CAP COM’s business analytics and business intelligence (BABI) team works with ERM and business units across the credit union.
The comprehensive approach uncovers problems hiding behind singular views, such as FICO scores not reflecting the potential impact of loans in forbearance.
BABI reports contain data, particularly around credit risk, that empowers decision-makers.
For the past three years, CAP COM Federal Credit Union ($2.6B, Albany, NY) has been honing its abilities to reduce risk and maximize reward — taking care to not throw out the BABI with the bathwater.
“BABI” is shorthand for the business analytics (BA) and business intelligence (BI) division the cooperative created in January 2018. The BABI team generates and interprets data as well as makes intelligible reports available to stakeholders across the enterprise.
Directing that effort is Mike Wiseman, manager of business intelligence at CAP COM. Wiseman joined the credit union eight years ago and spent the first five managing the credit union’s project management office. He then joined the newly formed BABI team and took the helm in October 2019. The team currently consists of Wiseman and two business intelligence analysts.
Mike Wiseman, Manager of Business Intelligence, CAP COM FCU
How does CAP COM define risk tolerance? Who sets it, and how does it affect what you and other departments do?
Mike Wiseman: We set our risk tolerances in various ways. Often, our limits or tolerance levels are driven by regulatory requirements, where there really isn’t room for interpretation. Other times, our risk thresholds are established as part of an enterprise review process, where our business owners and stakeholders work in coordination to establish the limits.
Organizationally, we have a dedicated enterprise risk management team. Our business units and our BABI team partners with this team to review and interpret the data to determine if adjustments to tolerances are needed.
We also have a cross-functional ERM committee that meets on a routine basis to review and discuss overall risks to the organization and help it focus on and prioritize designated areas.
How do you use data to track and graph risk tolerance monthly?
MW: We are currently using data to track risk and tolerance levels across multiple areas. For my team’s area of responsibility, we focus on risks associated with the credit union’s lending portfolios.
For example, we track and trend aggregate loan balances and member credit scores to understand potential exposure risk within any given portfolio. We’re also in the process of enhancing our delinquency and charge-off trending to identify potential risks within a portfolio and support the ability to be proactive versus reactive.
“Our team not only makes the data available for the relevant stakeholders but also makes it digestible.”
What software tools do you use for tracking and reporting?
MW: The tools we use to monitor risks and tolerance levels vary depending on the metric and subject area. Sometimes it’s as simple as keeping a spreadsheet updated monthly with the relevant information.
For some of our more complex or in-depth tracking, we’re migrating to leverage our enterprise data warehouse to support key performance indicator tracking and trending via Power BI dashboards.
For example, this year we implemented a new Power BI dashboard to better track and trend risk ratings and exposure in the credit union’s commercial loan portfolio and understand concentration risks within specific industry sectors and borrowers.
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Who does the tracking and who gets the reports?
MW: We track and report on different metrics differently throughout the organization. For example, we might report charge-off or credit card fraud trends to the board of directors, whereas we report credit score migrations and other risk metrics to strategic committees such as the credit union’s asset liability committee.
How does your work help the credit union more effectively deal with existing risk?
MW: Our team not only makes the data available for the relevant stakeholders but also makes it digestible. It is extremely difficult to see trends or monitor performance by looking at rows of data in a spreadsheet.
For example, if your member FICO scores have remained constant over a period of time, you might not observe risk in your portfolios. However, if a large portion of those loans have been deferred due to COVID-19, you might have some hidden issues that might become a problem if you aren’t monitoring the entire process.
Our team has revealed those ancillary data points to bring more color to what might have been singular data views in the past.
“Helping our stakeholders pull the thread is one of the biggest values our BABI team brings to the organization. Sometimes you don’t know the questions to ask until you see your data paired with results.”
How does your work help the credit union more effectively deal with risk, existing or new?
MW: Helping our stakeholders pull the thread is one of the biggest values our BABI team brings to the organization. Sometimes you don’t know the questions to ask until you see your data paired with results.
However, having a dashboard doesn’t mean anything if it doesn’t include definitive action steps to take. We’ve been working to implement a monthly focus group where our BABI team walks through the data analysis with our business stakeholders. Together, they jointly develop action items with targeted deliverable dates to help ensure all parties maintain progress.
How has the pandemic and CAP COM’s response to it affected your risk profile? Did it raise concerns about fraud, or delinquency, or both? And if so, how?
MW: COVID-19 required us to rethink many services, especially related to risk and fraud. As new government programs were introduced — like enhanced unemployment benefits and PPP loans — we saw a swift migration of fraudsters looking to exploit those programs. This newly developing reality required us to update how we tracked and monitored related metrics, which enabled us to better prepare to identify those types of fraud occurrences.
CU QUICK FACTS
CAP COM FCU
HQ: Albany, NY
Data as of 06.31.21
12-MO SHARE GROWTH: 24.6%
12-MO LOAN GROWTH: 9.5%
Additionally, the uncertainty of economic conditions and where the bounce-back was heading required us to adjust — from how we planned our budgets to how we allocated funds for potential loan losses.
I think the pandemic forced us as an organization to look at the data differently. Even the mechanics of data delivery shifted because we weren’t all sitting in a meeting room looking at a presentation. We needed to have reporting and data available that was easy to digest and accessible in a virtual manner.
We also were concerned about the effect the pandemic had on members. One of the key items we’ve been tracking are which communities of members are receiving the most unemployment funds. This has helped us understand if there are potential pockets in our local area that have been impacted at a higher proportion by pandemic-related ripple effects, such as shutdowns, so we can adjust our processes to address concerns in those areas.
This interview has been edited and condensed.
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