Extending the Design of Smart Mobile Application to Detect Fraud Theft of E-Banking Access Using Big Data Analytic and SOA
Lazuardi Ridho Maulana, Ahmad Nurul Fajar, Meyliana Meyliana · 2021
For the current situation in which digital banking services are becoming more popular, fraud detection applications are required. Banks are among the other businesses with confidential data assets that must be safeguarded because they have financial information. E-banking channel (mobile banking, internet banking, ATM) is required in the digital era for managing financial activities such as international remittance, transfer fund, and other banking activities. Banking industry facing how the fraudster try to breach the mobile banking services, it will be the biggest challenge for banks in order to maintain the confidence, integrity, and availability of their IT security systems. Potential attacks on confidential information may be carried out by the employee as well as by external parties. Banks attempt to engineer a software to prevent a higher loss due to fraud action in order to maintain the balance of security and convenience of customers when using a banking services. One of the most common attacks is social engineering and data intervention by internal employees; the focus of this research is to discuss the two potential attacks on accounts that have been dormant for a long time and deal with them using an application based on the SOA and Big data approach.