Data—for better or for worse—is often the differentiator between success and failure. And while fresh, actionable data can provide the means to an end, in investigations, outdated and narrow data can lead to misinformed actions, wasted time, delays and significant financial losses.
Unfortunately, in the world of big data, there's a vast amount of outdated—or just plain erroneous—consumer and business data spread across a multitude of sources, both public and premium. Here are a few tips to keep in mind when evaluating data to help separate good data sources from bad.
#1. Seek authoritative sources of information.
Look for sources that use authoritative data—data acquired from things like records for property taxes, driver’s licenses, utility bills or voter registrations, where it’s highly likely consumers provided correct, personal information or substantiated their identity.
Authoritative data can be extremely useful when looking to prove or disprove a hypothesis. Law firms will often use authoritative data to verify testimony. Sources like active utility records can serve as evidence of occupancy to demonstrate the subject lived at a residence at a particular time.
The same is true on the corporate side. Data sourced from business licenses and corporate state registration records often boasts a much higher level of quality and actionability, and can be very useful in corporate due diligence investigations—perhaps shedding light on a potential acquisition target.
#2. Look for data that "tells a story".
Deed transactions, criminal records, traffic tickets, vehicle sighting records, liens of judgment, etc., all provide information about a consumer at a certain point in time. When combined with authoritative data sources, this event-driven data can tell a story, helping to paint a more complete picture of an individual.
For example, an Insurance Special Investigative Unit (SIU) can use vehicle sighting records during a fraud investigation to help prove insurance rate evasion or fraud. These records can show patterns of behavior between a residence and a place of employment or another place of interest. This information can be used to help prove a vehicle had damage prior to a reported incident, or that while a car’s owner resides in one state, the vehicle is registered in another state that has less costly insurance rates. Vehicle sighting records can also be useful in vehicle repossession cases to determine where the car physically is, and in legal testimony validation.
When it comes to corporate data, because licenses and corporate registrations are core documents associated with a business, they can tell a very compelling story in a corporate due diligence or fraud investigation—helping uncover unknown relationships between the subject company or employees and known criminals.
#3. Ensure the data is timely.
As data ages, its useful life tends to decline. Data seekers should place a high level of importance on the quick integration and dissemination of incoming data. When evaluating a database, be sure to find out how fresh its records really are. Look for databases that provide new data at near real time. We’re not talking just daily updates—but rather fresh data within a matter of hours. Additionally, databases that provide batch monitoring services offer continuous and automated monitoring that can help keep records clean, reducing risk and increasing efficiency. The constant, updated outputs maximize a database's ability to provide the most relevant results to users.
#4. Quality over quantity – always.
Don’t just seek data for the sake of data. A smaller amount of quality information is much more valuable to data seekers than a vast amount of less credible data. Look for authoritative data providers with algorithms designed to weed through the disparate data, and data analytics methods that identify anomalies and produce quality, relevant output.
Whether trying to solve a fraud case, determine right-party contact information, or conduct due diligence on a company or employee, fresh and actionable information is critical. For collectors, contacting the wrong party can have legal ramifications. For law enforcement, the right data can mean finding a missing child. In a corporate due diligence investigation, good data can mean more effectively preventing or detecting fraud, avoiding significant financial losses.
While the vast majority of available data is likely irrelevant to your end goal, using a carefully curated database with a well-tuned search engine is far more likely to uncover that key piece of data needed to solve the puzzle.
Use these key principles to better evaluate the quality of your data sources. The right data provides customers with the best material available, enabling more informed decisions and better business outcomes.
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