QlikView Fraud Analytics helps the world’s largest insurance and financial organizations detect fraud through improved analytics. Strengthening Qlik fraud detection through analytics is a major initiative for the new administration one that’s heavily powered by discovery of the unexpected.
While many analytical tools exist to generate predictive models and visualizations, most fall short in enabling non-technical business users to navigate their data.
Many organizations are making significant investments in data science and in advanced analytics. These investments support a number of use cases such as the sales forecasting, fraud detection, inventory optimization, market basket analysis, pricing optimization, and many more.
With QlikView Fraud Analytics, organizations can quickly search and interrogate data from all systems – allowing everyone in the agency to navigate their data and create interactive visualizations and sophisticated analysis.
Rapidly spot trends, patterns, and outliers to detect potential signs or the suspects of fraud. Investigate suspicious activities and transactions, missing and duplicate information, watch lists, and case management. Additional uses include transaction pattern analysis and insider threat detection. Users explore, analyze, and modify their analysis with simple mouse clicks to discover the findings by following their natural process of interrogation.
Qlik Fraud Detection
QlikView associative data model unveils new methods of uncovering the fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time.
A key weapon for the insurers in identifying these fraud perpetrators is the analysis of data. Insurers must be able to search for the associations in data between similar types of claims, in similar locations, including something unique like a mobile phone number.
These associations between the data can lead to a significant increase in identifying groups of people that commit these types of fraud. This is exactly where Qlik fraud detection can play an important role in this activity.
QIX Associative engine, present at the heart of Qlik Sense, is designed to make the discovery of these associations easy and intuitive. Together with the ability to quickly create drag and drop the visualizations, Qlik Sense can help Insurance Fraud Analysts identify trends, patterns and examples of fraudulent Whiplash claims.
The next step for insurers would be to combine the power of Qlik Sense with their Qlik fraud detection models. The result would be a Qlik Sense visualization embedded into the claims system that showed the claims handler real-time results of the fraud model at the time of the Notification of Loss. This Qlik fraud detection would allow the insurer to push suspicious claims to a dedicated fraud management team for further investigation.
Example : First-Party Bank Fraud
First-party fraud involves the fraudsters who apply for credit cards, loans, overdrafts and unsecured banking credit lines, with no intention of paying them back. It is a serious problem for banking institutions. Banks are usually increasing provisioning for loan defaulters , which leads to increase high interest rates to secure their investment.
The surprising magnitude of these losses is because of two factors. The first is that the first-party fraud is very difficult to detect. Tricksters act very closely to the legitimate customers, until the moment they bust out, cleaning out all their accounts and promptly disappearing.
A second factor is the nature of the relation between the number of participants in the fraud ring and the overall dollar value controlled by the operation. This connected explosion is a feature often exploited by the organized crime.
With QlikView Fraud Analytics we can have a comprehensive descriptive in depth analysis of different relationships between different entities in master records. Qlik is being used today by the global organizations to rapidly spot trends, patterns, and outliers through intuitive and interactive visualizations. This ultimately helps them detect the potential signs or suspects of fraud.
Qlik aids the investigation into suspicious activities and transactions, watch lists, and case management. Additional uses include transaction pattern analysis and insider threat detection. Users explore, analyze, and modify their analysis with simple mouse clicks to discover the findings by following their natural process of interrogation:
- Qlik’s patented associative engine automatically identifies relationships and disassociation’s within the data through built-in logic – no data modeling required
- Our platform leverages in-memory storage and compresses data by 90% to pull together large volumes of multiple disparate sources, resulting in rapid query and navigation performance
- Users have google-like search capabilities to locate data
- Users can easily drill into transaction-level detail to identify areas for additional investigation
- Qlik deploys content to any mobile device without the need for additional design/development
- Qlik provides the ability to build both simple or complex, interactive reports. Many organizations have replaced their static “traditional BI” reports with one Qlik app
- Data governance offers the organizations superior balance for Business and IT giving users unprecedented data access and flexibility, while maintaining data integrity and security unlike ANY other self-service BI software on the market today.
QlikView Fraud Analytics enables you to create detection strategies that leverage the power of Qlik to sift through ultra-high volumes of data for clues of fraud with rules and predictive algorithms. We at Locus IT provide QlikView Fraud Analytics training and support services. For more information please contact us.