An Enhanced Technique in ATM Risk Reduction using Automated Biometrics Fingerprint in Nigeria

An Enhanced Technique in Automated Teller Machine (ATM) Risk Reduction using automated Biometrics fingerprint in Nigeria was carried out as a preemptive measure to sub mantle the fraudulent activities of fraudsters in the banking industry. This research was aimed at developing an Automated Fingerprint Identification Machine (AFIM) that will enhance the performance and security of bank customers’ accounts now cashless policy is being enforced. This work adopted software development lifecycle (SDLC) as well as secured harsh (SHA) algorithm to determine the interface between the scanner and the proposed system and also the threshold of the scan fingerprint image. A SecuGen Hamster plus device was used on a Dell Inspiron machine for obtaining the fingerprint. Cross-correlation pattern matching schemes for matching and aligning the enrolled sampled image on the single singular point (as a reference point) was adopted for authentication. However, the model implementation showed robustness in security and service delivery performance.