
    In a credit risk assessment system, given a binary risk profile 'n' where each bit represents a specific credit risk factor, develop a function that identifies and activates the leftmost inactive risk factor (represented by 0) by changing it to 1. This modification helps in stress-testing how a customer's creditworthiness would be affected if an additional risk factor becomes active, while maintaining the status of all other existing risk factors.
    

    
def set_left_most_unset_bit(n):
    """
    In a credit risk assessment system, given a binary risk profile 'n' where each bit represents a specific credit risk factor, develop a function that identifies and activates the leftmost inactive risk factor (represented by 0) by changing it to 1. This modification helps in stress-testing how a customer's creditworthiness would be affected if an additional risk factor becomes active, while maintaining the status of all other existing risk factors.
    

    """
def set_left_most_unset_bit(n):
    """
    In a credit risk assessment system, given a binary risk profile 'n' where each bit represents a specific credit risk factor, develop a function that identifies and activates the leftmost inactive risk factor (represented by 0) by changing it to 1. This modification helps in stress-testing how a customer's creditworthiness would be affected if an additional risk factor becomes active, while maintaining the status of all other existing risk factors.
    

    """
    if not n & n + 1:
        return n
    (pos, temp, count) = (0, n, 0)
    while temp:
        if not temp & 1:
            pos = count
        count += 1
        temp >>= 1
    return n | 1 << pos