Identity theft has become commonplace in the digital world. Fraudsters have developed complex schemes that leverage high-quality personally identifiable information (PII) to file fraudulent unemployment insurance claims. The ID Theft FraudXTM solution is part of our proven suite of expert data analysis, management, and fraud prevention tools. Leveraging Machine Learning technology and data science, ID Theft FraudXTM is specifically designed to use data collected by Unemployment Insurance (UI) Agencies to help identify claims that are highly indicative of identity theft behavior – including larger-scale fraud schemes. ID Theft FraudXTM is designed to be agile so that it can quickly adapt to ever-evolving fraud schemes.   

• OPTimum Identity Theft leverages 11 key categories of data to score each report.
• Investigators can also flag claims for investigation and record the investigation results. This provides a feedback loop to the analytics engine to further refine the scoring algorithm.
• Additionally, as shown in this screenshot, scoring trends are graphically represented on screen that allow investigators to track scoring changes and pattern shifts that are indicative of fraud schemes like claim hijacking.

  Initial and continued claims. Data gathered during the claims process is used by the FraudX algorithm to discern patterns indicative of organized fraud. Attributes typically used include mailing address, IP address, and bank account number.

  Adjudication/Investigations. Agents can use the claimant’s score on the ID Theft report as an indicator of the likelihood that the identity is stolen. Agents can also drill into the data to look for patterns and expand leads.

  Efficient use of staff is maximized as cases most likely to be fraud will consistently have the highest risk scores.

  For collections, it lowers the amount of outstanding balances.
      For Adjudication it can be used to resolve cases where ERs respond to wage and separation, also a reduced workload
     Within the application, investigators can maintain grey lists for suspicious email domains, and ISPs that are commonly indicative of suspicious activity
     They can also add IP Addresses that the system should ignore in order to prevent false positives like library IPs and the agency IP. Once added, the application immediately take those datasets into account when calculating the next score. 
     Lastly, investigators can adjust the scoring to better align with patterns of fraud that they see in their state.  This gives investigators the flexibility to target specific attributes and boost the weight within the overall scoring.

The attributes used by the algorithm, as well as the relative weights given to individual attributes, can be adjusted based on individual state characteristics as well as the accuracy of results returned as the report is run.

  Ease of Use – staff are given ranked leads and a multitude of data points that allow them to clear most of the investigation within the FraudX

The attributes used by the algorithm, as well as the relative weights given to individual attributes, can be adjusted based on individual state characteristics as well as the accuracy of results returned as the report is run.

  With Case management, most of the investigatory work can be done within the fraudX. The product provides investigators with the ability to drill into the data to look for patterns and expand leads

The attributes used by the algorithm, as well as the relative weights given to individual attributes, can be adjusted based on individual state characteristics as well as the accuracy of results returned as the report is run.

State A began to encounter that 70% of their initial claims over a period of a few weeks were hitting fraud score thresholds. 

• Both the IDH broker and audits available within our ID Theft product are detecting the fraud claims and enabling the claims to be blocked.

State B using an audit available in our ID Theft solution discovered a pattern of debit cards, bank type, and address gave indication of fraud

• The ID Theft audit over a 2 month timeframe detected fraud and enabled the state to stop paying $22,049,595 in weekly claims. This would have resulted om over $1.1B in fraud if the claims were allowed to exhaust their benefits.