Insurance Fraud Detection and Prevention

AFDP is a comprehensive modular solution developed by Adastra for fraud detection and investigation support. Its universality, scalability and network analysis capabilities make AFDP highly effective in a variety of fields. AFDP continues to expose hundreds of fraud cases per year, and prevents countless others. The current third generation solution includes increased flexibility, faster automation, optimized intuitive software for fraud case management, as well as a new, highly effective Network Analysis module.

Value Proposition for Insurance

Experts estimate that one in ten claims involves some level of fraud; spread across the value generated by Canadian insurance fraud costs the industry more than $1 billion per year. Not surprisingly, fraud has become a central focus of insurance companies and watchdog organizations. Because of a general public perception of fraud as a victimless low priority offence, as well as a proliferation of cases and escalating investigation and prosecution costs, companies often opt to pay out. The accumulated losses associated with many “minor” fraudulent claims are nevertheless significant, and any solution able to lower the prevalence of fraud even by a small amount can produce significant savings.
AFDP helps produce savings by regularly monitoring, detecting, and evaluating non-standard insurance events on the basis of client analysis, the subject of insurance, and its agents and liquidators. AFDP brings a greater degree of control and surveillance, limits risk, and increases the effectiveness of investigations, and the success of prosecutions.

The Solution

AFDP includes comprehensive data quality service; data integration into analytical data marts and graph databases; business rule configuration and management; network pattern detection; and processing and storing of data, to provide accurate data support to both automated processes and frontline staff.

Insurance fraud detection and prevention solution by Adastra Bulgaria.

Indicators, Scores, Weights

To detect fraudulent behaviour, AFDP customizes existing indicators, scoring them according to the degree of risk represented.

Network Analysis And Pattern Detection

The network analysis module offers a highly-intuitive interface to examine directly the relationships between all parties related to a suspicious case. Graph patterns can be configured and evaluated in the same way as traditional fraud indicators.


Scored indicators are filtered, and cases identified as suspicious are loaded into a report for further evaluation. Changes to filter settings are performed by creating a new version of the filter; the original versions are available at any time for tracking and evaluation.


The report on suspicious cases displays the details of each case and includes a list of point scores. With reports, it is always possible to inspect the filter setting along with the relevant indicators, date of creation and its author.


AFDP documents the entire workflow process to enable monitoring and audits of responses and their effectiveness.


Due to the sensitivity of fraud-related information, security is resolved on the level of database access and AFDP configuration access.



Organizations can automate fraud-related processes while effectively maintaining full control over them.

Competitive Advantage

A unique system that detects and prevents fraud, and ultimately saves companies money, is a decisive factor in gaining an advantage over the competition.


Fraud analysts can collaborate during the investigation process while full audit trail for their decisions is maintained.

Easy Integration

By offering highly flexible REST APIs, AFDP provides easy integration with other business processes. For example, in insurance, AFDP scores can be easily plugged in FNOL systems to enable fast-tracking of claims.

Meet Regulatory Expectation

AFDP helps organizations meet and exceed the requirements of regulators, especially for internal controls and monitoring systems.

Cost Effectiveness

The modular structure of the solution makes it more easily integrated with existing Data Warehouse infrastructures. Costs can be reduced further by leveraging prior technological and business investments.

Let’s talk Fraud Detection and Prevention