This paper examines the role of AI in improving cybersecurity in digital finance and the consumers’ attitude towards the adoption and effectiveness of AI-based solutions to cyber threats. Especially when the financial sector over time has shifted to online platforms, then issues of fraud, hacking, and data tampering become very paramount. This work seeks to compare the effectiveness of four AI models; Random Forest, SVM, Neural Networks, and Decision Tree in combating different types of cyber threats in the digital finance sector. This experiment conclude that Random Forest has the highest accuracy rate of 92% while, SVM has 89% accuracy rate, Neural Network has the accuracy rate of 85% and Decision Trees have 80%. These arguments show the benefits that can be derived through the employment of AI in addressing the issue of fraud and risks in the field of digital finance. Moreover, this research provides evidence that AI based cybersecurity enhances consumer confidence with 75% of participants expressing high confidence in solutions and technologies built on artificial intelligence. AI has efforts aimed at making sure that there is security for the transaction in finance, which in the process, increases customer satisfaction for the automated systems in finance. In any case, it can be concluded that the use of AI helps in solving the problems of cybersecurity and provides financial institutions with a capable method for addressing these issues as well as a powerful tool for the development of new financial services