Welcome 2024: New Artificial Intelligence tools that will aid fraud detection

AI-based solutions can connect with other security systems like biometric authentication and identity verification to detect fraudulence. (Image via Wikimedia Commons)

Over the last 20 years, fraud has cost economies around the world an average of 6.05 per cent of GDP. Companies have also reported that cyber attacks have cost them between three per cent and 10 per cent of their annual revenue. In addition, experts predict that between 2023 and 2027, the world will lose more than $343 billion due to digital fraud. In light of the estimated amounts of losses to be incurred, how a company can establish an effective fraud management system becomes paramount now.

The term “fraud management” refers to the process by which a company may find, stop, detect, and react to instances of fraud. The field of fraud management is significantly impacted by Artificial Intelligence (AI). By analysing massive volumes of data, AI systems like Machine Learning (ML) algorithms can spot irregularities that could point to fraud. Several forms of fraud, including phishing, identity theft, and payment fraud, can be detected and prevented by fraud management systems powered by AI. They can also adjust to changing circumstances and pick up on emerging tendencies in fraud, making them more effective detectors. For a more all-encompassing strategy against fraud, AI-based solutions can connect with other security systems like biometric authentication and identity verification.

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Advantages of AI in the field of fraud prevention:

Real-time Surveillance: AI-powered systems can continuously monitor transactions and activity, promptly detecting any abnormalities and probable instances of fraud. The swiftness of this speed is vital in thwarting the occurrence of fraudulent transactions.

Advanced Pattern Recognition: Artificial Intelligence can detect complex patterns and correlations in data that may be beyond the comprehension of human analysts. It allows for the identification of even subtle indications of fraudulent activity.

Behavioural Analysis: Artificial Intelligence can analyze user behaviour and construct profiles to detect departures from typical patterns. It is very efficient in detecting instances of account hijacking.

Adaptive Learning: AI systems consistently acquire knowledge from fresh data, adjusting to changing fraud techniques and maintaining an advantage over fraudsters’ tactics.

AI fraud detection tools for 2024

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SEON: SEON offers a range of tools and technology that include detailed device fingerprinting for creating thorough user profiles, extensive data enrichment based on email addresses, IP addresses, or phone numbers, and the ability to examine over 90 social and digital profiles to uncover the genuine intentions of your customers. SEON stands out as a unique fraud-detection tool due to its upfront cost and the inclusion of a free trial. The current roster of clients comprises Revolut, Albo, Kindred Group, and Nubank.

Sift: Sift provides fraud prevention services for 34,000 websites and applications, including globally recognised brands like Airbnb and McDonald’s. The company’s primary offerings consist of a comprehensive Digital Trust and Safety Suite, which integrates all the separate API tools into a unified and complete solution. Additionally, there exists a specialised module that serves the purpose of verifying the identity of users and preventing unauthorised access to accounts, hence mitigating account takeover (ATO) assaults. This module offers the functionality of enabling two-factor authentication (2FA) simultaneously.

Signifyd: Signifyd safeguards 10,000 e-commerce sites worldwide with the assistance of three essential products: payments optimisation, revenue protection, and abuse protection — to prevent chargebacks. The company’s products are designed to handle substantial volumes of transactions, and they even implement chargeback protection through a chargeback-guarantee model, which requires payment of chargeback administration fees in advance.

ArkOwl: Mike Greiling, a GitLab engineer, and Rob Daline co-created ArkOwl before integrating into the platform-as-a-service of NICE Actimze in 2019. It can retrieve email information from up-to-date databases, including those of service providers, social networking sites, WHOIS databases, and webmail hosts. While email data enrichment is its primary objective, the system can also examine and enhance information derived from phone numbers and IP addresses, as illustrated when reading domain information. It conducts searches on multiple social media platforms to provide valuable user profiles.

Ekata: This application is a sophisticated and firmly established system for detecting fraudulent activities. Established in 1997 (formerly known as Whitepages), Ekata provides worldwide identity authentication and fraud mitigation services. Ekata, acquired by Mastercard in 2021, has direct experience working with major corporate clients, including Lyft, Equifax, and Microsoft.

For managing these activities and doing manual fraud investigations, the anti-fraud platform has five primary products:

  • Transaction Risk
  • Phone Intelligence
  • Account Opening
  • Address Risk APIs
  • Pro Insight interface

Check and mate

AI and ML are built into the best cybersecurity solutions and renders them dynamic ability to adapt to threats that evolve constantly. It will, thus, protect you from fraud risks that use automated scripts, like taking over your account, keying your credentials, card fraud, making a fake account, and more.


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