
    Design a fraud detection algorithm that determines the number of possible transaction sequences where n consecutive banking activities contain exactly m instances where a transaction amount is greater than the previous one, helping identify unusual spending patterns. The algorithm should analyze all possible permutations of the transaction sequence to calculate how many ways these specific patterns can occur, which is crucial for establishing baseline behavior patterns in fraud detection systems.
    

    
def eulerian_num(n, m):
    """
    Design a fraud detection algorithm that determines the number of possible transaction sequences where n consecutive banking activities contain exactly m instances where a transaction amount is greater than the previous one, helping identify unusual spending patterns. The algorithm should analyze all possible permutations of the transaction sequence to calculate how many ways these specific patterns can occur, which is crucial for establishing baseline behavior patterns in fraud detection systems.
    

    """
def eulerian_num(n, m):
    """
    Design a fraud detection algorithm that determines the number of possible transaction sequences where n consecutive banking activities contain exactly m instances where a transaction amount is greater than the previous one, helping identify unusual spending patterns. The algorithm should analyze all possible permutations of the transaction sequence to calculate how many ways these specific patterns can occur, which is crucial for establishing baseline behavior patterns in fraud detection systems.
    

    """
    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)