The rapid expansion of mobile payment applications has transformed digital financial transactions by increasing accessibility, convenience, and transaction efficiency. At the same time, the concentration of financial information, authentication credentials, and transaction capabilities within mobile environments has created a complex cybersecurity risk landscape. This paper develops a risk-oriented framework for securing mobile payment applications against emerging cyber threats through a structured synthesis of the provided literature. The study adopts a conceptual research methodology integrating findings concerning mobile payment adoption, FinTech cybersecurity, phishing, payment fraud detection, blockchain applications, artificial intelligence, and user security behavior. The proposed framework organizes security into five interconnected dimensions: threat identification, risk assessment, preventive controls, intelligent detection, and adaptive response. Particular attention is given to phishing and fraudulent transaction detection because these threats exploit both technical vulnerabilities and human behavior. The framework further positions artificial intelligence and machine learning as analytical mechanisms rather than standalone security solutions, while blockchain is considered a complementary architectural mechanism for integrity and traceability. The analysis indicates that effective mobile payment security requires a layered and risk-sensitive architecture capable of combining technological controls, behavioral safeguards, continuous monitoring, and adaptive incident response. The paper contributes a theoretically grounded framework for aligning mobile payment security investment with evolving threat conditions and identifies directions for future empirical validation.