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Data Science for Internal Auditors Training

Reinvent your future with our Data Science for Internal Auditors training. Acquire various roles in the space of Accounting and Auditing. Learn to bridge the gap between Business and IT with Data Analytics skills.
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Internal Auditors course - 360digitmg
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Internal Auditors course reviews - 360digitmg
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"76% of companies in Asia-Pacific and Europe employ data analytics in auditing effort." - (Source). Data Science has become the game-changer for the Internal Audit function. More Internal Audit departments are hiring data scientists to streamline internal audit procedures. This is an area of career growth for Data Scientists. Most companies hire a Data Scientist Internal Auditor. Most analytics software uses Artificial Intelligence algorithms to scan multiple transactions and probably thousands of trial balance entries to provide meaningful results of analyses. This obviates the need for multiple auditors during the internal audit process. This course is helpful for learning specific skills that Auditors can leverage that can help them deliver unparalleled quality and coverage thus maximizing business value.

Internal Auditors

Program Cost

INR 12,000/-

Internal Auditors Programme Overview

The Data Science for Internal Auditors course is among a unique set of programs that 360DigiTMG is offering in its catalog of Industry-Specific courses. It is handcrafted to suit the needs of internal auditors. Auditors have the critical need to identify areas of fraud in accounting practices, tax filing, etc. According to the Journal of Accountancy, the power of Data Science and Analytics can help auditors improve by enabling them to test on larger (and complete) sets of data vs just test samples, enhanced anomaly detection and provide a comprehensive analysis of the general ledger.The internal audit function can also leverage the power of Data Analytics and Artificial Intelligence to detect and analyze fraudulent transactions in the realm of finance and accounting. In this analytics course for internal auditors, the student journeys through the fraud detection lifecycle and learns various proactive and reactive approaches to handling fraud. The use of Network Analytics and graph data to identify fraud is explored in depth. In this course, internal auditors and accountants are taught Inferential Analytics, Descriptive Analytics, Hypothesis Testing, Regression Techniques, Feature Extraction, Feature Engineering, Feature Selection, Machine Learning, Text Mining, Natural Language Processing, Time Series Analysis, Forecasting, Black box techniques, and Neural Networks.

Who is an Internal Auditor?

An internal auditor is a professional hired by a company to give an objective assessment of the performance of operational and financial activities. They are supposed to regulate corporate governance. They have to ensure that companies comply with tax and labour laws and regulation.

As part of the audit process, they examine financial statements, conduct interviews with employees, supervise work schedules, check inventory to eliminate errors and expose risks. They create risk assessment profiles for each department that they audit.

Data Analytics in Internal Auditor's role

An Internal Auditor can apply Data Analytics approaches to enhance the internal audit of the following areas

a) Sales and Operations
b) Finance and Accounting
c) Order to Cash, Procure to Pay
d) Legal and Regulatory Compliance
e) IT Infrastructure.

Internal audit department can use Data Analytics to

i. Identify Additional risks
ii. Understand existing risks- effective risk profiling
iii. Testing of data via simulation
iv. Keeping watch for fraudulent transactions.
v. Real-Time Exception Management
vi. Provide assurance coverage
viii. Provide reports to management

Internal Auditors Learning Outcomes

This course will teach auditors how to blend Data Analytics and Machine Learning techniques with the internal audit functions of a company. Manual audits are often a nightmare to auditors as the data is stored across multiple files, stores, and systems. Data Analytics simplifies the audit procedure and reduces the load as it allows you to extract data from any source. It also helps the auditor to integrate data from multiple sources. The auditor can publish the results of his analysis faster. Initially, the student is exposed to the Fraud Analytics Lifecycle. Automated Data Analytics makes fraud detection easier as it becomes easy to dig very deep into the data. It also uses less staff time and cost. Manual detection of fraud is a cumbersome process. Network analytics techniques and advanced and futuristic techniques to detect fraud are also studied in this course. The course also mentors students on the various proactive and reactive approaches to handling fraud. Descriptive and Predictive Analytic techniques to identify risk are elaborated. The principal benefit of using Data Analytics tools is that the audit has more time to give meaningful insights to the customers and better analyses as the software takes care of number crunching. The student will also learn to employ Data Visualization techniques to present the results of an internal audit to senior management.

Learn about the Accounting domain and responsibilities of Internal Auditor
Develop a deep understanding of Fraud Analytics Lifecycle
Gain a sense of proactive vs reactive approaches to handling fraud
Develop an understanding of descriptive and predictive analytics
Apply network analytics techniques to identify and detect fraud
Explore advanced and futuristic techniques to identify fraud
Perform forecasting to take proactive business decisions
Use data visualization concepts to represent data for easy understanding

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16 hours

Classroom Sessions

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20 hours

Python Programming Videos

Who Should Sign Up?

  • Internal Auditors
  • CFO/Director/Head of Accounting
  • Business Analysts
  • Data Analysts
  • Banking and Accounting Analysts
  • Certified Financial Analysts
  • Credit Analysts
  • Financial Advisors
  • Math, Science and Commerce Graduates

Internal Auditors Course Modules

This Data Science course for Internal auditors enables the participant to learn about the accounting domain and the key responsibilities of an internal auditor. The preliminary modules paint a pretty portrait of Data Science and its applicability in the Internal Audit Function. Project Management skills are explored at the very inception of this course. The ABCs of Data Analytics namely, Inferential Analytics, Descriptive Analytics, Feature Engineering, Feature Extraction, and Feature Selection are discussed with students. A separate module on Hypothesis Testing and Regression Techniques is also included. Today increasingly internal auditors are using Machine Learning approaches to identify risk and detect fraud. An entire module is therefore dedicated to Machine Learning. Fraud Detection using Network Analytics and Graph Data is also included. Text Mining, Natural Language Processing and its applications in audits also feature in the curriculum of this course. Today companies are leaning towards Black Box techniques like Neural Networks, SVM to identify fraud in audit processes. All these techniques in addition to Time Series and Forecasting are the central themes of the concluding modules of this course.

How we prepare you
  • Internal Auditors training with placements
    Additional Assignments of over 60+ hours
  • Internal Auditors course with placements
    Live Free Webinars
  • Internal Auditors training institute with placements
    Resume and LinkedIn Review Sessions
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    Lifetime LMS Access
  • Internal Auditors training
    24/7 Support
  • Internal Auditors certification
    Job Placements in Internal Auditors Fields
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    Complimentary Courses
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    Unlimited Mock Interview and Quiz Session
  • best Internal Auditors training with placements
    Hands-on Experience in Live Projects
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