High Risk’ and several have a very high outstanding balances (larger bubbles). The Category 1 accounts are highlighted without deviating from the color scheme by decreasing the color intensity of the bubbles associated with lower risk accounts. This visualization also allows users to intuitively drill in for more detailed account information by clicking individual bubbles.

The area chart, which can be toggled between risk of delinquency and bankruptcy, currently shows the percentage of Class 5 (highest risk of delinquency) accounts has been growing over the past couple years and makes up nearly half the client’s open accounts as of September 2017.

Visuals that quickly and clearly convey high level information are critical for creating effective dashboards. Powerful tools like QlikView, QlikSense, Tableau, Spotfire, etc. also allow users to quickly drill in and extract more detailed information directly from a dashboard with only a few clicks. For example, clicking a quadrant in the bubble chart produces a pop-up with the # of accounts and $ owed as well as a link to the filtered table in the account list. Hovering over the stacked area chart gives “details on demand”, which prevents overcrowding and allows users to focus only on details they want to see.

Summarized Points:

• Consistent color scheme across all visualizations – the same color indicates the same thing.
• The color red has a negative connotation: more red (higher risk) = bad.
• Bold and larger fonts used to show key metrics while smaller or faded fonts show detail or legend information.
• Using the same time scale across multiple visualizations better enables users to notice trends in their data.

The Contributors:

Jessie Lian is a UX designer at Axis Group, she has a background in information management and business. She has a passion for understanding people, a fascination with info viz, and an obsession with color palettes. You can often find her celebrating & contemplating in the great outdoors.

Patrick Mangiagli got his BS in Ceramic Engineering and MS in Composites Engineering from Penn State, then joined Axis in 2013. In his spare time, he enjoys being outdoors any time of year and taking his mutt for long walks.

Luis Nario et al. “The Evolving Role of Credit Portfolio Management.” https://www.mckinsey.com/business-functions/risk/our-insights/the-evolving-role-of-credit-portfolio-management. Accessed 2 April 2018.