
    Design a fraud detection algorithm that determines the number of ways n distinct transaction patterns can be arranged such that exactly m patterns have a higher risk score than their subsequent pattern in the sequence. This calculation helps identify suspicious transaction orderings and potential fraud patterns within the bank's real-time monitoring system.
    

    
def eulerian_num(n, m):
    """
    Design a fraud detection algorithm that determines the number of ways n distinct transaction patterns can be arranged such that exactly m patterns have a higher risk score than their subsequent pattern in the sequence. This calculation helps identify suspicious transaction orderings and potential fraud patterns within the bank's real-time monitoring system.
    

    """
def eulerian_num(n, m):
    """
    Design a fraud detection algorithm that determines the number of ways n distinct transaction patterns can be arranged such that exactly m patterns have a higher risk score than their subsequent pattern in the sequence. This calculation helps identify suspicious transaction orderings and potential fraud patterns within the bank's real-time monitoring system.
    

    """
    if m >= n or n == 0:
        return 0
    if m == 0:
        return 1
    return (n - m) * eulerian_num(n - 1, m - 1) + (m + 1) * eulerian_num(n - 1, m)