Using Member Data to Drive Lending

Technology has evolved to enable comprehensive and unprecedented access into a member’s past credit behavior, ultimately enabling users to see the probability of future credit behavior. However, most credit unions have not yet taken advantage of this technology to more closely align member behavior patterns with strategic goals and priorities. Financial institutions that can maximize member insight will ultimately make more targeted decisions and enhance business performance.

Members’ future credit behavior is unknown, however it can be predicted using what is known: members’ past credit behavior. Utilizing historical member-level financial data – up to 24 months’ worth – provides credit unions with actionable insights into a member’s potential next financial move.

Leveraging technology and past member credit behavior can help credit unions determine the best targets for acquiring new profitable accounts as well as best steps for optimizing account management, such as early risk detection, cross-sell opportunities and even options for offering new opportunities to a member who would not previously have qualified for a particular offer. Ultimately, this view of members’ past credit behavior helps to balance credit union growth, identify new marketplace opportunities and differentiate from the competition.

Leveraging Members’ Past Behavior

To confidently make credit decisions that align with business strategies, credit unions must make sense of credit data across all members and define the financial behavior of the ideal member.

Financial tendencies are better understood in patterns. These patterns enable credit unions to identify market segments that need the most attention. Using up to 24 months of credit history can help identify the most ideal member segments with a focus on ultimately predicting future member credit behavior.

Credit unions can balance growth and increase efficiencies by utilizing historical financial behavior to help determine the best business strategies across a member’s lifecycle. This truly is a game-changer for credit unions.

The Power of Attributes

Credit attributes are characteristics derived from a member’s credit behavior and used to help define the decisioning criteria needed to make confident lending decisions. Using attributes that are built from 24 months of credit history enables credit unions to quickly analyze a member’s credit profile and identify unique sets of behavior trends and credit characteristics, such as a member’s:

• credit patterns – which account, when, how much and how frequently;
• utilization changes – established patterns and impact of changing behavior;
• wallet share – derived when combining internal and external data to understand the member’s activity with the credit union and its competitors; and
• propensity – focus on accounts likely to open, activate or transfer a balance.

Through the use of trended attributes, credit unions can better manage credit decisions across the entire member life cycle – from acquisition to account management to collections – to create effective segmentation strategies. Some service providers even provide attribute bundles that can help define the best attribute combination to move the needle for a specific action, such as increasing account open rates or determining the best candidates for balance transfers.

Game-Changing Benefits

The ability to identify specific member trends can help credit unions deliver game-changing benefits – both in the boardroom and with its member base.

• Twenty-four months of credit data, such as balance, payment and credit limit, can differentiate behaviors to deliver key inputs for strategic decisions, like spending ratios against certain factors and predicting capacity to incur additional debt while staying current.

• Analyzed and detailed characteristics enable credit unions to better understand and evaluate a member’s credit risk, ultimately identifying the necessary steps to take to meet business objectives. For example, can the credit union detect when risk goes up and decrease its exposure before a consumer becomes delinquent?

• Make better credit decisions by incorporating trended historical member level data into real-time underwriting criteria. Better understanding member life cycle trends enables credit unions to make more knowledgeable decisions and offer relevant opportunities to specific members.

• Targeting accounts that have a higher propensity to be active enables credit unions to achieve increased member satisfaction and make more efficient and targeted decisions. Similarly, focusing on accounts that have a higher propensity to spend enables credit unions to drive profitability and growth across their portfolio.

Due to changing member credit behavior, there is a need for credit unions to maximize acquisition and account strategies through deeper member insights. A comprehensive view of a member’s past behavior and the ability to see the probability of future behavior enables credit unions to make relevant offers and decisions for specific members. By leveraging this data, credit unions can more effectively manage the entire member lifecycle.

Megan Strub is senior director of product management for Equifax, Inc.