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How AI Helps Companies Manage Their Finances

AI Helps Companies Manage Finances

Artificial intelligence (AI) models can improve overall business operations across all industries. Healthcare companies use it to enhance diagnostic and surgical capabilities. In addition, manufacturing industries tap AI to improve processes, cut costs, and reduce errors. Even financial institutions rely on this technology to enhance security and workflows. 

Before using AI-enabled machines, companies must possess a reliable document annotation tool to feed high-quality data into the system. Only then can they reap the benefits of this advanced platform. 

Besides solving widespread challenges, AI can be used for company-specific applications. For businesses that struggle with financial management, AI can help in the following ways.      

1) Reducing business costs 

Technology investments may be costly, but they can save companies long-term. For instance, chatbots can provide round-the-clock customer service, while digital marketing automation can boost any marketing campaign. More importantly, machine learning (ML) models can speed up accounting, invoice, and payment processing systems.     

As a result of streamlining repetitive tasks and keeping them error-free, workers’ productivity hours are increased, and costly mistakes are averted. Reducing operational costs would also mean companies, especially startups, will have fewer cash flow issues.   

2) Maximizing revenues 

Besides cutting costs and streamlining operations, AI and ML models can improve a company’s profitability. Moreover, it can save costs without sacrificing a firm’s income potential. For instance, they can be utilized for more targeted and effective marketing campaigns, leading to enhanced sales.   

An intelligent marketing campaign is vital in keeping expenses down and in using the right strategies regardless of which stage your prospect may be in their purchasing journey. ML systems can gather customer behavior and preferences to make your advertising strategies more effective. Moreover, this technology can collect customer relationship management (CRM) data to boost digital marketing. Thus, AI can automate the sales funnel using data from CRM and other sources, allowing for more high-quality and relevant leads or upgrades for existing clients.     

3) Efficient fraud detection and prevention 

The 2022 Global Economic Crime and Fraud Survey released by corporate financial firm PricewaterhouseCoopers (PwC) revealed that external actors remain a significant threat among businesses worldwide. Hackers and organized crime groups are two of the most prevalent threats, with digital platforms enabling them to perform their activities efficiently and anonymously.  

Because of efficient data analysis capabilities, AI models can detect fraud faster and swiftly. They can study patterns in consumer behavior and preferences, and any anomaly could raise red flags. In addition, ML takes a proactive approach against fraudulent activities, rejecting questionable transactions upon detecting a dubious pattern.     

With these features, companies can ensure that all their transactions are legitimate. Effective fraud prevention and detection capabilities mean companies are less vulnerable to financial losses. In the US, fraudulent cases take more than a year to be detected, costing average monthly losses worth USD$8,300, according to a 2020 report by the Association of Certified Fraud Examiners.

AI financial management

4) Improving risk assessment procedures 

Financial institutions such as lending and credit card companies may have a skilled team of risk assessors, but loan application approvals remain time-consuming and laborious. With AI integration, this exercise can become less tedious with reduced risks of mistakes humans are bound to make. 

As a result, most companies use financial technology tools to access and process an applicant’s credit history swiftly. Some customized fintech apps subject interested borrowers to a pre-qualification process and later analyze collected data to determine whether they may or may not avail of the loan product. 

Business-to-business (B2B) product and service providers can also use AI-driven risk assessment methods in evaluating their clients. It can identify companies likely to miss payments based on credit history and other financial records when used as a predictive tool.    

5) Generating accurate financial reports

Business owners and executives must regularly have a clear picture of the company’s financial situation. Thus, accounting activities must be done periodically, not only for their consumption but also for submission to the tax agency concerned.   

Automating accounting procedures ensures that internal fraud can be prevented and that reports contain precise figures. Fraud detection and prevention can also work internally. This subject is a critical issue to address, as internal actors were also named among the key perpetrators of fraud, based on the PwC study mentioned in the previous section. With tools such as optical character recognition, ML models can process and validate invoices, receipts, signatures, and handwriting, reducing the risks of spurious transactions.     

In a few technologically-forward companies, AI models are used to forecast spending and propose recommendations for budget cuts while considering operational efficiency.   

The bottom line 

AI and ML models can help businesses manage their finances by decreasing costs and increasing sales and productivity. These advanced technologies can offer more effective and fast solutions for detecting risks and preventing fraudulent transactions.

In addition, efforts are ongoing to expand these applications to focus on AI’s prescriptive and predictive capacities. Thus, it may not take long before the platform could fully take over core financial activities with little to no human intervention.  


  1. Bizmanuals. undated. How Important is Data Annotation in Business?. Accessed 06 July 2022
  2. Houldsworth, L. 10 March 2021. 3 Ways to Improve Financial Management with AI in 2021. Accessed 06 July 2022
  3. Gray, C. 12 April 2022. How is AI helping to transform the finance industry?. Accessed 06 July 2022
  4. Jordan, B. 02 February 2018. How AI Will Transform Financial Management Accessed 06 July 2022
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