7 answers
Genevieve
Student
Topeka, Kansas
62
Questions
Asked
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How would data science be used in accounting?
Would it analyze ways to boost revenue and control expenses?
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7 answers
William Nwaogu
Construction, CAD and BIM
143
Answers
Lagos, Nigeria
Updated
William’s Answer
Data Science can be used in Accounting for:
AI database queries of accounting books.
Generating data for accounting forecasts.
Carrying out forensic accounting.
Analysis of customer behaviour in market for prospecting.
Automation of algorithmic trade for insight.
AI database queries of accounting books.
Generating data for accounting forecasts.
Carrying out forensic accounting.
Analysis of customer behaviour in market for prospecting.
Automation of algorithmic trade for insight.
Thank you!!
Genevieve
Chris Otieno Ochieng
Data Scientist
6
Answers
Kisumu, Kisumu County, Kenya
Updated
Chris Otieno’s Answer
Data science is an interdisciplinary field that uses statistical and computational methods to extract insights and knowledge from data. While traditionally associated with fields such as computer science and engineering, data science is becoming increasingly relevant in many other industries, including accounting.
In accounting, data science is used to analyze and interpret financial data in new and innovative ways. Here are some specific ways that data science is being used in accounting:
Fraud detection: Data science can be used to detect fraudulent activity by analyzing large amounts of financial data and identifying patterns or anomalies that may indicate fraud.
Risk assessment: Data science can be used to assess financial risks by analyzing large datasets and identifying potential risks or areas of concern.
Forecasting and prediction: Data science can be used to forecast future financial performance by analyzing historical data and identifying trends and patterns that can be used to make predictions about future outcomes
Auditing: Data science can be used to automate auditing tasks, such as data collection and analysis, and identify potential areas of concern more quickly and accurately than traditional auditing methods.
Optimization: Data science can be used to optimize financial processes and identify areas where efficiency can be improved, such as reducing costs or improving revenue streams.
In summary, data science is being used in accounting to improve financial analysis, fraud detection, risk assessment, forecasting and prediction, auditing, and optimization. As the amount of financial data continues to grow, the use of data science in accounting is likely to become even more important in the years to come.
In accounting, data science is used to analyze and interpret financial data in new and innovative ways. Here are some specific ways that data science is being used in accounting:
Fraud detection: Data science can be used to detect fraudulent activity by analyzing large amounts of financial data and identifying patterns or anomalies that may indicate fraud.
Risk assessment: Data science can be used to assess financial risks by analyzing large datasets and identifying potential risks or areas of concern.
Forecasting and prediction: Data science can be used to forecast future financial performance by analyzing historical data and identifying trends and patterns that can be used to make predictions about future outcomes
Auditing: Data science can be used to automate auditing tasks, such as data collection and analysis, and identify potential areas of concern more quickly and accurately than traditional auditing methods.
Optimization: Data science can be used to optimize financial processes and identify areas where efficiency can be improved, such as reducing costs or improving revenue streams.
In summary, data science is being used in accounting to improve financial analysis, fraud detection, risk assessment, forecasting and prediction, auditing, and optimization. As the amount of financial data continues to grow, the use of data science in accounting is likely to become even more important in the years to come.
Great answer Chris, thank you so much!!
Genevieve
Sarah Cruz
Finance Manager
2
Answers
Las Vegas, Nevada
Updated
Sarah’s Answer
Hey Genevieve,
I think your interest is awesome! I have worked in public accounting for some time and think the use of data analytics and science (in all fields, but definitely accounting and auditing) are critical tools in the future of any profession. Bottom line is, we can do more when we utilize data analytics and science. You are spot on that it could recognize insights that help companies increase revenue, control expenses, identify areas of inefficiencies etc. I will say I think it's important to think of them as tools as people with knowledge of accounting and auditing concepts should still be involved in the building of the logic and interpretation of the insights provided. Data science and analysis continues to revolutionize all professions and it's a great idea to think about learning those skills while also learning a core applications (like accounting and auditing).
I think your interest is awesome! I have worked in public accounting for some time and think the use of data analytics and science (in all fields, but definitely accounting and auditing) are critical tools in the future of any profession. Bottom line is, we can do more when we utilize data analytics and science. You are spot on that it could recognize insights that help companies increase revenue, control expenses, identify areas of inefficiencies etc. I will say I think it's important to think of them as tools as people with knowledge of accounting and auditing concepts should still be involved in the building of the logic and interpretation of the insights provided. Data science and analysis continues to revolutionize all professions and it's a great idea to think about learning those skills while also learning a core applications (like accounting and auditing).
Thank you!! :)
Genevieve
Aisha Taylor
Mortgage Closing Specialist
97
Answers
Detroit, Michigan
Updated
Aisha’s Answer
Data scientists are professionals who dive into into data and make sense out of it. If you're an accounting professional, it's obvious that you will be good in numbers. and one of the most important things that a data scientist needs is mathematics. Going from accountant to data analyst can be a logical career change for those looking to leverage their experience in accounting and finance into a broader role in analytics, they go hand in hand.
Thanks for sharing your perspective! :)
Genevieve
Keith Rodgers
Sales Director
107
Answers
Phoenix, Arizona
Updated
Keith’s Answer
You could use a graphic analytics to illustrate the greatest area of growth/opportunity. Apply them and couple that with other new tech (AI) to better predict cash flows and seasonality to anticipate peaks and valleys.
Thank you Keith!!
Genevieve
David Tomala
Director of Analytics
4
Answers
Los Angeles, California
Updated
David’s Answer
One of the most fun and unexpected uses is Benford's law to catch accounting errors/fraud. https://insights.sei.cmu.edu/blog/benfords-law-potential-applications-insider-threat-detection/
Cool, that sounds like a fun career! Thank you!!
Genevieve
Samantha Brooks
Investigations & Forensics Associate
56
Answers
New York, New York
Updated
Samantha’s Answer
Hi Genevieve,
Great question! I work in forensic accounting and my coworkers and I use data analytics all the time when conducting complex investigations related to fraud, money laundering, bribery, corruption, or even insider trading. Being able to analyze large data sets and identify any relevant patterns or trends is often the key to helping us determine whether or not we think any wrong-doing occurred. While we also use many other data sources during investigations, such as text messages or emails, information obtained in interviews, or contractual agreements, data analytics are often a necessary final piece of the puzzle that really helps us put the story and timeline together. I have always found it extremely fascinating how much data analytics and sometimes guide us in the right direction when we’re trying to crack a case.
Great question! I work in forensic accounting and my coworkers and I use data analytics all the time when conducting complex investigations related to fraud, money laundering, bribery, corruption, or even insider trading. Being able to analyze large data sets and identify any relevant patterns or trends is often the key to helping us determine whether or not we think any wrong-doing occurred. While we also use many other data sources during investigations, such as text messages or emails, information obtained in interviews, or contractual agreements, data analytics are often a necessary final piece of the puzzle that really helps us put the story and timeline together. I have always found it extremely fascinating how much data analytics and sometimes guide us in the right direction when we’re trying to crack a case.
Thank you!!
Genevieve