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.
Chris Otieno’s Answer
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.
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).
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.