“Data that is not looked at is not quality data.”
Alan Matsumura Director, PayNet, Inc.
Small business lenders need accurate information to make informed decisions, particularly when large financing decisions depend on external information such as credit reports. Accurate information results from quality data. Data quality is a characteristic of data that impacts its ability to meet the needs of the user. But what is data quality? There are many ways to evaluate data quality. Here are six significant characteristics of data that impact the level of quality.
- Accuracy describes the degree of correctness based on business rules. This is the most typical way to consider data quality.
- Consistency pertains to the integrity of definition and data capture method across time, business, areas, etc.
- Timeliness requires that data is available when needed. Not having current information can lead to an incorrect credit decision.
- Completeness indicates that data gaps are avoided. The completeness of data is a significant factor if you are using the data to model or benchmark across historical periods. Data gaps may be observable or unknown if you are not aware of current obligations a borrower may have with other lenders.
- Availability suggests that data can be accessed and used by appropriate individuals yet protected by security procedures to prevent unauthorized access and use.
- Believability implies that results make sense because results that are hard to explain will not be followed.
PayNet recognizes the critical nature of data quality so we conduct extensive processing of the bits and bytes. Our patented business methods are used to gather, process and provide services. PayNet is in the unique position of receiving, processing, evaluating and making sense of lease, loan and line of credit data from hundreds of lenders. We go through a rigorous data integration process with our members (coupled with ongoing verification procedures) to ensure the data behaves as expected and ties to our members’ systems. We look at the submitted data every business day of the year to meet our own rigorous measures of data quality.