Master of Science in Economic Crime Forensics with a Concentration in Data Science Online

Gain specialized, data-focused expertise in the detection, investigation and prevention of economic crime. This unique master’s degree program is one of the few of its kind in the nation.

Apply by: 5/8/23
Start classes: 5/22/23
Request Info Request Info Apply Now

Program Overview

Explore the M.S. in Economic Crime Forensics – Data Science online program

Total Tuition: $27,450
Program Duration: As few as 24 Months
Credit Hours: 30

The growth of big data and its universal value across all business functions has led to a proliferation of hard-to-detect economic crime in many organizations. Learn real-world solutions and advanced crime-fighting technologies in the online Master of Science in Economic Crime Forensics with a Concentration in Data Science from La Salle University.

This rarely offered, 100 percent online program prepares you for advanced career opportunities with a robust understanding of network communication, internet fraud, digital forensics and network security. In the La Salle University economic crime forensics program, you will explore the various aspects of cybersecurity, including cyber intrusions, espionage and warfare. Learn more about data analytics, data mining, database management and artificial intelligence as you sharpen your skills in SQL and R.

Graduates of the online M.S. in Economic Crime Forensics – Data Science will learn how to:

  • Propose business law standards, standards of ethics and professional codes of conduct related to corporate leadership
  • Evaluate and support accounting and auditing concepts related to the causation of corporate economic crime
  • Develop standards of conduct relative to litigation services, including conflicts of interest and background consideration
  • Develop managerial and communication skills to measure and support fraud deterrence
  • Propose business law standards, standards of ethics and professional codes of conduct related to corporate leadership
  • Evaluate and support accounting and auditing concepts related to the causation of corporate economic crime
  • Develop standards of conduct relative to litigation services, including conflicts of interest and background consideration
  • Develop managerial and communication skills to measure and support fraud deterrence

Upon completion of the online M.S. in Economic Crime Forensics – Data Science program, you will be prepared for a wide range of fraud investigative roles, including:

  • Fraud Examiner
  • Fraud Investigator
  • Forensics Investigator
  • Fraud Examiner
  • Fraud Investigator
  • Forensics Investigator

Online technology programs also available:

La Salle University offers a variety of specialized technology programs. Check out all of our technology online programs.

Total Tuition: $27,450
Program Duration: As few as 24 Months
Credit Hours: 30
Need More Information?

Call 844-466-5587

Call 844-466-5587

Tuition

Benefit from pay-by-the-course tuition

Our M.S. in Economic Crime Forensics – Data Science online program offers affordable, pay-by-the-course tuition which is the same for in-state and out-of-state students. All program and course fees are included in the total tuition cost.

Tuition breakdown:

Total Tuition: $27,450
Per Credit Hour: $915

Tuition breakdown:

Total Tuition: $27,450
Per Credit Hour: $915

Calendar

Choose from multiple start dates and finish faster

La Salle University online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.

Now enrolling:

Next Apply Date: 5/8/23
Next Class Start Date: 5/22/23
TermStart DateApp DeadlineDocument DeadlineRegistration DeadlineTuition DeadlineClass End DateTerm Length
Summer 15/22/235/8/235/12/235/17/235/18/237/16/238 weeks
Fall 18/28/238/14/238/18/238/23/238/24/2310/22/238 weeks
Fall 210/23/2310/9/2310/13/2310/18/2310/19/2312/17/238 weeks

Now enrolling:

Next Apply Date: 5/8/23
Next Class Start Date: 5/22/23

Have questions or need more information about our online programs?

Ready to take the rewarding path toward earning your degree online?

Admissions

Apply easily to the M.S. in Economic Crime Forensics – Data Science online

Applications for the M.S. in Economic Crime Forensics – Data Science are evaluated on a holistic basis. The Admissions Committee takes into account interest, aptitude and potential for achievement in graduate studies. The requirements include:

Admission Requirements:

  • Bachelor’s degree from an accredited institution
  • Minimum 3.0 GPA
  • No GMAT required

Prior to evaluation by the Admissions Committee, applicants must submit the following:

  • Transcript(s) from the college/university where you earned your bachelor’s degree and, if applicable, master’s degree. You will be notified if you need to submit additional transcripts for advising purposes.
  • Minimum 3.0 GPA
  • No GMAT/GRE required
  • A current professional resume
  • Provide a personal statement (about 500 words in length) explaining why you are interested in this program, your qualifications and how this program will assist with your professional goals

Documentation can be sent via email to [email protected]. If you need to submit official documents by mail, send them to:

La Salle University
Office of Adult Enrollment
Box 112
1900 West Olney Avenue
Philadelphia, PA 19141

Have a question? Call us at 844-466-5587.

Courses

Preview the diverse courses in the M.S. in Economic Crime Forensics – Data Science online program

For the M.S. in Economic Crime Forensics – Data Science online, the curriculum is comprised of five core courses, four specialty courses and the integrative capstone course.

Duration: 8 weeks
Credit Hours: 3
The course provides an overview of the legal systems and expertise required for fraud risk professionals. The course enables participants to deepen their knowledge of the U.S. legal system by acquiring a broader understanding of processes and procedures that focus on fraud investigation, prosecution, and civil remedies. The course covers knowledge of law enforcement agencies, federal rules and regulations and evidence management, and expert testimony.
Duration: 8 weeks
Credit Hours: 3
Financial statement fraud involves intentional misstatements or omissions of financial statement amounts or disclosures to deceive users of the statements. This topic, commonly known as “cooking the books,” will introduce students to management's motives and pressures to achieve desired financial results as opposed to true economic financial results. This course will enable students to both understand and detect the creative accounting methods management employs to “cook the books,” along with related fraud prevention strategies.
Duration: 8 weeks
Credit Hours: 3
Occupational fraud and abuse is described as the use of one’s occupation for personal enrichment through the deliberate misuse or misapplication of one’s employing organization’s resources or assets. Through the use of real-life case examples, this course will focus on the types of persons most likely to perpetrate occupational fraud, the conditions under which fraud might be committed, and the specific schemes used to defraud organizations of amounts ranging from hundreds to millions of dollars.
Duration: 8 weeks
Credit Hours: 3
Computers have made organizations easier to run. All accounting information, inventory records, customer data, and intellectual property that an organization possesses is contained somewhere in an electronic file. As such, these electronic files are vulnerable to attacks from both employees and outsiders from around the world. This course will provide the student with an understanding of how computer fraud and manipulation is accomplished and what security measures should be instituted to prevent it.
Duration: 8 weeks
Credit Hours: 3
The opportunity to commit and conceal fraud exists only when there are assets susceptible to misappropriation and a lack of internal controls to prevent or detect fraud. This course will focus on the high-risk fraud environments wherein assets are more vulnerable to misappropriation and fraud because of either a lack of, or non-functioning of, internal controls. The study of various fraud investigative methods and the process for communicating an expert report will be an essential part of this course.
Duration: 8 weeks
Credit Hours: 3
The capstone project is an opportunity to pursue an independent learning experience focused on a specific aspect of economic crime forensics based on the student interest. The capstone is intended to extend students beyond the coursework and cases to apply knowledge in ways that are relevant to their professional goals. Students will work on a research project or in an experiential learning environment. Each student will be required to present his/her capstone both as an oral presentation and a summary written document.
Choose 4 of the following:
Duration: 8 weeks
Credit Hours: 3
This course entails analysis and evaluation of database designs in relation to the strategic mission of the project. Topics include database systems, database architectures, and data-definition and data-manipulation languages. Also included are logical and physical database design, database models (e.g., entity-relationship, relational), normalization, integrity, query languages including SQL, and relational algebra, in addition to social and ethical considerations and privacy of data. This course incorporates case studies and a project using a relational DBMS.
Duration: 8 weeks
Credit Hours: 3
This course introduces the field of data mining, with specific emphasis on its use for Machine Learning algorithms. Techniques covered may include conceptual clustering, learning decision rules and decision trees, case-based reasoning, Bayesian analysis, genetic algorithms, and neural networks. The course covers data preparation and analysis of results. Skills in Microsoft Excel are useful.
Duration: 8 weeks
Credit Hours: 3
This course introduces students to the field of artificial intelligence (AI). Students will learn how big data and data mining techniques are utilized by machines to create the AI models used by autonomous aircraft and automobiles, personal assistants, IT security software, fraud investigations and credit bureaus. The course will review the history, present day use, and future of artificial intelligence. Through case studies and current events, students will examine the benefits and risks associated with AI. The course will cover issues related to AI and privacy, ethics, and machine bias. Neuromorphic computing, the Open Neural Network Exchange (ONNX), and data analytics will also be discussed.
Duration: 8 weeks
Credit Hours: 3
This course will require students to learn the R programming language and assess how to use it and find interesting features in data. Students will learn about R and statistical best practices and how to display data in a manner that will help you explain your findings to those who do not have a technical background. Moreover, the course introduces students to modeling and simulation. Topics may include basic queueing theory, the role of random numbers in simulations, and the identification of input probability distributions.
Duration: 8 weeks
Credit Hours: 3
This course introduces students to mathematical models that can be employed to make informed decisions in a wide variety of data-driven fields, including (but not limited to) finance, banking, marketing, health care, retail, manufacturing, and transportation. Goals such as increasing revenue, decreasing costs, and improving overall efficiency of operations in the face of various constraints are considered. Students learn to recognize when a problem lends itself to a particular type of model, formulate the model, and use appropriate methods to solve or extract information from the model. Particular emphasis is placed on linear programming (with exposure to network models and integer programs) and the simplex method. Forecasting, inventory management, and queueing models, as well as Markov chains, are also studied. Additional topics covered include sensitivity analysis, duality, decision analysis, and dynamic programming. Software (both spreadsheets and a computer algebra system) is employed consistently throughout the course to expedite the solution and analysis process; emphasis will be placed on the practical application of models rather than on the models' mathematical properties.

La Salle University is ranked in the top 50 percent of national universities nationwide by U.S. News & World Report (2023).

Request More Information

Submit this form, and an Enrollment Specialist will contact you to answer your questions.

Or call 844-466-5587

Begin Application Process

Start your application today!
Or call 844-466-5587 844-466-5587
for help with any questions you may have.