Income Misrepresentation Index

Point Predictive’s Income Misrepresentation Index tracks the patterns of income and employment suspected of misrepresentation across 130 million application submissions.
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Last Updated 02/06/24

Introduction

Point Predictive’s Income Misrepresentation Index tracks the patterns of income and employment suspected of misrepresentation across 130 million application submissions. The index analyzes the level of suspicious reported information on applications to understand whether income and employment misrepresentation is rising or falling. The Income and Employment Misrepresentation index shows that income misrepresentation risk grew significantly to 180% from 2017 to 2021, before falling again in 2022 to approximately 150%. Solving income and employment fraud remains among lenders’ top priorities in 2024.

How was the Income Misrepresentation Index developed, and what criteria were considered in its creation?

The Income misrepresentation index was developed using historical data from 2017 through 2024. The data included over 26 billion data points aggregated across 75 million consumers and 165 million applications for auto loans. The index uses that underlying application and consumer data to determine how often borrowers and dealers are misrepresenting the income or the employment of the consumer on the loan application. It tracks the average number of fraud alerts pertaining to income and employment misrepresentation across all applications for the measured time period. The types of income and employment alerts that are tracked include some of the following:
  • Has the borrower’s reported income dramatically increased in a short period of time?
  • Has the borrower’s reported income fluctuated wildly across many applications?
  • Has the borrower’s income been associated with a known fraudulent employer?
  • Has the borrower used multiple different employers in a short period of time?
  • Does the borrower’s stated income match the expected income for the occupation or history of the employer.
The average firing rate of alerts is aggregated across applications for a given time period to determine if income and employment misrepresentation is rising or falling.

Can you elaborate on the data sources and analysis methods used to compile the index?

The index was created using Point Predictive’s proprietary data which includes applications from 2017 through 2024. The data consists of auto loan applications. We collect approximately 85 fields of information on every application including demographics, loan information, vehicle information, sales information, dealership information and loan performance data.

How frequently is the index updated?

The index is updated quarterly.

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