Empowering Innovation

A credit union can track historical deposits to determine the account types that are driving the overall growth (e.g., checking, savings, certificates of deposit, IRAs). Credit union users can also track new member money flows since onboarding to help guide members to the specific products and services which would benefit them based on deposit dollar amount changes.

A credit union can analyze the use of remote deposit capture (RDC) alongside member demographic data, such as residential addresses, to adjust its branch investment strategy or optimize adoption through marketing campaigns. By examining a map, the credit union can pinpoint the locations where members are utilizing the RDC digital banking channel. Comparing this with non-digital members can help determine where RDC campaigns should be conducted.

A credit union can analyze its shared branch transactions by channel to identify which branches are primarily being used for transactions that could be accomplished through digital channels instead. This helps in identifying actions that can improve member communication, increase digital channel adoption, and optimize shared branch cost structure.

A credit union can analyze growing member relationships. Credit union users can track the flow of member funds to guide them towards products and services that would benefit them, based on changes in deposit amounts. This enables the credit union to focus on fund flows before and after a significant financial event, helping their members thrive during income challenges.

A credit union can analyze and monitor the performance of their individual branch employees related to the placement of different products, such as deposits, to identify areas of excellence and/or areas of improvement that should be addressed to meet the branch performance goals.

A credit union can analyze and monitor the performance of their individual branch employees related to the amount and type of transactions to identify areas of excellence and/or areas of improvement that should be addressed to meet the branch performance goals.

A credit union can identify which branches have loans at a higher risk of default. This allows the loan portfolio manager and the branch manager to take mitigating actions, coaching employees to modify the loan strategies to reduce the loan portfolio risk.

A credit union can identify intrinsic loan risk by looking at the type of loan product and the associated credit risk trends. This allows the loan portfolio manager to understand which products perform better than others and implement actions to improve the overall loan portfolio risk position by modifying the product placement strategies to increase or decrease the portfolio risk levels.

A credit union can identify distribution of cumulative loss over time. By assessing or filetering by type of product, the loan portfolio manager can identify the products which perform better than others and strategize actions to improve the overall Loan Portfolio.

A credit union can identify trends in charge-offs and loan losses by credit tier over time. This allows the loan manager to analyze current and past trends in charge-offs by credit tier, which can be used to enhance loan approval strategies and minimize future loan charge-offs.

A credit union executive can monitor the current performance and trends over time of key metrics, such as the total loan portfolio, total deposits, and member base, to identify potential areas of risk or improvement to achieve the yearly credit union goals.

A credit union can identify members that have declining deposit trends. This will enable the credit union to identify members that are experiencing situations of financial hardship. By utilizing the member data extracted from the platform, the credit union can take actions to help those members, but also can monitor the credit union’s performance against its liquidity targets.

A credit union can identify trends in the number of accounts opened per branch. Credit union users can use this data to address branches that are not meeting the new membership target. They can also analyze the branch ratio of loans vs. deposits to identify areas of opportunity for improvement.

The credit union management can analyze the performance of their loan officers in reviewing and approving new loans to identify areas of possible improvement.

A credit union can evaluate the current and past distribution of loan products to determine if the distribution aligns with their loan goals and strategy. By securing a detailed view by loan product and by branch, a credit union can quickly identify and address challenges in opening highly profitable products at the branch level.

A credit union can quickly identify maturing loans and take the necessary actions to renew the lending relationship with its members. Possible actions include outbound calling campaigns, online banking notifications, or flagging members for interaction at the branch.

A credit union can analyze the details of its total loan portfolio balance over time to determine trends and areas of possible improvement.

A credit union can map where its members are geographically located and compare the number of accounts and balances in each geographical area. By doing so, a credit union can determine opportunities for growth and identify its strongest market locations. This can help focus on local growth campaigns or optimize investments in new branches.

A credit union can analyze the distribution of its members by age and gender to determine its membership demographic profile and future trends. Finding inadequate penetration within the youth population can indicate that the credit union needs to focus on new marketing strategies to tap this important segment of the population. Member gender analysis can help the credit union monitor the gender fairness in account opening practices and potentially reduce its overall risk profile.

A credit union can analyze credit card balances by branch to determine areas of strength and opportunities for increasing card balances. The credit union can use this information to identify branches that need more focus on balance transfer campaigns or discussions with members about the benefits of using the card compared to bank or FinTech cards.

A credit union can analyze its credit card accounts by risk tier to determine the effectiveness of overall card risk mitigation efforts. Looking at trends by year can help determine the effect market conditions have on the card portfolio and allow the credit union to identify strategies for mitigating risk.

A credit union can monitor and analyze the total outstanding amount collected and repossessed by each collection operator to identify the best-performing employees and their best practices to increase overall collection performance.

A credit union can identify the next two most beneficial products for every member based on member demographics and historical behavior. This use case empowers the credit union to achieve a better match between the credit union product offerings and the members’ real needs, driving a quantifiable increase in member satisfaction, engagement, and revenue.

A credit union can identify actions that could be implemented for a specific member and the best viable option to implement them. This use case uses demographic and behavioral data to recommend actions to increase product penetration, promote online channel usage, promote services through educational materials, and tailor personalized messages to increase the level of member engagement and satisfaction.

A credit union can segment its members into predefined personas based on their level of engagement and channel activity to easily identify members with low engagement and target those groups with specific promotions and engagement campaigns.

A credit union can determine members’ actual and future value to target the most valuable members while minimizing expenses on less profitable ones.

A credit union can identify the members who are more likely to become delinquent in the future to take proactive steps and avoid delinquency management and collection costs.

A credit union can identify the members at risk of leaving based on their behaviors and level of engagement. This use case allows the credit union to implement a targeted approach and work with ‘high-risk’ member groups to reengage and retain them.

See How You Stack Up: Trellance’s Advanced Benchmarking product allows you to create customized peer groups based on asset size and geographic location to see how you stack up against comparable credit unions. With fast and easy implementation, you can start seeing insights right away into how your credit union is performing compared to others. Using data from Form 5300, Home Mortgage Disclosure Act (HMDA), and other industry and economic reporting, see and compare key metrics, lending trends, and composition as well as profitability. Advanced Benchmarking also includes a Current Expected Credit Loss (CECL) calculation based on Weighted Average Remaining Maturity (WARM). Even if you’re not using the WARM methodology for your CECL calculations, use this to assess the reasonableness of other methodologies.

A credit union can utilize the comprehensive portfolio risk data to analyze the risk by loan type and propensity to migrate credit. This allows the credit union to be proactive in deterring losses by completing proactive campaigns and altering loan approval policies to mitigate risk.

A credit union can use this tool to optimize their risk-based pricing structure by comparing earned interest rates to the specific costs of underwriting, approving, funding, and managing various loan products, credit characteristics, and origination channels.

A credit union can streamline its processes for calculating the allowance for credit losses by having access to a wide variety of generally accepted CECL methodologies, ranging from sophisticated methodologies driven by loan-level data to less complex methodologies requiring no data input from the credit union.

A credit union can quantify the strategic risks to serve its members by analyzing the current portfolio risk, evaluating the macroeconomic volatility of the geographic areas served, and performing scenario analysis to stress-test the credit risk under the harshest potential conditions.