Fraud Detection and Prevention Market size was valued at USD 41.94 Billion in 2022 and is poised to grow from USD 57.73 Billion in 2023 to USD 272.34 Billion by 2031, at a CAGR of 23.80% during the forecast period (2024-2031).
Fraud Detection and Prevention market, in the past years, experienced several common frauds supported by modern fraud methods like generative AI. The growing number of online transactions has also given rise to the complexity and frequency of such deceitful activities. To control the number of these activities, companies worldwide are investing to launch improved solutions for industries like healthcare, BFSI, and others.
Fraud detection is of supreme importance, mainly for the banks and other firms that daily deal with a major number of transactions. They have greater chances of suffering from fraud. Nonetheless, other domains like credit card companies, electronic payment platforms, e-commerce companies, and B2C fintech firms also demand fraud detection to reduce or avoid financial fraud cases. With the growing digital trend, the number of frauds has also significantly increased. Especially in the BFSI sector, stolen or fake credit card fraud is increasing. The ecommerce and retail industry has witnessed a substantial boom since the pandemic and the ecommerce channels have been most commonly targeted. The common techniques are promo abuse, delivery fraud, payment fraud, and more. Also in the IT and Telecom industry, phone fraud is growing common. They use telecommunication services and products aiming to acquire money illegally.
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Use of Improved Technologies to Increase Fraud Detection Efficiencies in the Market
With Machine Learning and Artificial Intelligence, market players have launched more effective techniques than ever. Companies are increasingly using AI software and chatbots to improve the detection of fraud analysis. This will majorly reduce fraudulent activities in the market. In the insurance sector, fraud detection solutions made with machine learning, AI chatbots, improved algorithms, analytical design, and widespread databases will offer real-time detection of fraud. Companies can also train software developers to improve dedicated software packages with superior technology as per needs. The main features like real-time monitoring will study past fraud patterns and match them with the present claims. Later, it can be used to monitor suspicious behaviors in real-time. Predictive modeling will make predictions and offer information on potential risks. Automation aids in avoiding losses by speeding up the procedures. A simplified and smooth workflow is always more efficient than a conventional one. Identity analysis comprises the study of history of the policyholder, family history, biometric verification, and more. It gives sufficient information to determine if the person belongs to a certain red-flag category.
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- In 2024, Riskified, an innovative company, announced the growth of its Dispute Resolve platform. This expansion is majorly driven by the growing demand to simplify the chargeback operations, especially during the high chargeback volumes post-holiday periods. It integrates improved AI and gateway to enhance and automate the efficiency of the dispute process associated with the chargeback.
- In 2023, ClearSale, a global risk prevention and business intelligence provider, announced the launch of its novel Client Portal. The portal is used by the customers of ClearSale to watch and manage fraud prevention information, chargebacks, and orders. It offers improved functionality and a simplified interface.
- In October 2023, SEON, an end-to-end fraud prevention platform, announced that it is now available to the AWS (Amazon Web Services) Marketplace. This availability will offer a smooth process for partners and customers, allowing them to avoid fraud and improve efficiency.
- In April 2024, NICE Actimize company announced the launch and availability of Integrated Fraud Management (IFM 11). This platform is AI-driven fraud detection and management. It leverages recent improvements in AI along with its exceptional collective smart abilities to introduce unmatched fraud detection correctness, efficiency, and agility to defend financial services companies and their clients from the upcoming AI-driven scams and fraud.
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Today, fraud detection and avoidance is a serious issue for any business functioning in the modern world. But, by understanding the basics of fraudulent detection and prevention, with the prominent types of fraud, businesses can adopt the ideal solution for their needs and priorities.
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