In today’s information age, why so much stale data?
When was the last time you used a stand-alone GPS navigator in your car? Google Maps made the single-use devices obsolete, not only because they became redundant. The data was stale. To not become victim to its own model, Google continually deploys vehicles to map streets already covered, always updating its data. And that’s just for driving. When you can see the road and make informed decisions yourself. What about business transactions? Millions of them. With thousands of customers, vendors, and contractors. Happening every minute.
Due diligence cannot be so reliant on stale data with latency periods of days or weeks. The Veritas Data Genomics Index looks at all corporate data, admittedly more static than traditional global sanctions databases, but the caution is still valid. The nature of a database requires maintenance. Data must be updated. Data must be purged. “Up to date” can mean many things.
On the first day of the ACAMS moneylaundering.com conference here in Florida, every conversation I’ve had included an attendee’s frustration with using stale data. The solution is pulling data directly from sources without the need for manual intervention, updating, and maintenance. Current data changes the conversation. False positives? Not with current data. Dispute obligations? Not with current data. Verification challenges? Not with current data.
The proliferation of public records sources make the acquisition of current data more possible every day. The biggest challenge is not availability of data, it is the structure of that data. Many government blacklists are published in running narratives, not structured data tables. Full text searches become necessary, along with carefully crafted algorithms for data analysis.
Still, better to put our shoulder to the wheel of intelligent data mining than to continue to spend so much time updating an already outdated concept.
To read the full article on all types of data stored in business and ideas for manaing it, visit: datagenomicsproject.org