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Data mining in financial crime detection

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  1. Introduction
  2. Understanding financial crimes
  3. Types of financial crimes
    1. Insurance crimes
    2. Bank fraud
    3. Online credit card fraud
    4. Loan default
  4. Conclusion
  5. References

In this paper, we have discussed different financial crimes that are seen today i.e credit card fraud, card not present fraud, Loan default, Bank Fraud, Money Laundering, Insurance crime etc. Then we have discussed how data mining becomes helpful for detection of these types of financial crimes. Today Industry is facing huge losses due to these types of financial crimes, so it would be able to find financial crime through data mining techniques and remove it then it can be great benefit to the industry. In this paper we have suggested a two-tier architecture model for financial crime detection. In the first stage the financial transaction is verified against the rule-based system and is given risk score by the system. These rules contain the human insight. And then this transaction is passed to second stage of data mining technique, which will learn from the past experience of fraudulent transactions and then decide about the current transaction.

[...] As with other financial crimes, detection must occur before any loss is sustained. There are lead indicators like the "manipulation of credit" described above and in the lack of references, high associations of matching attributes, and dubious acceptance criteria. The critical factors for detecting all of these financial fraud crimes is knowing the behavior of credit, bank, and loan accounts and developing an understanding of the categories of customers. Data mining can be used to spot outliers or account usages that are normal and out of character. [...]

[...] Link analysis may be used to look for a ring of fraudulent providers, and, of course, data mining tools, such as neural networks, may be used for training and detection if samples of fraud cases exist. The net amount of the claim may be too MISCODING In processing claims, insurance companies rely mainly on diagnostic and procedural codes recorded on the claim forms. Their computers are programmed to detect services that are not covered. Most insurance policies exclude nonstandard or experimental methods. [...]

[...] The absence of certain data, such as activity in a credit report, is also signals of possible identify theft and fraud LOAN DEFAULT This type of financial crime involves the manipulation and inflation of an individual credit rating prior to performing a "sting," leading to a loan default and a loss for the financial service provider This financial crime is done by creating a false identity and it takes time to develop. Once an account has been created with a stolen or false identity, the marketing initiatives employed by the bank or credit-card issuer assist the perpetrator in building a portfolio of credit-cards, loan accounts, and a viable credit-rating and history?before defaulting on them. [...]

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