An identity score is a method for detecting identity theft. It basically identifies whether a person is really the person who he/she claims to be.
Identity scores include a comprehensive set of user’s data which measures the legitimacy of an individual. The data can include individual’s personal information, public records, government records, credit records, internet data and corporate data. As identity scores include so much information and can also predict behavioral patterns, hence identity scoring is a great identity theft prevention measure.
Businesseswidely use identity scores nowadays to prevent identity fraud and as a tool to verify public records. Businesses are using identity scores to limit their exposure to loss. Therefore, identity scoring greatly influences third-party authentication systems and fraud verification tools to verify identities and suspicious activities.
An identity score of an individual can consist of almost all types of public information.
What are the components of identity score?
Identity score of an individual consists of various components. These components are used in combination to generate the identity score of a particular individual. This means that the results may vary from one individual to another individual.
The main components of an identity score includes:
Name components This contains personal identifying information of a person such as his/her name, phone number, etc.
Behavioral use pattern components These include the patterns analyzed from above information.
Internet components It comprises of personal identifying information available on the internet (such as social networking websites, blogs, etc.).
Hacker and fraud components This includes personal identifying information stolen in data breaches and used for fraudulent purposes.
Synthetic identity components These are those components which are used to create a synthetic (false) identity which may lead to synthetic identity theft.
How identity scoring works?
The working of identity scoring includes matching the information provided by the user with the unlimited number of records available in public databases and then calculating it against analyzed patterns to recognize fraud or identity theft.
Let us explain this with an example. Identity thieves stole Martha’s Social Security Number (SSSN). These thieves also stole a laptop and hacked it. The thieves combined Martha’s SSN with a name found on the laptop. Consequently, they used it to open several new accounts and obtain credit cards. Now, an identity protection system using identity scoring would alert Martha that her SSN has been fraudulently used.
How are identity scores calculated?
At times, predictive analytics is used to calculate identity scores. Predictive analytics is the science of gathering behavioral data. It also involves comparing the data with historical patterns. As a result, it recognizes potentially risky or fraudulent activity.
Identity scores are very much mutable i.e., they tend to fluctuate now and then. This is because the source information i.e., public records and personal identifying information are constantly fluctuating. Whenever a person switches a job; buys, sells, rents a property; or faces an encounter with the law enforcement, consequently, his/ her public records are altered. Managing the information across so many different platforms makes it very difficult to fix faults in one’s information.
First of all, identity scoring systems accumulate publicly available information. Then, they use predictive analytics to estimate the patterns of how the information is used. Finally, they measure the authenticity of a particular identity.
What are the uses of identity scores?
The uses of identity scores are:
Identity scores offer an accurate proof of an identity’s legitimacy as it uses so much data for comparison.
Businesses use identity scores for identity verification and measuring fraud risks.
Individuals use them for preventing malicious use of identities and synthetic identity theft.
Identity scores also enable grading of behavioral patterns through predictive analytics. Through this, an identity monitoring service can trace an individual’s or a criminal group’s activity across several places, instead of tracking a single area.
They precisely evaluate the possibility that an application will result in fraud.
Identity scoring verifies identities in circumstances of employment hiring and information verification.
The following companies use identity scores in their protection systems:
Experian Experian provides risk management and identity verification services by using identity scores in its Fraud Shield product. Its additional score product combines information from both credit and fraud-related sources.
e-Merges.com The fraud prevention product of e-Merges.com named “Electorate” uses identity scoring to validate public records.
Fair Isaac The scoring solution of Fair Isaac called Falcon ID uses predictive analytics in its fraud verification process and enables information sharing across businesses.
ID Analytics Chief organizations trust ID Analytics’ product MyIDScore.com to identify and prevent identity fraud. It is a free service that makes consumers aware of any risks of identity fraud.
MyPublicInfo MyPublicInfo uses identity scoring as a base for its several products.