Aim: To estimate accuracy in Digital signature identification and verification using Novel Convolutional Neural Network compared with Support Vector Machine. Materials and Methods: Convolutional Neural Network and Support Vector Machine Algorithms are implemented in this research work. Sample size is calculated using G power software and determined as 10 per group with pretest power 80%. Results and Discussion: Convolutional Neural Network provides a higher of 98.34% compared to Support Vector Machine with 97.63% in Digital signature identification and verification. There is a statistically significant difference between the study groups with p = 0.125 (p<0.05). Independent T-test value states that the results in the study are insignificant. Conclusion: Convolutional Neural Network gives better accuracy then Support Vector Machine Algorithm