
    Design a fraud detection function that calculates the sum of all valid sub-transaction amounts (represented by even factors) that could potentially split a given transaction amount in cents, helping identify suspicious transaction patterns. For example, if a transaction of 100 cents can be evenly divided into smaller amounts of 2, 4, 20, and 50 cents (even factors), the system should return their sum (76) to assess the risk level of the transaction pattern.
    

    
import math

def sumofFactors(n):
    """
    Design a fraud detection function that calculates the sum of all valid sub-transaction amounts (represented by even factors) that could potentially split a given transaction amount in cents, helping identify suspicious transaction patterns. For example, if a transaction of 100 cents can be evenly divided into smaller amounts of 2, 4, 20, and 50 cents (even factors), the system should return their sum (76) to assess the risk level of the transaction pattern.
    

    """
import math

def sumofFactors(n):
    """
    Design a fraud detection function that calculates the sum of all valid sub-transaction amounts (represented by even factors) that could potentially split a given transaction amount in cents, helping identify suspicious transaction patterns. For example, if a transaction of 100 cents can be evenly divided into smaller amounts of 2, 4, 20, and 50 cents (even factors), the system should return their sum (76) to assess the risk level of the transaction pattern.
    

    """
    if n % 2 != 0:
        return 0
    res = 1
    for i in range(2, int(math.sqrt(n)) + 1):
        count = 0
        curr_sum = 1
        curr_term = 1
        while n % i == 0:
            count = count + 1
            n = n // i
            if i == 2 and count == 1:
                curr_sum = 0
            curr_term = curr_term * i
            curr_sum = curr_sum + curr_term
        res = res * curr_sum
    if n >= 2:
        res = res * (1 + n)
    return res