Identity Matching and Behavior Profiling

Discovering the true identity of your customer is the first step to protecting your business and growing your bottom line. Many times, a consumer appears to be a new prospect, but is actually a returning customer. By accurately identifying the customer, you reveal all past information from previous encounters with that person.

Knowing the customer’s true identity also permits the integration of third party data for more insightful analysis.  Information in the public domain, such as census data, can be very helpful. We can enrich our picture of the consumer if we know even small details about him, such as his general home location, etc.  Once we know for sure who the customer is, then we can integrate very precise data, such as credit bureau information and third party data.


Enterprise-Class Life and Health Claims Monitoring



Trustworthy Data Depends on Enterprise Data Quality


Case Study

Best Practices for Deriving Value from Data


Predicting Customer Behavior

Everything we learn increases our chances of proper understanding and prediction. In many casual relationships there is no requirement for the customer to identify himself, but anytime you extend credit, you have an obligation to ascertain the customer’s identity.  Even when the customer is obligated to tell us very little, we can use Identity Analytics and Behavior Profiling to build a probabilistic assessment of who the customer is, or might be.


Eliminate Fraud from the Point of Activation

Guard against identity thieves, repeat offenders and high risk customers, starting at the point of activation. With sophisticated analytics engines that use matching and scoring algorithms, Infogix’s aliasing and customer risk scoring engines validate all relevant applicant information against a database of known offenders.


Behavior Profiling Enables Early Detection

The early customer onboarding period is the time when your vulnerability is highest. With intelligent threshold adjustments and fingerprinting behavior analysis, tightly monitor purchases, transactions, usage, changes to contact information, and validity of top-up attempts. This enables fraud management to stop abuse at the first indication of suspicious behavior from newly acquired. This also allows customer service teams to have insight into future behaviors of new and existing customers in order to respond most effectively.


Customer Risk Scoring: You’re in Control

Once a customer is on board, it is important to monitor their behavior throughout the customer lifecycle . Customer Risk Scoring assigns a risk score to every new customer and dynamically updates the scores of current customers. Each individual is assigned categories based on their risk scores, and these become available for product or service approval, as well as for tighter threshold adjustments in rule building and profiling. Static scoring criteria are based on parameters such as demographics, aliasing results and credit scores. Dynamic scoring is based on credit and claims information (if available), and is continuously updated and computed based on parameters such as payment history, past due balances, previous product purchases, policy and claims history. Customers are assigned categories based on their risk scores, and these become available for tighter threshold adjustments in rule building, profiling and workflow actions.

For more information on how our customers use this capability, visit some case studies and blogs.

–       Critical Point-of-Sale Solution Saves $78M

–       Fraud Detection Management System (FDMS) Increases Fraud Detection by 20%

–       Fraud Analytics – Stop Fraud at the Point of Sale

–       Use Fraud Analytics to Hang Up the Phone on Roaming Fraud