FICO Distribution - HART 2022-A
HART 2022-A has 67.4% of its pool with Super-prime FICO scores.
2025-08-21
📊 Chart Summary
HART 2022-A has 67.4% of its pool comprised of loans with Super-prime FICO scores, totaling $150,787,540 in unpaid principle balance according to Edgar sec.gov filings. The reporting period for this information begins 2025-07-01 and ends 2025-07-31.
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Summarize FICO Score Distribution
Summarize the fico distribution for HART 2022-A. Break down the number of loans, UPB, and percentage of the pool for each FICO category (e.g., Super-prime, Prime, Subprime). Highlight the dominant FICO segment and what this indicates about the credit quality of the pool.
Highlight Credit Quality Concentration
Analyze the fico distribution for HART 2022-A to identify any concentration in specific FICO categories. Discuss the implications of having a high percentage of the pool in Super-prime or Prime categories versus Subprime or Deep-subprime.
Compare to Historical FICO Trends
Compare the fico distribution for HART 2022-A to historical FICO score distributions for ABS auto deals issued since 2017. Highlight any deviations, such as a larger-than-average allocation to Subprime, and discuss what this indicates about underwriting or market conditions.
Visualize Credit Tier Distribution (Bar Chart)
Create a bar chart visualization based on the fico distribution for HART 2022-A, showing the UPB for each FICO category. Highlight the largest FICO category with a distinct color and annotate the chart with its percentage of the pool.
Risk Assessment for Subprime Allocations
Using the fico distribution for HART 2022-A, assess the risk associated with loans in Subprime and Deep-subprime categories. Discuss how these allocations could impact delinquency and default rates in various economic scenarios.
Impact of Missing FICO Data
Evaluate the potential risks associated with the "Not provided" FICO category in the fico distribution for HART 2022-A. Discuss whether missing FICO data might obscure risks or indicate specific underwriting practices.
Compare Credit Quality Across Peer Deals
Benchmark the fico distribution for HART 2022-A against other ABS auto loan or lease deals issued in the same year. Discuss how the FICO distribution aligns with or deviates from peer deals and what this suggests about borrower quality.
Visualize Hypothetical Performance Scenarios
Using the fico distribution for HART 2022-A, simulate a hypothetical economic downturn where default rates for Subprime and Deep-subprime loans increase by 10%. Visualize the impact on overall pool performance and discuss potential investor concerns.
Assess Diversification Across FICO Categories
Evaluate the diversification of HART 2022-A's fico distribution by analyzing the spread of loans across FICO categories. Discuss whether this diversification helps mitigate risks or if over-concentration in specific categories poses challenges.
Find Additional Credit Data
Identify sources where you can access more data on the FICO distribution for HART 2022-A. Include platforms like trustee reports, rating agency updates, or issuer disclosures for detailed insights into the credit quality of the pool.
Compare Prime and Non-Prime Allocations
Analyze the split between Prime (e.g., Super-prime, Prime) and Non-prime (e.g., Subprime, Deep-subprime) allocations in HART 2022-A's fico distribution. Discuss how this mix influences the pool's overall risk profile and investor appeal.
Create a Weighted Average FICO Metric
Calculate the weighted average FICO score for HART 2022-A using the fico distribution. Include the calculation methodology and discuss how this metric can help investors assess the credit quality of the pool.
Analyze Trends in Credit Tier Shifts
Compare the fico distribution for HART 2022-A to FICO score distributions from prior deals by the same issuer. Highlight any trends, such as shifts toward higher or lower credit tiers, and discuss their potential implications for underwriting strategy.
Assess Sensitivity to Macroeconomic Conditions
Discuss how HART 2022-A's fico distribution might perform under macroeconomic conditions such as rising unemployment or declining used car values. Focus on how loans in Subprime and Deep-subprime categories might be affected.
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