Insight 2: Income Consistency
Pngme provides actionable insights through its mobile SDK and unified API. Such insights are driving growth and powering robust credit capabilities with the top financial institutions in Nigerian & Kenya. This week, we’re taking a look at Insight 2: Income Consistency to give an idea of how our Insights are built and how they can work for you. Check out the below snapshot of Insight 2: Income Consistency and learn about more Pngme insights through our handbook.
A desired financial health characteristic is for the user to have a steady flow of income. Underwriters must be wary of income volatility. In this analysis, we compare income from the last 30 days with that of the last 60 days with this ratio feature, income_30_60. More specifically, income_30_60 is defined as the estimated income from last month divided by estimated income from the last 2 months.
Perfect consistency between the two time periods is for the ratio to be 0.5. As we start in the middle and extend out to the tails of the chart, we observe more credit risk as users exhibit more income volatility month-to-month.
The above demonstrates that income volatility relates to overall credit risk. Based on an institution’s risk tolerance and financial products being offered, they may choose to approve/reject users based on this increased credit risk.
Types of Volatility:
There are two types of income volatility in the above findings: users who make most of their income in the last 30 days and users who made most of their income in the 30 days prior to that period (30-60 days ago).
Risk profile 1: 18% of users made the majority of their 60-day income in the previous 30 days, not in the last 30. These users have suffered some type of life event which has caused a sudden decrease in cash flow.
Risk Profile 2: 50% of users made the majority of their 60-day income in the last 30 days as opposed to the previous 60. These users may either: 1) have a shorter financial history or 2) have experienced a sudden windfall, which is not indicative of future income.
WANT TO LEARN MORE ABOUT PNGME’S DATA SCIENCE SERVICES: REQUEST A CONSULTATION