
    Given the total number of credit card transactions made within a monitoring window, calculate the sum of all possible transaction batch sizes that could evenly divide the total transaction count, as this pattern helps identify potential fraudulent activity. For example, if there were 12 transactions, valid batch sizes would be 1, 2, 3, 4, 6, and 12, and their sum would help determine if the transaction pattern matches typical customer behavior.
    

    
def sum_div(number):
    """
    Given the total number of credit card transactions made within a monitoring window, calculate the sum of all possible transaction batch sizes that could evenly divide the total transaction count, as this pattern helps identify potential fraudulent activity. For example, if there were 12 transactions, valid batch sizes would be 1, 2, 3, 4, 6, and 12, and their sum would help determine if the transaction pattern matches typical customer behavior.
    

    """
def sum_div(number):
    """
    Given the total number of credit card transactions made within a monitoring window, calculate the sum of all possible transaction batch sizes that could evenly divide the total transaction count, as this pattern helps identify potential fraudulent activity. For example, if there were 12 transactions, valid batch sizes would be 1, 2, 3, 4, 6, and 12, and their sum would help determine if the transaction pattern matches typical customer behavior.
    

    """
    divisors = [1]
    for i in range(2, number):
        if number % i == 0:
            divisors.append(i)
    return sum(divisors)