After a long week at work, I sat down with a glass of wine to start thinking about what I wanted to cook for dinner. I looked for recipes online but found I was short a few ingredients. But, I was determined (and hungry!)so I marched into the kitchen to start prepping with whatever I had. 




While cooking, I realized that Identity Verification is very similar to taking custom ingredients and cooking up a beautiful dish, where the customer input data and our data sources are our ingredients. Although the importance is stressed upon data partners having the right kind of data, we usually tend to forget that there are so many small nuances around customer input data as wellCustomer input data can vary dramatically by industry, customer segment (B2B vs. B2C), age demographics, and much more. Understanding the core details about a customer’s input data helps to identify the correct data sources needed and creates optimized configurations for match rules.  


International Identity Verification 

Identity verification on the international scale has an additional layer of complexity. Each country does not necessarily have a singlecohesive database of all the individuals and immigrants in the country. So, data sources are mainly comprised of government, telecom, utility, credit header, and commercial data. Some of the immigrant population may not show up on the government or credit header data, but rest assured they most likely have a mobile phone, household utilities, or the postal address. 


Identity Verification with Restrictions 

There are often many verification restrictions that come with someone’s age, citizenship status, or lifestyle. For example, customer serving in the cryptocurrency field may be looking to verify people in the 18-30-year old demographic. In some countries, people may not even have a credit footprint until they turn 25.  

Someone in a large metro area may not need a drivers license. An individual living with someone else may not have  their own utility bills. A person living in a rural area may not have a telephone that is reported in a telecom data source.  

So, when a customer runs someone through an identity verification platform, it is more likely to return a low match rate not because most of them are fraudulent, but because the dataset did not have what the customer was looking for. In such a situation, it would be best not to put all your eggs in one basket. Use different sources such as telecom or a government source in conjunction with credit data to verify people. In other words, use a pinch of other seasonings! 


In this case, Global Data Consortium acts as the chef in the kitchen. We comb the various different ingredients from various customerschoose the best data sources, and creatcustom rule configurations to return the best possible match ratesOur Sales and Product teams work with your business diligently on a Proof of Concept that will help you decide what’s best for your business, along with our feedback and recommendations. At GDC, we’ve mastered the art of collecting all the ingredients from across the globe to make sure that the dish you get is phenomenal.