• [ Pobierz caÅ‚ość w formacie PDF ]

    transactions for review prior to processing.
    " Examples:
    o If the Amount is over 500 and the Shipping Type is
     express to a shipping address that does not match the
    billing address, then review the order before shipping.
    o If more than 2 DVD Players were ordered, if the Shipping
    Country is Romania, and the Shipping Type is  express ,
    then review the order before shipping.
    The benefit of Rules is that they allow the merchant to apply expert
    knowledge relevant to the business. Rules are customisable and can be
    modified as market conditions and fraud trends change. Rules make it easy
    to determine why a transaction is flagged. The main drawback of rules is that
    they require constant updating and monitoring to ensure that they are
    effective. Rules are only as good as the people who build them and they are,
    therefore, not effective at catching subtle patterns that may not be obvious to
    the merchant (Scutt, 2001:20).
    Use Any Boolean Expression Use Any Field in the Database
    o = equal to o Billing Address, City, Province,
    o != not equal to Postal Code
    o
    o
    o > greater than o Credit Card Number
    o >= greater than/equal to o Current Time, Day, Month, Year
    o Item Count
    o Quantity of a single item
    Use  * as a wildcard
    o Total Cost of Order
    o IP Address
    Combine statements with
    o Item Serial Number
    o AND
    (Scutt, 2001:19).
    o OR
    Table 7: Building Rules / Exceptions
    3.2.3.8 Statistical Models
    Statistical models, like a risk scoring facility are essentially  learn by example
    tools that test the transaction attributes of an incoming Internet order with
    known fraudulent activity listed in the statistical model database. The output
    of a statistical model is typically a risk score (e.g. 1-100). Statistical models
    leverage historical and forensic data in order to catch new fraud attempts.
    The risk score is determined by evaluating numerous factors simultaneously.
    Subtle patterns that would normally be overlooked by the merchant will be
    highlighted by the statistical model.
    Unfortunately, most merchants do not have the required ample, accurate, and
    cleansed historical data required by a statistical model to provide accurate
    34
    results. Since multiple factors contribute to the risk score, it is sometimes
    difficult to interpret the score (Scutt, 2001:22).
    35
    3.2.3.9 Hybrid Solution (Arsenal Approach)
    A hybrid solution combines the attributes of the above strategies, for example:
    " Rules to enforce business rules or weed out bluntly fraudulent
    transactions
    " Real-time Authorisation to validate credit card number
    " Statistical Model to evaluate the overall risk
    " Rules to determine whether to Accept, Reject or Review the order
    (Scutt, 2001:24).
    " The overall return on investment (ROI) depends on many factors:
    o Overall fraud rates
    o Total volume of transactions
    o Margin on transactions
    o Cost to review order
    o In-house risk management expertise.
    " A multi-tool (hybrid) solution typically leads to the highest ROI because
    better screening reduces the volume of orders to be reviewed (Scutt,
    2001:24).
    E-business was hailed as the great equaliser a few years ago as it enabled
    small merchants to compete on an equal footing with large multi-nationals
    selling to a potential international client base. With regard to e-fraud and the
    prevention of e-fraud the statistics and numbers above have shown that it is
    becoming very difficult for smaller e-merchants to survive and remain
    profitable if they cannot afford to subscribe to available fraud prevention
    services that would allow more accurate screening of transactions.
    36
    4 THE FUNDAMENTALS OF PREDICTIVE FORENSIC PROFILING
    4.1 THE PARETO PRINCIPLE
    It is nearly a century since Vilfredo Pareto (1848 - 1923) defined what became
    known as the Pareto principle (cf. Pareto 1906). Commonly known as the
    80/20 rule, the Pareto principle describes the distribution of wealth in that, in
    any population that contributes to a common effect, relatively few of the
    contributors account for the bulk of the effect.
    JM Juran was the first person to generalise the Pareto principle and apply it to
    all areas of business as a means of focusing on the real problems or issues.
    Juran, the father of quality control, coined the phrase 'the vital few and the
    trivial many' that is regularly used to describe the Pareto principle. The Pareto
    principle is generally used in conjunction with the Lorenz curve (and the Gini
    Index) as a graphical representation of the actual deviation from an equal
    distribution situation (cf. Lorenz, 1905.) [ Pobierz całość w formacie PDF ]

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