3 Ways AI will Transform the Finance and Accountancy Sector in 2020: Here, you will read about the top 3 ways in which Artificial Intelligence will revolutionize the finance and accounting industries over the coming years. First, understand the meaning of Artificial Intelligence and its role in this business sector.
What is AI?
Artificial Intelligence (AI) provides extraordinary capabilities to machines. It is a trending technology that uses Machine Learning (ML) and Deep Learning algorithms to simulate intelligence into systems. Apart from these technologies, it also uses Natural Language Processing (NLP) such that machines learn to respond similarly to humans in certain situations.
This technology, along with the implementation of Robotic Process Automation (RPA), is poised to make transformations in almost every industry. However, it has made tremendous growth in the department of finance and accounts.
As per Accenture, companies can reduce their cost by 80 percent and save time to perform business tasks by 80-90 percent with the implementation of AI and RPA in their organization.
To become a professional in AI and successfully implement it in your organization, sign up for an Artificial Intelligence online course.
Now, you can read about the role of AI in the finance department.
AI in Finance and Accountancy
AI has made advancements across various industries and is making a huge impact on the industry of finance and accountancy. It helps organizations save time and money along with offering insights. Further, this technology helps in eliminating monotonous tasks and make time to work on matter with higher priority. With the implementation of AI in your organization for finance and accounting, you can stay on top of the completion and also attract the new generation users and employees towards your company.
Here are 3 ways in which you can implement AI in your organization’s finance and accountancy department in the coming year.
Efficient Data Entry and Data Analysis
AI allows organizations to manage their transactions even though they are mundane and time-consuming. Rather than having all the data spread across a number of files, PDFs, documents, and spreadsheets, ML allows you to draw information automatically from images of receipts. It classifies this data under their respective categories before generating graphs and analysis reports.
The analyzed reports offer significant business insights that can help you improve the organization’s financial planning. Moreover, ML also extracts meaningful insights while continuously processing the data. This helps the organization to get an understanding of their long-term investment and spending patterns.
Fraud Detection and Reduction
With the widespread of e-commerce business organizations, the risk of online fraud has increased. Today, there are more methods of online payments than ever. With the rapid growth in financial data spread across a number of payment channels, there is an increase in the risk of fraud.
According to the reports of Action Fraud, there was approximately 66 percent increase in the number of payment-related fraud cases in the UK between the years 2015—2016.
As per the Association of Certified Fraud Examiners, on an average basis, a company loses about 5 percent of its annual revenue due to internal fraud. Auditors can manually audit only 10 percent of the organization’s expense reports which allows the majority of probable fraud to pass by undetected.
With AI, you can audit almost 100 percent of your expense reports more accurately and in a shorter time frame than humans. It can analyze a large amount of data to detect fraudulent activities that may otherwise go unnoticed. AI integrated fraud detection systems have the ability to learn and assess in case of new potential threats. By analyzing more data, the system becomes smarter and improves in the process of dealing with financial fraud. Besides, you can also use these systems to detect suspicious behaviors or anomalies and mark them for further investigations.
Another significant benefit of implementing AI in this sector is the ML application of credit card fraud detection. Most financial organizations are well-equipped with systems that are trained with payment history. Backtesting and algorithm training are both based on large sets of data containing the credit card transaction history. Classification algorithms have the ability to mark these transactions as fraud or non-fraud thereby, allowing you to stop fraudulent activities in real time.
Corporate Policy Enforcement
You can use AI to reduce the time taken to spot non-compliance problems in the financial data. You can easily scan for the transactions made outside the organization’s policy with respect to employee receipts, purchase orders, credit cards, and travel bookings. It enables auditors to correct the errors before helping employees enforce corporate policies. Further, with this implementation, you will also be able to detect violations of expenses by employees like personal expenditure, personal usage of credit card, travel add-on, and unverifiable receipts.
Organizations will have the ability to determine the policies that work well for their success and if it is justified to violate specific policies due to better visibility of the spending patterns. As an example, you can share economic services to save the company’s finance, suggest various updates on policies to improve the alignment with the comfort of employees. With AI, you can collect financial data and identify patterns after which you can make data-driven recommendations for the corporate policies.
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