
    Given a customer's transaction history where normal transactions are marked as '0' and suspicious ones as '1', find the time window that shows the largest disparity between normal and suspicious transaction counts. This analysis will help identify periods of concentrated unusual activity that may indicate potential fraud.
    

    
def find_length(string):
    """
    Given a customer's transaction history where normal transactions are marked as '0' and suspicious ones as '1', find the time window that shows the largest disparity between normal and suspicious transaction counts. This analysis will help identify periods of concentrated unusual activity that may indicate potential fraud.
    

    """
def find_length(string):
    """
    Given a customer's transaction history where normal transactions are marked as '0' and suspicious ones as '1', find the time window that shows the largest disparity between normal and suspicious transaction counts. This analysis will help identify periods of concentrated unusual activity that may indicate potential fraud.
    

    """
    n = len(string)
    current_sum = 0
    max_sum = 0
    for i in range(n):
        current_sum += 1 if string[i] == '0' else -1
        if current_sum < 0:
            current_sum = 0
        max_sum = max(current_sum, max_sum)
    return max_sum if max_sum else 0