A method for identity verification, wherein the method comprises: obtaining personal information and network environment information of a current operator after an account information updating request is received, wherein the network environment information of the current operator represents a security of a network environment in which the current operator is located; separately performing risk identification on the personal information and the network environment information to correspondingly obtain a first risk identification result and a second risk identification result, wherein the first risk identification result is used to represent a risk that the current operator is inconsistent with an account owner, and the second risk identification result is used to represent a risk that the security of the network environment in which the current operator is located is risky; selecting an identity verification method based on the first risk identification result and the second risk identification result; and performing identity verification on the current operator based on the selected identity verification method; wherein the selected identity verification method is an identity verification method using a prestored machine learning model and the step of performing identity verification on the current operator based on the selected identity verification method comprises: inputting the first risk identification result and the second risk identification result to the prestored machine learning model to obtain an identity verification result of the current operator, wherein the identity verification result is used to represent a probability that the current operator is the same as the account owner. obtaining personal information and network environment information of a current operator after an account information updating request is received, wherein the network environment information of the current operator represents a security of a network environment in which the current operator is located; separately performing risk identification on the personal information and the network environment information to correspondingly obtain a first risk identification result and a second risk identification result, wherein the first risk identification result is used to represent a risk that the current operator is inconsistent with an account owner, and the second risk identification result is used to represent a risk that the security of the network environment in which the current operator is located is risky; selecting an identity verification method based on the first risk identification result and the second risk identification result; and performing identity verification on the current operator based on the selected identity verification method; wherein the selected identity verification method is an identity verification method using a prestored machine learning model and the step of performing identity verification on the current operator based on the selected identity verification method comprises: inputting the first risk identification result and the second risk identification result to the prestored machine learning model to obtain an identity verification result of the current operator, wherein the identity verification result is used to represent a probability that the current operator is the same as the account owner.