Fraud Detection Software

90% of organizations suffer from fraud. Many recognize the problem, few solve it.

It is critical to identify and prevent fraudulent activities in their early stages. This is not an easy task: scammers are constantly changing their tactics. If a company has no well-established tools to repel fraud, it is at risk of financial losses.

Our company offers effective strategies for fighting it: 

  • best fraud prevention solution implementation;
  • fraud detection software development.

Our Fraud Detection Solution

Ready to start combating fraud? Use our self-learning algorithms for case detection. 

Over the years, our experts have structured a reliable fraud detection system that generates hundreds of thousands of fraud indicators. Combining machine learning and expert decisions will help you improve fraud detection accuracy and avoid becoming a cybercrime target by means of effective fraud prevention software.

Our fraud detection software developers at RNDpoint keep improving our tactics of abusive behavior detection, in order to provide high levels of protection for your business.

Case study: Fraud detection solution for Insurance industry

fraud detection software in insurance

Insurance Fund addressed us with the issue of financial loss due to fraudulent activity of some of their customers. RND Point developed a custom anti-fraud solution. The automated fraud detection conbined with algorithms identifies up to 90% of complex fraudulent schemes  and decreased fraud by 26%.

Industries We Serve

For certain businesses, turning to fraud detection services is the way to avoid regulatory penalties and losses. RNDpoint’ experts specialize in insurance, healthcare, banking, manufacturing, procurement, and telecom industries.

Insurance fraud detection software

Health, home, and car insurance fraud is most common in this industry. Our experts analyze all the stages of insurance claim processing and identify cases of suspicious activities. To complete this task, we use diverse methods: machine learning, anomaly detection, text mining, business rules, and more.

Healthcare fraud detection software

Developing medical fraud detection software, we help healthcare organizations successfully automate fraud detection and improve the integrity of their practices. We target most typical fraud categories and help circumvent medical billing errors, fraudulent claims, upcoding, billing for services that weren’t provided, and more.

Financial fraud detection software

Banks have less than a second to detect and stop a fraudulent transaction. We develop fraud detection software for banks using intelligent analytics to identify suspicious behavior and curb financial fraud before it affects customers. Credit card fraud prevention software we implement keeps organizations safe and their clients satisfied.

Manufacturing fraud detection software

Fraud detection is especially relevant to the manufacturing sector. The most widespread fraud types in this industry are IP infringement and false warranty claims, among others. RNDpoint’ experts develop and implement fraud prevention and detection software that significantly reduce financial losses and helps quickly identify fraud cases.

Procurement fraud detection software

Companies engaged in procurement have to follow a systematic approach to detecting abusive behavior. Recognizing the difficulty of spotting fraud in the complex procurement environment, our experts tailor fraud detection software to identify anomalies, suspicious patterns, and possible collusion cases.

Telecom fraud detection software

Operators and subscribers alike can fall victim to multiple fraud types: over-the-phone phishing scams, international revenue sharing, traffic pumping, and more. Telecom fraud detection software greatly mitigates the risks of fraud, and RND Point’ specialists help telecom companies make effective decisions on fraud cases in real time.

Our Fraud Detection Services

RND Point’ fraud detection services cover two broad stages: data analysis and processing.

Data analysis 

RND Point’ experts analyze data using a variety of methods, including but not limited to:

  • Email suspect
  • IP bots, blacklists, worms, spam history
  • IP movement velocity
  • Device fingerprint activity
  • Geolocation distance between data points
  • Phone format validity
  • Domain registration
  • Frequency of repeated data
  • Location checking by country, city, and postal codes
  • Records of the community sharing fraud information

Data processing

After our solution has tracked millions of domains, proxies, and device fingerprints, the processing begins. At this stage, we use the following toolsets:

  • Rules
  • Algorithms
  • Machine learning

Our Fraud Detection Roadmap

  • Discovery. Our experts analyze the most common fraud scenarios in your business operations and prepare a set of specific criteria. 
  • Rules. Using these criteria, our clients define business conditions to create rules of fraud detection. 
  • Algorithms. We build machine learning algorithms to enable case detection.
  • Scanning. The bulk of discrete data is turned into grouped cases and marked for a possibility of fraud.
  • Fraud indicators. The system generates hundreds of fraud indicators, which are assigned to a human expert to make the final decision.
  • Decision. The expert makes the final decision on whether the case is FRAUD or NOT.

Why Choose Fraud Detection Solutions by RND Point

With our custom fraud detection systems, we aim at fostering a proactive anti-fraud culture in our client’s organizations. Our studies reveal that such systems help to fight against new, unusual and known bad behaviors and filter suspicious cases in advance.

In cooperation with our clients, we help them build a fraud-and-abuse taxonomy based on fraud detection insights. As a result, our fraud prevention solution helps automate improvements to the manual revision processes and raises overall accuracy and efficiency of fraud detection at organizations.

Business outcomes

  • Fraud detection increased by 10%
  • Minimized risks of revenue loss
  • Development of a proactive anti-fraud culture

Key features

  • Advanced machine learning algorithms
  • A wide range of features
  • Adjustable functionality
  • High security level
  • Ongoing support

Got challenge? Get in touch!