What is Coverage?
In the context of consumer permissioned data, coverage is the percentage of the US population that can leverage a platform to permission their data. Sounds simple, but there are layers to coverage.
- Private Sector Workforce: 129 million
- Government Employees: 22 million
- Self Employed: 9 million
- Unemployed Benefits: 8.5 million
At the highest level coverage is the percentage of the population that’s able to permission their data, but in order to achieve a high level of overall coverage, providers need to provide high levels of coverage for each data source. For example if a lender is trying to verify the income and employment of loan applicants, they need high coverage for:
- Payroll Providers
- Government issued benefits
- Tax documentation
High levels of coverage for each data source maximizes the total coverage of the population. The higher the coverage, the more applicants that are able to permission their data for verification.
Coverage can be increased several ways. A provider can add more employers to their database. A provider can support more payroll providers. A provider can leverage a new datasource to unlock a previously unreached population segment (tax data helps verify the self-employed who don’t receive traditional paystubs).
How to Calculate Coverage
Coverage can quickly be calculated by doing reverse math and backing into an overall percentage.
- Start with the number of employer integrations
- Then find the number of employees that work for each employer
- Add the number of employees together to come up with a total number of employees covered
- Compare this number with the working population
There are of course nuances depending on the data source you’re evaluating. I.e tax and the self employed segment of the market.
Coverage via API Integrations connection VS Screen Scrapers
Not only is it important to cover large portions of the population, it’s important how you create that coverage. Tools that leverage API Integrations connections are able to provide higher quality data than tools that leverage screen scraping. API Integrations is an open standard for access delegation, commonly used as a way for internet users to grant websites or in Truv’s case create a direct connection to the network layer of payroll providers. This allows the data to be transferred securely and instantly. It’s common to see tools not providing API connections because it’s difficult.
What is Conversion?
If coverage is “How many people CAN use it” then conversion is “How many people DO use it.” In order to use consumer permissioned data, providers must introduce points of required user input. This input could be selecting a payroll provider and asking for login credentials, or it could be asking someone to search for their income source then log into their benefits portal. These required input moments create friction. Friction leads to users not completing a required action, and in this case never permissioning their data. Conversion measures how many people complete permissioning their data vs the people who quit before finishing.
Increasing conversion is tricky business and forces providers to reduce friction during the input process. For example, how many workers know their payroll login credentials off the top of their head? Very few. If you prompt an Amazon employee to sign into their payroll system you have created a high friction process. But if a provider already knows which payroll system Amazon uses and asks the user to login via their Amazon credentials, it creates a low friction process and increases conversion.
How to Calculate Conversion
Similar to coverage, conversion is fairly simple to calculate.
- Determine the number of users that are asked to permission their data and are covered
- Determine the different steps users are asked to take
- Measure the number of users who complete each step
- Compare the final number to the starting number
It is also extremely useful to measure conversion rates at different points in the permissioning process, not just the final number. This will help identify any bottlenecks in the process.
How They’re Related and Why are They’re Important
The combination of coverage and conversion produce the total number of users that permission their data. Coverage is the total number of people that can use a tool and conversion is the number of people covered who choose to complete the full process. For a verification of income and employment the equation would look like this:
Total number of applicants x Coverage Rate x Integrations Quality = Converted Applicants that verified income and employment
Coverage and conversion directly affect the bottom line of businesses.
In the lending world, having a high coverage and conversion rate leads to a decreased cost per loan distributed. In the banking world, having a high coverage and conversion rate leads to more accounts opened.
Coverage also reduces the risk of fraud and distributing unqualified loans. By creating a digital link to the source of data, there is no opportunity for fraudulent documents being uploaded or human error.
Evaluating Coverage and Conversion
When evaluating a partnership with a consumer permissioned data platform, it’s important to figure out how their total coverage will apply to your specific target demographic. You should perform a retroactive analysis on your customers and then compare it against the coverage that’s offered.
For example, if you’re verifying income and employment you should pull data on the different employers your applicant’s worked for in the previous 6 months. You should give this list to the solution you’re evaluating, and have them determine the percentage of applicants they would have covered.
Truv covers just over 90% of the U.S. working population through a combination of different products. Unlike other tools, Truv primarily leverages API Integrations connections to retrieve data. This means the quality of the data and speed at which it is returned is much greater than the competition that primarily leverages screen scraping.
Let’s deep dive into each product and discuss the unique characteristics that make Truv the stand out solution in the market.
Verification of Income and Employment: Payroll
Truv’s payroll verification solution leads the market in coverage with over 2.3 million employers supported. This means 90% of the U.S. working population that leverages Truv will be able to find either their employer or payroll provider to permission financial data. If a user searches for an employer that is not currently in the database, Truv flags that information and puts it on the list of integrations to create. This system ensures that Truv is always creating new integrations and expanding its coverage. Truv also allows users to log in via benefits portals, further expanding its coverage to more of the population.
Benchmark Coverage Stats (actual coverage will vary depending on typical verification population):
- 66% of NASDAQ
- 97% of Fortune 1000
- 96% of Federal Government Agencies
- 64% of Healthcare
- 48% of Colleges and Universities
Truv also maximizes conversion rates by providing users with easy ways to permit their date. Truv currently maps over 195k employers directly to payroll providers (mapping more every day), meaning if someone works for one of those companies they will be asked to log in via their company credentials. This creates less friction and increases conversion rates. Truv also supports 43 unique single sign-on providers, meaning that users are asked to sign in with their SSO credentials instead of entering their payroll information. These mapping along with features like native password resets creates an optimal conversion rate.
Verification of Income and Employment: Tax
Truv allows users to verify their income and employment by logging into their tax return submission portal. Truv currently supports over 70% of the population who digitally submitted tax returns by allowing them to login via TurboTax.
Verification of Income and Employment: Financial Accounts
Truv supports 98% of banking users with its financial accounts verification product. The 98% is composed of over 14k different banks, credit unions, and financial technology companies.
Truv is also the only financial account data provider that cleanses and attributes data to create predictive models. With over 114 data categories and over 2200 attributes, Truv puts data in the correct category at a rate of 95% and then helps underwriters build a predictive model to determine the eligibility of an applicant.
Truv provides home and auto insurance verification.
For home insurance:
- Truv covers 91% of home insurance providers
- # of top 15 providers: 14
- # of additional top 25 providers: 10
- Subsidiary providers: 8
- Boutique providers 38
For auto insurance:
- Truv covers 96% of auto insurance providers
- # of top 15 providers: 14
- # of additional top 25 providers: 8
- Subsidiary providers: 11
- Boutique providers: 30
Insurance verification is traditionally a manual process that requires documentation uploads. Truv insurance verification automates this process and reduces the risk of fraud and stale data.
As the digital world continues to evolve, the importance of comprehensive coverage cannot be overstated. Companies like Truv are leading the way in providing seamless data access to consumers and businesses alike. By investing in innovative solutions and continually updating their integrations, Truv is setting a new standard for coverage and user experience in the industry.