In the world of credit risk management, understanding the performance of different portfolio segments is vital. It’s not just about knowing the current state of accounts but also about predicting future behavior and managing risks accordingly. This is where vintage analysis comes into play.
What is Vintage Analysis?
Vintage analysis involves examining accounts based on when they were opened or “originated.” By grouping accounts in this way, financial institutions can monitor performance over time and assess the risk associated with different campaigns, products, or markets. Let’s break down how this works and why it’s an essential tool for credit professionals.
Tracking Portfolio Performance Over Time
Suppose you’re running different client acquisition programs during various quarters. You might want to evaluate the risks and successes associated with each program. In doing so, you know which programs to stop, continue or modify. Vintage analysis allows you to do precisely that.
For example, you might group accounts based on how long they have been opened, referred to as “months on books” (MOB) in loans and credit cards. Then, you could track how many of these accounts become delinquent after a certain period. Since most card issuers revoke accounts at 90 DPD, we will use this as an indicator for bad accounts in this example.
In the table above, accounts are categorized based on their booking or opening dates, represented under the MOB (Months on Books) column. The percentage of accounts that reached 90 DPD (Days Past Due) is calculated for each group, allowing you to identify which segments may pose greater risks to your portfolio. Notably, the table reveals that accounts booked between January to March exhibited the highest likelihood of reaching 90 DPD within a 12-month timeframe. The group in question began with a delinquency rate of 0.56% in the initial 90-day period, gradually escalating at a near-constant rate to conclude at 2.32% after 12 months.
This detailed analysis enables your risk and analytics team to pinpoint the segments demonstrating higher-than-average delinquency. Should a particular campaign be identified as performing poorly in comparison to others, vintage analysis can initiate a thorough investigation into the underlying reasons. These insights not only shed light on specific areas of concern but also provide valuable guidance to refine and improve future risk management strategies and campaign effectiveness.
Improving Credit Policies and Client Acquisition
As you can see above, vintage analysis provides a snapshot of different portfolio segments’ performance over time. By identifying specific groups with an alarming delinquency rate (e.g., accounts reaching 90 DPD), financial institutions can uncover underlying risk patterns.
For example, if accounts opened in Q1 have a higher delinquency rate than those in Q2, it might indicate a problem with the credit policy applied during that period or with the type of clients targeted. By drilling into these details, the financial institution can:
- Re-evaluate Credit Scoring Models: Are the current credit scoring models adequately predicting risk? If not, they may need refinement.
- Adjust Underwriting Standards: If a specific segment consistently underperforms, it may be worth tightening the underwriting criteria for that group.
- Enhance Monitoring and Collections: Proactively manage accounts showing signs of risk through closer monitoring and early intervention in collections.
Monitoring Simultaneous Campaigns
What if multiple campaigns are being run simultaneously? Even in such a scenario, vintage analysis proves to be a versatile tool to monitor the performance of each campaign over time. By classifying accounts according to MOB (Months on Books) and associating them with particular campaigns, the efficiency and success of each can be tracked in a coherent manner.
For instance, in the example provided, Campaign A has demonstrated a higher tendency to reach 90 DPD. It began with a delinquency rate of 0.59% within the initial three months and escalated to a peak of 2.44% after a full year, the highest among all four campaigns. Such precise analysis equips you with the knowledge needed to make critical decisions. Whether it involves continuing the campaign, making necessary modifications, or even discontinuing it, this analytical approach ensures that your credit risk management remains adaptive, informed, and effective.
Conclusion: A Valuable Tool in Credit and Collections
Vintage analysis is more than a simple evaluation technique. It’s a multifaceted tool that offers an in-depth understanding of credit behavior across diverse portfolio segments. By categorizing accounts based on their opening dates and meticulously observing their performance over time, you gain insights that are vital for risk management, tactical policy enhancements, and strategic planning.
Moreover, when applied to campaigns exhibiting higher delinquencies, vintage analysis can arm your collections team with the crucial information needed to prepare and execute better, more aggressive strategies. This proactive approach enables timely intervention, reducing potential losses and ensuring that problematic areas are addressed efficiently.
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