Financial Fraud Detection

India is becoming digitally advanced nowadays. Peoples are now shifting from cash mode to electronic payment mode like a credit card, mobile payment, net banking, etc. Hence, financial fraud is rapidly increasing day by day. For the protection from these kinds of financial frauds by developing their fraud detection system (FDS). The research paper explains what financial fraud actually is. This research paper also deals with the type of financial frauds. The researcher also analyses the various methods used by the companies to protect their clients from these financial frauds. The researcher then concludes the paper by citing the various challenges faced in the implementation of these techniques of financial fraud detection.

1.     Introduction:

Our everyday life and financial institutions are adversely affected by the financial frauds. These financial frauds diminish the confidence of these financial institutions and also reduce their savings. Financial institutions used lots of methods to prevent these types of financial frauds. However, fraudsters are very smart and they are able to break these techniques. After the lots of efforts done by the Government, financial institutions. These financial frauds are rapidly increasing in India. This paper deals with various financial fraud detection techniques such as Sampling, Ad-hoc, Benford’s Law, etc. are adopted by the financial institutions to protect themselves and their clients from these financial frauds. The rest paper is organized as section 2 of the paper contains the definition of financial fraud. Section 3 contains types of financial frauds. Section 4 and 5 contains benefits and methods of financial frauds detection respectively. At last, the researcher concludes the paper by analyzing the various challenges faced by the fraud detection techniques.

2.     Definition of Financial Frauds:

According to the Association of Certified Fraud Examiners (ACFE) ,

“Fraud includes any intentional or deliberate act of depriving another person from property or money by cunning, deception or other unfair acts.[1]

3.     Types of Financial Frauds:

3.1  Credit Card Fraud:

These types of frauds make unauthorized use of personal credit card to perform the transaction without the knowledge and consent of credit card holder. These type of frauds can be done when credit card is lost or stolen. This type of fraud can also be done by taking information from the credit card holder in several ways like phishing.[2] This type of fraud is further classified into two categories:

  1. Application fraud where fraudsters by presenting the false information of any people and went to the issuing company and obtain the new card.
  2. Behavioral fraud which are further classified into mail theft, stolen or lost card and counterfeiting of cards.[3]

3.2  Mortgage Fraud:

This type of financial fraud has been done to misrepresent the value of property and obtain the loan on that property. This can be done by manipulating the manipulating mortgage documents.[4]

3.3  Money Laundering:

It is a method where criminals convert their black money earned from illegal methods and illegal businesses into valid income and valid business. This type of fraud is extremely undesirable.

3.4  Financial Statement Fraud:

The financial statement depicts the financial status of any company with following objectives:

  1. To make the business more profitable one.
  2. To make improvement in performance of actions of company.
  3. These statements reduce the tax obligations upon the company.

3.5  Securities and Commodities fraud:

Securities and commodities frauds are similar in nature. Under this type of fraud, fraudsters convinced the party to invest their money in their company by providing fake information. This type of fraud includes Pyramid schemes[5], Ponzi schemes[6], Hedge fund fraud[7], foreign exchange fraud and embezzlement.[8]

3.6  Insurance fraud:

This type of fraud can be easily committed by consumers, agents, brokers, insurance company employees, healthcare providers and many others in the form of insurance process like application, eligibility, rating, billing and claims.

4.     Benefits of Fraud detection methods:

  1. These methods reduce the fraudulent activities.
  2. These methods reduce the losses incurred by the company because of financial frauds. 
  3. These methods help to ruled out high risk vulnerable employees to fraud.
  4. These techniques provides for organizational tools.
  5. By adopting these techniques, the shareholders started trusting the organization.

5.     Methods of Financial Fraud Detection:

There are 5 methods of Financial Fraud detection:

5.1  Sampling:

Sampling is necessary for some process of fraud detection. When there is involvement of large number of data population, sampling method of fraud detection more effective. As this technique only consider few data population, the fraud detection can not be controlled completely. As fraud detection does not occur randomly, the company have to check each and every transactions making this method a lengthy one.

5.2  Ad-hoc:

In this method, fraud is detected through hypothesis. The organisation tests all the transactions and search the possibility of any fraud and if any fraud is occuring, organisation has right to have investigation on that fraud.

5.3  Repetitive or Continous Analysis:

Repetitive or Continous analysis includes creation and running of the cript against the large volume of data which is useful in detection of financial fraud as they occur over the period of time. To go through all the transactions and getting the periodic notifications of frauds, company runs scripts regulary. The efficiency and accuracy of company’s fraud detection process is increased by this message.

5.4  Analytics Techniques:

When fraud is big and not a normal one then this technique is used. Analytics techniques are further categorised into 3 steps:

  1. Firstly calculate the statistical parameters to search the values which exceeds standard derivation average.
  2. Now after looking the values, search for anomalies which are the indicator of fraud. 
  3. Now last step is classification of data and grouping of data.

5.5  Benford’s Law:

Benford’s law is an indicator of frauds. By using Benford’s law, company tests certain numbers and identify them which appears most frequently than normal and they are the subjects of frauds.

5.6  Other fraud detection techniques:

  1. Data Matching: This technique is used to search for the exact similar data with other data.
  2. Sounds like: This method is used to identify variations invalid company employee’s name.
  3. Duplicates: This is a method frequently used by business organizations for the detection of fraud and errors in business transactions.

6.     Conclusion:

This research paper firstly explain the definition of financial fraud and then analyses the different types of financial frauds occurring in our societies and then this paper deals with the various methods company and organization are using for detection of frauds and protecting their clients from such frauds.

Inspite of these methods, companies are still facing some challenges in prevention of financial frauds. Following are some challenges:

  1. Typical classification problems:

Computational insight and information mining-based money related misrepresentation identification are dependent upon similar issues as other characterization issues

  1. Fraud types and detection methods:

Fraud types is an assorted field and there has been a huge lopsidedness in both fraud types and detection techniques considered: some have been concentrated widely while others.

  1. Privacy considerations:

Financial fraud is a sensitive topic and stakeholders are reluctant to share information on the subject. This has led to experimental issues such as undersampling.

  1.   Computational performance. 

As a high-cost problem, it is desirable for financial fraud to be detected immediately. Very little research has been conducted on the computational performance of fraud detection methods to be used in real-time situations. 

  •   Evolving problem:

 Fraudsters are continually modifying their techniques to remain undetected, which means such detection methods are required to be able to constantly adapt to new fraud techniques.

References:

[1] A. Abdallah, M. A. Maarof, and A. Zainal, Fraud detection system: a survey, Journal of Network and Computer Applications 68 (2016), 90–113. 

[2] L. Anan, R. Hayden, K. Joshi, M.-C. Nadeau, and J. Steitz, Fraud management: recovering value through next-generation solutions, McKinsey & Company, McKinsey on Payments, Volume 11, Number 27, pp. 30–36, June 2018. 

[3] BCBS, Principles for the sound management of operational risk, Bank for International Settlements, June 2011. 

[4] BCBS, The Basel framework, Bank for International Settlements, 2020. 

[5] D. Broeders and J. Prenio, Innovative technology in financial supervision (suptech) { the experience of early users, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 9, July 2018. 

[6] R. Coelho, M. De Simoni, and J. Prenio, Suptech applications for anti-money laundering, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 18, August 2019. 

[1] A. Abdallah, M. A. Maarof, and A. Zainal, Fraud detection system: a survey, Journal of Network and Computer Applications 68 (2016), 90–113. 

[2] L. Anan, R. Hayden, K. Joshi, M.-C. Nadeau, and J. Steitz, Fraud management: recovering value through next-generation solutions, McKinsey & Company, McKinsey on Payments, Volume 11, Number 27, pp. 30–36, June 2018. 

[3] BCBS, Principles for the sound management of operational risk, Bank for International Settlements, June 2011. 

[4] BCBS, The Basel framework, Bank for International Settlements, 2020. 

[5] D. Broeders and J. Prenio, Innovative technology in financial supervision (suptech) { the experience of early users, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 9, July 2018. 

[6] R. Coelho, M. De Simoni, and J. Prenio, Suptech applications for anti-money laundering, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 18, August 2019. 

Frequently Asked Questions

Q.1  How do you identify financial frauds ?

Ans: Cash flow analysis is a specific application of horizontal analysis that helps highlight possible areas of fraudulent accounting. Since the cash flow statement most directly reports how money flows into and out of the company, cash flow analysis often helps detect misstatements.

Q.2 what is fraud detection in big data?

Ans: Big data fraud detection is a cutting-edge way to use consumer trends to detect and prevent suspicious activity. Even subtle differences in a consumer’s purchases or credit activity can be automatically analyzed and flagged as potential fraud

Q.3 What is a fraud policy?

Ans: A fraud policy is a “thou shalt not steal” document that allows companies to communicate with their employees on the reporting procedures they should follow if they suspect that fraud is going on. Importantly, the policy should be written and signed on an annual basis by all employees, from the top down. It sets the tone by specifying that fraud will not be tolerated at any level of the workforce and lays out the consequences to employees

Q.4  Is it costly to implement an effective fraud policy?

Ans: No, and it’s money well spent. Some of the anti-fraud recommendations have a dollar tag associated with them. Others do not, since they are nothing more than changes to policies that are already in place. Setting up a “whistle-blower” program or a hotline is relatively inexpensive. There might be fees associated with steps like changing where customer deposits are sent. It might be advisable for small business owners to have their company’s bank statements sent to their houses. That way, they can personally monitor every check or wire transfer to make sure it is appropriate. About 85 percent of all fraud that occurs is done through checkbooks and cash. So, simple mechanisms like reconciling every bank statement or setting up a physical lockbox for cash can deter fraud.


[1]http://www.acfe.com/uploadedfiles/acfewebsite/content/documents/rttn-2010.pdf.

[2] Phishing is a cybercrime in which a target or targets are contacted by email, telephone or text message by someone posing as a legitimate institution to lure individuals into providing sensitive data such as personally identifiable information, banking and credit card details, and passwords.

[3] S.Bhattacharyya, S.Jha, K.Tharakunnel, J.C. Westland, Data mining for credit card fraud: A comparative study, Elsevier, Decision Support Systems, Volume 50, Issue 3, p602-613(2011)

[4] Ngai E, Hu Y, Wong Y, Chen Y, and Sun X The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature Decision Support Systems Volume 50, Issue 3, p559 569 (2011)

[5] A pyramid scheme is a sketchy and unsustainable business model, where a few top-level members recruit newer members, who pay upfront costs up the chain, to those who enrolled them

[6] A Ponzi scheme is a fraudulent investing scam promising high rates of return with little risk to investors.

[7] Hedge funds are private investment partnerships. There are minimal regulations associated with hedge funds

[8] Embezzlement is the act of withholding assets for the purpose of conversion (theft) of such assets, by one or more persons to whom the assets were entrusted, either to be held or to be used for specific purposes.

India is becoming digitally advanced nowadays. Peoples are now shifting from cash mode to electronic payment mode like credit card, mobile payment, net banking, etc. Hence, financial fraud is rapidly increasing day by day. For the protection from these kinds of financial frauds by developing their fraud detection system (FDS). The research paper explains what the financial fraud actually is. This research paper also deals with the type of financial frauds. The researcher also analyses the various methods used by the companies to protect their clients from these financial frauds. The researcher then concludes the paper by citing the various challenges faced in the implementation of these techniques of financial fraud detection.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1.     Introduction:

Our everyday life and financial institutions are adversely affected by the financial frauds. These financial frauds diminish the confidence of these financial institutions and also reduce their savings. Financial institutions used lots of methods to prevent these types of financial frauds. However, fraudsters are very smart and they are able to break these techniques. After the lots of efforts done by the Government, financial institutions. These financial frauds are rapidly increasing in India. This paper deals with various financial fraud detection techniques such as Sampling, Ad-hoc, Benford’s Law, etc. are adopted by the financial institutions to protect themselves and their clients from these financial frauds. The rest paper is organized as section 2 of the paper contains the definition of financial fraud. Section 3 contains types of financial frauds. Section 4 and 5 contains benefits and methods of financial frauds detection respectively. At last, the researcher concludes the paper by analyzing the various challenges faced by the fraud detection techniques.

2.     Definition of Financial Frauds:

According to the Association of Certified Fraud Examiners (ACFE) ,

“Fraud includes any intentional or deliberate act of depriving another person from property or money by cunning, deception or other unfair acts.[1]

3.     Types of Financial Frauds:

3.1  Credit Card Fraud:

These types of frauds make unauthorized use of personal credit card to perform the transaction without the knowledge and consent of credit card holder. These type of frauds can be done when credit card is lost or stolen. This type of fraud can also be done by taking information from the credit card holder in several ways like phishing.[2] This type of fraud is further classified into two categories:

  1. Application fraud where fraudsters by presenting the false information of any people and went to the issuing company and obtain the new card.
  2. Behavioral fraud which are further classified into mail theft, stolen or lost card and counterfeiting of cards.[3]

3.2  Mortgage Fraud:

This type of financial fraud has been done to misrepresent the value of property and obtain the loan on that property. This can be done by manipulating the manipulating mortgage documents.[4]

3.3  Money Laundering:

It is a method where criminals convert their black money earned from illegal methods and illegal businesses into valid income and valid business. This type of fraud is extremely undesirable.

3.4  Financial Statement Fraud:

The financial statement depicts the financial status of any company with following objectives:

  1. To make the business more profitable one.
  2. To make improvement in performance of actions of company.
  3. These statements reduce the tax obligations upon the company.

3.5  Securities and Commodities fraud:

Securities and commodities frauds are similar in nature. Under this type of fraud, fraudsters convinced the party to invest their money in their company by providing fake information. This type of fraud includes Pyramid schemes[5], Ponzi schemes[6], Hedge fund fraud[7], foreign exchange fraud and embezzlement.[8]

3.6  Insurance fraud:

This type of fraud can be easily committed by consumers, agents, brokers, insurance company employees, healthcare providers and many others in the form of insurance process like application, eligibility, rating, billing and claims.

4.     Benefits of Fraud detection methods:

  1. These methods reduce the fraudulent activities.
  2. These methods reduce the losses incurred by the company because of financial frauds. 
  3. These methods help to ruled out high risk vulnerable employees to fraud.
  4. These techniques provides for organizational tools.
  5. By adopting these techniques, the shareholders started trusting the organization.

5.     Methods of Financial Fraud Detection:

There are 5 methods of Financial Fraud detection:

5.1  Sampling:

Sampling is necessary for some process of fraud detection. When there is involvement of large number of data population, sampling method of fraud detection more effective. As this technique only consider few data population, the fraud detection can not be controlled completely. As fraud detection does not occur randomly, the company have to check each and every transactions making this method a lengthy one.

5.2  Ad-hoc:

In this method, fraud is detected through hypothesis. The organisation tests all the transactions and search the possibility of any fraud and if any fraud is occuring, organisation has right to have investigation on that fraud.

5.3  Repetitive or Continous Analysis:

Repetitive or Continous analysis includes creation and running of the cript against the large volume of data which is useful in detection of financial fraud as they occur over the period of time. To go through all the transactions and getting the periodic notifications of frauds, company runs scripts regulary. The efficiency and accuracy of company’s fraud detection process is increased by this message.

5.4  Analytics Techniques:

When fraud is big and not a normal one then this technique is used. Analytics techniques are further categorised into 3 steps:

  1. Firstly calculate the statistical parameters to search the values which exceeds standard derivation average.
  2. Now after looking the values, search for anomalies which are the indicator of fraud. 
  3. Now last step is classification of data and grouping of data.

5.5  Benford’s Law:

Benford’s law is an indicator of frauds. By using Benford’s law, company tests certain numbers and identify them which appears most frequently than normal and they are the subjects of frauds.

5.6  Other fraud detection techniques:

  1. Data Matching:

This technique is used to search for the exactly similar data with another data.

  1. Sounds like:

This method is used to identify variations in valid company employee’s name.

  1. Duplicates:

This is a method frequently used by the business organizations for the detection of fraud and errors in business transactions.

6.     Conclusion:

This research paper firstly explain the definition of financial fraud and then analyses the different types of financial frauds occurring in our societies and then this paper deals with the various methods company and organization are using for detection of frauds and protecting their clients from such frauds.

Inspite of these methods, companies are still facing some challenges in prevention of financial frauds. Following are some challenges:

  1. Typical classification problems:

Computational insight and information mining-based money related misrepresentation identification are dependent upon similar issues as other characterization issues

  1. Fraud types and detection methods:

Fraud types is an assorted field and there has been a huge lopsidedness in both fraud types and detection techniques considered: some have been concentrated widely while others.

  1. Privacy considerations:

Financial fraud is a sensitive topic and stakeholders are reluctant to share information on the subject. This has led to experimental issues such as undersampling.

  1.   Computational performance. 

As a high-cost problem, it is desirable for financial fraud to be detected immediately. Very little research has been conducted on the computational performance of fraud detection methods to be used in real-time situations. 

  •   Evolving problem:

 Fraudsters are continually modifying their techniques to remain undetected, which means such detection methods are required to be able to constantly adapt to new fraud techniques.

References:

[1] A. Abdallah, M. A. Maarof, and A. Zainal, Fraud detection system: a survey, Journal of Network and Computer Applications 68 (2016), 90–113. 

[2] L. Anan, R. Hayden, K. Joshi, M.-C. Nadeau, and J. Steitz, Fraud management: recovering value through next-generation solutions, McKinsey & Company, McKinsey on Payments, Volume 11, Number 27, pp. 30–36, June 2018. 

[3] BCBS, Principles for the sound management of operational risk, Bank for International Settlements, June 2011. 

[4] BCBS, The Basel framework, Bank for International Settlements, 2020. 

[5] D. Broeders and J. Prenio, Innovative technology in financial supervision (suptech) { the experience of early users, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 9, July 2018. 

[6] R. Coelho, M. De Simoni, and J. Prenio, Suptech applications for anti-money laundering, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 18, August 2019. 

[1] A. Abdallah, M. A. Maarof, and A. Zainal, Fraud detection system: a survey, Journal of Network and Computer Applications 68 (2016), 90–113. 

[2] L. Anan, R. Hayden, K. Joshi, M.-C. Nadeau, and J. Steitz, Fraud management: recovering value through next-generation solutions, McKinsey & Company, McKinsey on Payments, Volume 11, Number 27, pp. 30–36, June 2018. 

[3] BCBS, Principles for the sound management of operational risk, Bank for International Settlements, June 2011. 

[4] BCBS, The Basel framework, Bank for International Settlements, 2020. 

[5] D. Broeders and J. Prenio, Innovative technology in financial supervision (suptech) { the experience of early users, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 9, July 2018. 

[6] R. Coelho, M. De Simoni, and J. Prenio, Suptech applications for anti-money laundering, Bank for International Settlements, Financial Stability Institute, FSI Insights on Policy Implementation No. 18, August 2019. 

Frequently Asked Questions

Q.1  How do you identify financial frauds ?

Ans: Cash flow analysis is a specific application of horizontal analysis that helps highlight possible areas of fraudulent accounting. Since the cash flow statement most directly reports how money flows into and out of the company, cash flow analysis often helps detect misstatements.

Q.2 what is fraud detection in big data?

Ans: Big data fraud detection is a cutting-edge way to use consumer trends to detect and prevent suspicious activity. Even subtle differences in a consumer’s purchases or credit activity can be automatically analyzed and flagged as potential fraud

Q.3 What is a fraud policy?

Ans: A fraud policy is a “thou shalt not steal” document that allows companies to communicate with their employees on the reporting procedures they should follow if they suspect that fraud is going on. Importantly, the policy should be written and signed on an annual basis by all employees, from the top down. It sets the tone by specifying that fraud will not be tolerated at any level of the workforce and lays out the consequences to employees

Q.4  Is it costly to implement an effective fraud policy?

Ans: No, and it’s money well spent. Some of the anti-fraud recommendations have a dollar tag associated with them. Others do not, since they are nothing more than changes to policies that are already in place. Setting up a “whistle-blower” program or a hotline is relatively inexpensive. There might be fees associated with steps like changing where customer deposits are sent. It might be advisable for small business owners to have their company’s bank statements sent to their houses. That way, they can personally monitor every check or wire transfer to make sure it is appropriate. About 85 percent of all fraud that occurs is done through checkbooks and cash. So, simple mechanisms like reconciling every bank statement or setting up a physical lockbox for cash can deter fraud.


[1]http://www.acfe.com/uploadedfiles/acfewebsite/content/documents/rttn-2010.pdf.

[2] Phishing is a cybercrime in which a target or targets are contacted by email, telephone or text message by someone posing as a legitimate institution to lure individuals into providing sensitive data such as personally identifiable information, banking and credit card details, and passwords.

[3] S.Bhattacharyya, S.Jha, K.Tharakunnel, J.C. Westland, Data mining for credit card fraud: A comparative study, Elsevier, Decision Support Systems, Volume 50, Issue 3, p602-613(2011)

[4] Ngai E, Hu Y, Wong Y, Chen Y, and Sun X The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature Decision Support Systems Volume 50, Issue 3, p559 569 (2011)

[5] A pyramid scheme is a sketchy and unsustainable business model, where a few top-level members recruit newer members, who pay upfront costs up the chain, to those who enrolled them

[6] A Ponzi scheme is a fraudulent investing scam promising high rates of return with little risk to investors.

[7] Hedge funds are private investment partnerships. There are minimal regulations associated with hedge funds

[8] Embezzlement is the act of withholding assets for the purpose of conversion (theft) of such assets, by one or more persons to whom the assets were entrusted, either to be held or to be used for specific purposes.

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