How Income Verification Works

Let's walk through a short scenario exercise to get your creative juices to flow:

You've always wanted to build a fintech product where users can signup and have access to loans. You've achieved your goal, and your app is now operational.

In your quest to make the app scale, you run into a problem, that is - you're unable to determine the income status of an individual before calculating the appropriate loan amount. One solution is to ask your users to upload their bank statements into your app, so you can download the bank statement from your backend and verify their income. However, as your app gains traction you realize that this process cannot scale. To tackle the daily influx of bank statements, you've two options;

1. Get more manpower, which will increase operational costs from your end.
2. Search for a solution that automates Income Verification.

What option will you go for? is the question.

Isn't the answer rather obvious? This guide is all about how you could utilize Okra Income Verification API when it comes to building an Income-based Fintech product.

Introducing Okra Income

Almost every loan application requires the ability to verify employment status, income, and ability to pay, but the process can be burdensome for hopeful candidates. They frequently need to retrieve and share several documents, which must be processed and reviewed by a lender.

The Okra Income product uses advanced pattern matching and machine learning algorithms to identify income streams, their sources, and length, as well as anticipate the number of recurrences. It provides information on the previous year's income figures and uses the streams to forecast the projected future income amount. Isn't this awesome?

The Okra Income product can help people;

• Get customized financial advice
• Get a loan

Lenders can quickly and securely obtain a consumer's income data directly from the source using Okra Income solutions. As a result, companies can make better-informed risk choices and devote fewer resources to manually evaluating papers.

The following is an example of an income stream response object:

"income": {
        "confidence": "98.9%",
        "last_two_years_income": 224616.0,
        "last_two_years_to_this_year_projected_income": 21728473.17,
        "last_year_income": 11726584.8,
        "last_year_to_this_year_projected_income": 32480401.75,
        "max_number_of_overlapping_income_streams": 2,
        "number_of_income_streams": 2,
        "projected_yearly_income": 53234218.7,
        "streams": [
            {
                "account": "xxxxx-xxxxx-xxxxx-xxxxxx",
                "avg_monthly_income": 194693.75,
                "bank": "xxxx-xxxxx-xxxxxx-xxxxxx",
                "days": 89,
                "income_last_date": "Wed, 05 May 2021 00:00:00 GMT",
                "income_start_date": "Fri, 01 Jan 2021 00:00:00 GMT",
                "monthly_income": 194693.75,
                "number_of_months": 4,
                "projected_months": 10.0,
                "employer": "CrossWallet, Inc",
                "type": "salary"
            },
            {
                "account": "xxxx-xxxx-xxxxx-xxxxx-xxxxx",
                "avg_monthly_income": 4273940.1,
                "bank": "xxxx-xxxxx-xxxx-xxx-xxxxx",
                "days": 104,
                "monthly_income": 4273940.1,
                "number_of_months": 5,
                "projected_months": 12.0,
                "type": "unstructured"
            }
        ]
    }

Response Object Explanation:

The confidence score is a measure of how accurate the income values are

• last_two_years_income = income for year y-2, where y = current year
• last_year_income = income for year y-1, where y = current year
• projected_yearly_income = projected income for year y
• last_two_years_to_this_year_projected_income = approximate income estimate using income from year y-2, y-1, and y
• last_year_to_this_year_projected_income = approximate income estimate using income from year y-1, and y

Each income stream contains

• days - the number of working days in the estimated income period
• number_of_months - the number of months the stream repeated
• projected_months - the number of months we project the income will continue to repeat
• income_start_date - the first date the stream of income was noticed
• income_last_date - the last date the stream occurred, and the income type which could be 'salary', 'recurring credit', or 'unstructured'

From the income response, the user makes an average of

N194,693.75 + N4,273,940.1 = N4,468,633.85 per month.

Okra Income: Built with robust coverage for consumers

Okra's all-encompassing solution covers a wide spectrum of candidates, including freelancers, full-time and part-time employees. Offering a quick and easy onboarding experience is critical in today's shifting financial services market for attracting new clients and generating revenue.

Conclusion

We understand that not everyone earns money through a paycheck. Many individuals are self-employed, freelancing, hence why we believe income data is very important. Income data has enormous promise for expanding financial possibilities and assisting people in living more financially healthy lifestyles.

A good place to check other cool stuff is our docs, and if you are passionate about open finance, you definitely should visit our website to see other services that might be appealing to you.

Contact sales or send an email to sales@okra.ng to get started!