Market Trends of AI In Fintech Industry
Fraud Detection Expected to Witness Significant Market Growth
- Artificial intelligence can assist in identifying rapid and effective ways to detect financial fraud and malpractice. They allow machines to process enormous datasets, which people sometimes struggle with. Using artificial intelligence for fraud detection accurately has various advantages. The ability to compute quickly is a well-known benefit of AI and machine learning. It creates a grasp of a user's app usage habits, such as transaction methods and payments, allowing it to spot anomalies in real time. It reduces false positives and allows specialists to focus on more complex issues because it is more efficient than manual techniques.
- Banks combat fraud through a multi-faceted approach, including encryption, two-factor authentication, AI-powered anomaly detection, and real-time monitoring. Additionally, they prioritize security with routine audits, educate both staff and clients on best practices, and foster collaborations with industry peers to stay ahead of evolving threats. The banking industry faces a range of fraud challenges, from identity theft and credit card fraud to phishing and money laundering. This diversity underscores the need for banks to continually refine their defenses, adapting to the ever-evolving tactics of fraudsters.
- According to a poll conducted by Certified Fraud Examiners (ACFE) and analytics pioneer SAS, the use of artificial intelligence (AI) and machine learning (ML) for fraud detection increased internationally in 2024. According to the poll, 13% of organizations employed artificial intelligence (AI) and machine learning to detect and deter fraud, with another 25% planning to do so in the next year or two, representing roughly 200% growth. According to the poll, fraud examiners identified this and other anti-fraud tech developments to be extensively expanding across industries.
- The players in the market are collaborating to provide better service to customers. For instance, in February 2023, Mastercard partnered with Network International, the Middle East and Africa's premier provider of digital commerce, to address fraud, declines, and chargebacks to minimize costs and risk for acquirers. Through the collaboration, Network planned to roll out Mastercard's Brighterion AI technology across the region, providing acquirers and businesses with transaction fraud screening and merchant monitoring services.
- Further, in March 2023, CSI, a comprehensive fintech and regtech solutions provider, collaborated with Hawk AI, a leading global provider of anti-money laundering (AML) and fraud prevention technologies tailored for banks and payment processors. Together, they unveiled their newest offerings: WatchDOG Fraud and WatchDOG AML. These products leverage advanced artificial intelligence (AI) and machine learning (ML) models to deliver a sophisticated, automated surveillance system. The system has been designed to swiftly identify, monitor, and report any suspicious or fraudulent activities in real time. Specifically, WatchDOG Fraud is adept at spotting emerging fraudulent patterns, regardless of the channel or payment method, by closely analyzing transaction behaviors.
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North America Accounting for the Largest Market Share
- North America is expected to dominate the AI in fintech market due to prominent AI software and systems suppliers, combined investments by financial institutions into AI projects, and the adoption of the highest number of AI in fintech solutions. The regional market is expected to experience significant growth over the coming years. Additionally, North America serves as the business hub for many AI fintech firms, with companies like Sidetrade choosing to locate their North American operations in Calgary.
- Government initiatives and investments in AI are driving the market. For instance, in October 2023, the US National Science Foundation allocated USD 10.9 million to bolster research, emphasizing the crucial alignment of artificial intelligence advancements with user safety. Spearheaded by the Safe Learning-Enabled Systems program, a collaboration among the NSF, Open Philanthropy, and Good Ventures, the initiative was aimed to catalyze fundamental research. This research is expected to be pivotal in crafting and deploying computerized learning systems, such as autonomous and generative AI technologies that prioritize safety and resilience.
- The players in the market are collaborating to provide better service to customers in the region. For instance, in June 2024, NatWest, in collaboration with IBM, announced that it was set to unveil Cora+, an enhanced iteration of its digital assistant, Cora, during London Tech Week. This move would position NatWest as a pioneer among UK banks, being among the first to leverage generative AI in a digital assistant. Powered by natural language processing and machine learning technologies, Cora provides round-the-clock assistance to customers, addressing their banking queries. In 2023 alone, this digital assistant handled a notable 10.8 million queries, showcasing a significant surge from the 5 million queries it managed in 2019.
- Some companies' solutions help businesses grow retail banking with next-best-action software, detect and combat financial fraud, and improve client relationships with multichannel customer experience solutions. For instance, in January 2023, Inscribe, a company dedicated to combating financial fraud, secured a substantial USD 25 million in funding, bolstering its efforts with cutting-edge artificial intelligence. Inscribe's AI technology meticulously parses, classifies, and cross-references financial onboarding documents, pinpointing any disparities between the submitted papers and the retrieved records. Leveraging its AI-driven fraud detection, Inscribe not only highlights inconsistencies but also automatically creates personalized risk profiles for each customer. These profiles, enriched with insights from bank statements and transaction histories, are crafted from key document details like names, addresses, and financial transactions.
- Banks in the region have started using blockchain technology to record data and combat fraud. Blockchain records the details of each transaction, making it easier to detect hacker attempts. This technology permits worldwide payments and allows for speedy transactions with low commissions. The Distributed Ledger Technology (DLT) of blockchain assists in the recording and sharing of data across different stores and a distributed network. Furthermore, cryptographic and algorithmic methods synchronize data across the financial network. This is a significant step since transaction data can be stored in different locations, paving the way for blockchain interoperability and cross-industry data exchange.
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