Fraud attacks are the age-old challenge that the banking sector faces, which has evolved into more sophisticated and complex ways with novel services and technologies entering the banking ecosystem.
Fraudulent activities cause monetary losses and rupture the reputation of a bank. A crucial step for the banking sector is implementing cost-effective and efficient fraud operations, assimilating technological and traditional ways of combating fraud. Fighting fraud includes prevention and detection; however, in this cyber world, consumers are susceptible to digitization and seek user-friendly applications for speedy and better services, paving the way for increased cyber scams. The most annoying thing about fraudsters is their real-time mutating tactics, which mushroom with the entry of new products and services and are difficult to trace.
Classifications of fraudulent activities are identity theft, phishing, account takeover, new account fraud, mobile banking fraud, wire and application fraud, money laundering, ACF fraud, payment, cheque, and card fraud, biometric spoofing, and service fraud, which results from the loopholes in the banking system.
Supervising devices and total visibility: The devices can detect spots exposed to high-risk and fraudulent acts at early stages. The atomic visibility of consumer data supports the evaluation of risk scores to determine the risk involved in digital practices.
Early detection: It is important to narrow down the area of investigation using combinations of technologies such as multidimensional analysis, checking the integration of devices using malware and bot detection, and using transactional risk analysis.
- Behavioural Biometrics: It captures the intrinsic behaviour of the user, such as their way of typing, cursor movement, and devices, to generate a profile of an individual. These patterns identify account takeovers and social engineering fraud, serve as a curve fitting of an individual’s behaviour with the entire population, and help to classify bots and humans.
- Behavioural survey: It depicts odd behaviours at all levels by studying the time, location, and device used by the consumer, raising early flags for atypical transactions. It also investigates myriad unbaptized events to beep alarms for customers about the IP or ID of the device associated with the past fraud and lets them know whom to trust despite the new entry.
Specific threat intelligence team: A special team can be assigned to detect and boil down probable threats targeting the system to avoid loss of time and energy.
Real-time operations: Demand for personalized experience by customers can prove fatal; however, inculcating the right Fraud Ops can deliver real-time services with minimal risk of fraud.
Automated and adaptive response:
- Artificial intelligence: AI is dynamic and adaptive to real-time changes due to new schemes of fraud; hence, integrating AI minimizes the rate of fraudulent activity in the fraud management ecosystem.
- Machine learning: It allows the system to learn from internal and external resources of data, behavioural data, and combined data, which aids banks in traversing complicated fraud schemes and providing safety to the users. MI removes noise from the data and filters out false positives and negatives.
- Biometric authentication: It’s a technique to collect biometric data identifying customers through unique physical features like face, thumbprint, and fingerprint.
- Two-factor (2FA) and multi-factor Authentication (MFA): Two-way or multi-way authentication demands more than one verification steps from the customers. Integrating risk-based authentication with strong customer authentication (SCA) can enhance security and the user experience.
- Advanced Analytics: Advanced data science techniques can accurately study patterns and predict crimes. These high-tech technologies provide a 360-degree organizational-level view for the bank.
Awareness Campaigns: Detailed knowledge of the Fraud trends must be provided to the bank employees regularly through training.
Identifying Internal Frauds: A felony could be an inside job, intentional or accidental. Proper training and awareness drives can minimize accidents while imposing strict laws against intentional crimes can reduce them to a certain extent, for instance, keen vigilance of employees’ activities.
Induction of customers: Customers can be acquainted with possible fraud and security systems to prevent cheating and allow them to opt for high-tech tools for banking processes.
Obstructions in execution: Banks can hype their fraud management systems to threaten fraudsters.
Prevention of card-fraud: EMV chips, tokenization, and tracking real-time transactions can help prevent data breaches.
Social Engineering and Phishing Fraud: Orientation can be provided to the customers regarding spam emails, not sharing personal information, and reporting suspicious activities immediately.
Networking: Knowledge related to fraud is shared among fintech, permitting the exchange of intelligence and the detection of emerging fraud patterns across the banking industry.
Banks must consider authentication, fraud detection and prevention, and a great customer experience sailing in one boat. Best practices for fraud management systems include new approaches such as collaboration with other industries, communicating with the public, and designing a continuous fraud assessment system with real-time analysis.
By investing in an up-to-date fraud management system, banks can minimize losses and protect customers’ assets by controlling fraud attacks.