Bazar Money Transfer的动态

Cognizant and FICO pair up to fight real-time payments fraud. Cognizant announced a planned collaboration with FICO, a leading analytics software company, to launch a cloud-based real-time payment fraud prevention solution powered by FICO? Falcon Fraud Manager. The joint offering would leverage both firms' artificial intelligence (AI) and machine learning (ML) technology to help banks and other payment service providers in North America protect their customers from fraud in the growing world of instant digital payments. While real-time payments have ushered in a new era of speed and convenience, they have also opened the door for scammers. The Cognizant and FICO offering would tackle this challenge by providing real-time fraud prevention with a seamless integration of the real-time payments rails. "In today's fast-paced financial landscape, staying ahead of fraudsters is crucial. Our collaboration with Cognizant aims to provide stronger protection for real-time payments by combining the Cognizant communication layer and clearing gateway with FICO Falcon Fraud Manager, the leading payments fraud management solution," said Alexandre Graff, Global Head of Partners & Alliances at FICO. "As new instant payments like FedNow Service gain popularity, banks and payment providers need to have guardrails in place to protect customers from the growing number of financial scams," said Nageswar Cherukupalli, Senior Vice President & Business Unit Head of Banking & Capital Markets and Strategic Initiatives of Cognizant. Source: https://lnkd.in/edGS6FgH Sign up for more news updates like this in our daily newsletter: https://lnkd.in/eskQx7Ym #regtech #partnership #ai #fraud #fraudprevention #cybersecurity #financialtechnology #financialservices #fintechnews

Exciting news from #FICOWORLD24! FICO and Cognizant have announced a groundbreaking collaboration. At this year's event in San Diego, Cognizant unveiled plans to launch a cloud-based real-time payment fraud prevention solution, powered by FICO? Falcon? Fraud Manager. This innovative solution leverages cutting-edge AI and ML technology to safeguard customers from fraud in the dynamic landscape of instant digital payments. Real-time payments offer unprecedented speed and convenience, but they also present new challenges. With this joint offering, FICO and Cognizant are addressing these challenges head-on by providing seamless integration of real-time payments rails and delivering accuracy in fraud detection and prevention. This collaboration is a testament to the power of AI and ML in financial services. To learn more about this innovative solution, click on the link below. #FICO #Cognizant #RealTimePayments #FraudPrevention #AI #ML #PaymentSecurity https://lnkd.in/eKVNjcvU

A?Fraud Management System (FMS)?is a technology-driven solution designed to detect, prevent, and manage fraudulent activities across various industries, such as banking, insurance, e-commerce, telecommunications, and more. It uses advanced analytics, machine learning, artificial intelligence, and rule-based systems to identify suspicious patterns, anomalies, or behaviors that may indicate fraud. Key Features: Real-Time Monitoring: Continuously tracks transactions and activities to detect fraud as it happens. Anomaly Detection: Uses AI/ML algorithms to identify unusual patterns or deviations from normal behavior. Rule-Based Systems: Predefined rules flag suspicious activities (e.g., high-value transactions, multiple login attempts). Risk Scoring: Assigns risk scores to transactions or users based on likelihood of fraud. Case Management: Provides tools for investigating and resolving flagged incidents. Integration: Seamlessly integrates with existing systems like payment gateways, CRM, and ERP platforms. Reporting and Analytics: Generates insights and reports to improve fraud prevention strategies. Benefits: Reduces financial losses due to fraud. Enhances customer trust by securing transactions. Improves operational efficiency by automating fraud detection. Helps comply with regulatory requirements. Common Use Cases: Detecting credit card fraud. Preventing identity theft. Stopping insurance claim fraud. Combating account takeover (ATO) attacks. Challenges: Balancing fraud detection with customer experience (e.g., minimizing false positives). Keeping up with evolving fraud tactics. Managing large volumes of data for real-time analysis. ADSTRA Company provided the best solutions and support in this business. contact us for more details and assistance. #ComplaintResolution #CustomerSatisfaction #TechSupport #BankingHelp #InsuranceHelp #FraudSolutions #TelecomSupport #ResolveAndImprove https://lnkd.in/eCyVumz2

???????????????? ???????????????????? ???????? ?????????????? ????????????; ???? ?????????? ?? ???????? ???? ???????????????????? ???????? ?????? ???????????????????? ??????????????: Govt's direction through I4C to curb the unauthorised use of PAN details is another welcome step towards protecting the gullible customers from organised gangs of cyber criminals. PAN enrichment services help lenders create Customer's profile using personal data. Problem comes when this data somehow reaches the Dark-webs or the digital fraudsters and is used to defraud the vulnerable section of customers. RBI and Govt have already taken many steps to protect customers from cyber criminals. RBI MD on digital payment security controls issued in Feb 21, inauguration of I4C in 2020 by MHA, Section 3.4 in RBI MD on FRM issued in July 24 mandating robust EWS framework for non-credit transactions and setting up of Data Analytics & MI units in Banks/NBFCs are major steps in this direction. However, easy money that too in non F2F environment attracts the fraudsters and no surprise that a whopping INR 1.2 lakh crore have been estimated as Cyber Fraud losses next year. To supplement the efforts of Govt and Regulator and to restrict the syndicates of Cyber criminals and keep the trust of customers on the digital systems all the stake holders i.e. Issuing Banks (Customer's Bank), Acquiring Banks(Merchants Bank), Payment Aggregators, card networks including NPCI (RuPay Card, UPI, AEPS), I4C, LEAs,?Industry experts and tech firms having expertise in AI ML and latest innovations need to collaborate and put in place necessary systems to a) proactively stop the frauds using Real-time business rules b) Minimise the Customer's losses using near real-time business rules c) Recover the defrauded money d) Catch the culprits?e) continuously innovate to be above the innovation curve of fraudsters. Recently launched RBIH mule hunter should also help and is a welcome step. However, it's success will again depend upon the quality and speed of exchange of data and collaboration among all stake holders. AI firms with expertise in leveraging latest innovations in technology for fraud detection would be extremely critical for the success of this RBIH initiative as well as in establishment of EWS framework and Data Analytics & MI unit in Banks/NBFCs.

Generative AI is amazing AND dangerous. Check out this article and let me know when you are ready to talk Cyber Liability and D&O for your company.

Henrik is not wrong! It is an amazing feat to be the #leader for #paymentsfraud, proving that SAS has the #machinelearning required in an integrated solution to prevent #scams through #accurate and #insightfuldecisions. But additionally, we are also a #leader in our #frauddetectionandprevention capability satisfying the heightened demands of #enterprisefraud! This includes the underpinnings provided by the platform for those banks looking for a #scalable #cloudnative view across all #fraudrisks. See the report link below. And if you do not believe this report you can look to this other recent #analyst report as well https://lnkd.in/g5Ng-7Yc

?The Evolving Landscape of Payment Fraud and How Eftsure Protects You ( Part 3) ?? Manual Controls: A Weak Link? ?? Manual processes in finance teams are not only time-consuming but also highly susceptible to human error. This vulnerability creates an open door for fraudsters to exploit. For instance, a simple mistake in data entry can result in significant financial losses, as seen in cases where incorrect bank account details lead to funds being diverted to fraudulent accounts. Additionally, manual approval processes often lack the rigorous verification needed to detect sophisticated scams. AI and deepfake technologies have amplified these risks. Fraudsters can now create convincing fake invoices, manipulate emails to mimic legitimate vendors, and even use AI-generated voice or video deepfakes to impersonate senior executives. In a notable case, a UK energy company was defrauded of $243,000 when criminals used deepfake technology to mimic the CEO's voice, instructing an employee to transfer funds to a fraudulent account. Such incidents demonstrate how advanced fraud tactics can easily bypass manual controls, exploiting the inherent weaknesses of human-dependent processes. As fraud tactics evolve, it’s crucial for companies and finance professionals to move away from outdated manual processes and adopt the new industry standard of "Digital Internal Controls." Digital Internal Controls, such as those provided by Eftsure, automate vendor verification, ensuring payments are made only to authorized accounts. Eftsure’s platform continuously monitors and verifies vendor information in real-time, detecting anomalies and flagging suspicious transactions before any damage can occur. By leveraging these advanced digital solutions, organizations can significantly reduce the risk of fraud and enhance their overall financial security. The transition to Digital Internal Controls is not just a technological upgrade; it’s a strategic imperative. Companies that embrace automation and real-time verification can stay ahead of fraudsters, safeguarding their assets and maintaining the integrity of their financial operations. Say goodbye to the vulnerabilities of manual controls and hello to a secure, automated future with Eftsure. #Automation #FinanceSecurity #Eftsure

Using Data and AI to Combat Account-to-Account Payments Fraud The rise of real-time payments (RTP) has necessitated a shift from traditional rules-based systems to AI-enabled solutions for fraud detection. Unlike traditional systems, AI excels at recognizing patterns and anomalies in data, allowing it to detect fraud more effectively and adapt in real time to emerging threats. This ability is crucial for tackling sophisticated fraud schemes, such as those involving mule accounts and coordinated scams, which are often interconnected. ?? AI's Role in Fraud Prevention AI-powered systems can evaluate transactions and assign nuanced risk scores, identifying irregularities like changes in geolocation, devices, or user behavior. Unlike traditional methods that rely on post-loss adjustments, AI models can adapt dynamically, making them ideal for the rapid decision-making required in RTP systems, where transactions are completed within seconds. This speed minimizes false positives and reduces the need for manual reviews, freeing up resources for more complex fraud cases. ?? Leveraging Data for Enhanced Security AI's effectiveness relies on access to diverse and robust datasets. Three data models have emerged for fraud prevention: ?? Single Financial Institution (FI) Insights: Limited to an individual FI’s data, this approach offers localized value but lacks a comprehensive market perspective. ?? Consortiums and Data Partnerships: Collaboration between multiple FIs or third-party providers expands data access, offering broader insights but limited by the scope of the consortium. ?? Multi-FI and Network-Level Insights: Aggregating data across FIs and networks provides the most comprehensive view, enabling better detection of risks such as mule accounts and cross-network fraud schemes. Cross-network analysis is particularly valuable in fragmented markets like the U.S., where fraud spans multiple networks, such as FedNow and crypto exchanges. Vendors like Visa, leveraging their extensive network and data assets, can enhance fraud prevention across these diverse channels. ?? Customizability and Explainability Effective fraud prevention requires tailored strategies that align with each FI's risk appetite and customer demographics. Customizable AI systems allow FIs to integrate their expertise, adjusting rules and objectives to meet their unique needs. Additionally, explainability in AI is critical for regulatory compliance and building trust. Systems must be designed to provide transparent insights into how decisions are made, addressing the "black box" issue that has historically hindered AI adoption. ?? Sub for more insights https://lnkd.in/d94JgWBU Source Visa #fintech #ai #banking Prasanna Thomas Richard Panagiotis Tony Nicolas Arjun Dr Ritesh Sandra

???????? ?????? ???????? ???????????????? ?? ???????? ???????? ???????????? ????????????????, ???????? ???? ?????????????? ?????????? ???? ?????? ?? ???????????????????? ??????????????? People often receive calls from unknown numbers, with the caller claiming to be from their bank and requesting verification details to "secure" their account. These are classic phishing attempts, but thankfully, many realize the danger and hang up before falling victim. Fraudulent calls like this are becoming all too common, with most people receiving 3-4 such calls a week. But here's the alarming part — these fraudsters aren’t just stopping at calls. They're using mule accounts to move illegally obtained funds, exploiting innocent victims in the process ?????????? ??????’?? ???????? ???????????? ???? ????????: In a bid to tackle this growing issue, the Reserve Bank of India (RBI) has introduced a revolutionary AI-powered tool called Mule Hunter. This tool is designed to detect and prevent the misuse of mule accounts, which criminals use for illegal financial activities ?????? ???????? ??x?????????? ???? ?? ???????? ??????????????? A mule account is an account used by criminals to launder money. Instead of transferring money to their own account (which would raise suspicion), fraudsters use the accounts of unsuspecting individuals—often poor, illiterate people or those with dormant accounts. These innocent people are unknowingly paid a small sum to facilitate the fraud without realizing the consequences Here's the shocking part: * 4.5 million mule accounts have been identified and frozen in India * Major banks like SBI, PNB, Kotak, and others have reported thousands of these accounts being involved in fraudulent activities * This is where the Mule Hunter AI Tool comes in, utilizing machine learning algorithms to detect unusual patterns of activity in these accounts. For example, an account that has been dormant for years suddenly shows large transactions—this is flagged immediately ?????? ???????? ?????? ???????? ????????? The AI tool analyzes 19 distinct patterns that could indicate fraudulent activity, helping banks identify suspicious accounts much faster than traditional methods. With this powerful technology, RBI aims to reduce digital fraud in the country significantly ????????????????????: Mule accounts are a serious problem in India, often exploited by criminals to launder money. The launch of Mule Hunter is a critical step in combating financial fraud, but it also highlights the importance of awareness. As consumers, we must be cautious of suspicious calls and transactions. The RBI is making progress, but the fight against fraud requires vigilance from all sides—banks, regulators, and individuals alike #DigitalFraud #AI #CyberSecurity #Payments #RBI #MuleHunter https://lnkd.in/dzSmEwjA

According to a recent survey by the Payments Association, AI-powered fraud poses a significant threat to the security of payment systems. However, amidst these challenges, innovative solutions are emerging to safeguard against such risks. The survey underscores the pressing need for proactive measures in combating fraudulent activities, especially as technology continues to evolve. One notable solution highlighted in the report is www.fraudgraph.ai, an advanced AI platform dedicated to detecting and preventing fraudulent transactions. FraudGraph's cutting-edge technology utilizes sophisticated algorithms and machine learning to analyze vast amounts of transactional data in real-time, enabling businesses to identify and mitigate potential risks efficiently. By leveraging AI capabilities, FraudGraph empowers organizations to stay ahead of fraudsters and protect their financial assets. As the digital landscape expands, so do the complexities of fraud. It's imperative for businesses to adopt robust solutions like FraudGraph to fortify their defenses and ensure secure payment ecosystems for both customers and stakeholders. To learn more about the survey findings and how www.fraudgraph.ai is revolutionizing fraud detection, check out the full article: https://lnkd.in/enEtvAJi