How AI Will Change ERP for Finance Departments for Good

Can you imagine going to sleep tonight and waking up three years into the future? What do you think 2022 will look like, and how drastically do you think your job will change?

Due to the latest advancements in artificial intelligence (AI), we can tell you that those who work in finance departments will find many of the mundane tasks they do every day being done by robots. When it comes to conducting day-to-day business for financial departments across all industries, AI is having a drastic impact set to permanently change financial departments by 2022 on a grand scale.

AI implements the use of machine learning, robotics, analytics, and automation to make predictions and adapt responses in specific situations that occur every day. This is especially beneficial for automating manual, repetitive tasks. Embedding AI into enterprise resource planning (ERP) software to automate and streamline typical accounting and bookkeeping processes while learning from past data can save companies both time and money, with boosted productivity. 

AI works much like the human mind in terms of analyzing, responding, and making suggestions. This is especially helpful when it comes to automating tasks such as accounts payables and receivables, initiating payments, matching purchase orders, entering data, categorizing info, and analyzing financial trends.

It can also be used for market trading, analyzing and processing big data, making credit decisions for potential borrowers, and managing the finances of a firm. This technology has the capability of taking over payroll tasks, auditing, tax payments, consistent customer services, behavior analysis, and fraud prevention.

Due to the benefits realized from integrating finance AI technologies, we foresee several major mainstream changes coming to the ways in which financial departments operate. Some of the most common ways ERP AI will impact financial departments are included in the paragraphs below.

Risk and Compliance

Companies of various industries have lists of rules and regulations they must comply with in order to reduce risk and keep both the public and their employees safe. Food and drug manufacturers, for example, must follow a strict set of rules set forth by the food and drug administration (FDA) to ensure that they are keeping the public safe. An architectural firm, on the other hand, doesn’t need to comply with the FDA, but with various building codes set forth by their local city governments. The lists of things companies must comply with vary not only from one industry to the next, but also from one country or state to the next. And the authorities a company must comply with can be numerous. This can be difficult for businesses to stay on top of without the use of ERP AI technology, especially if they are national or global brands. Implementing AI into the risk and compliance software and processes of a firm can help simplify complex compliance rules and make the reporting process simpler. This is especially helpful when it comes to global compliance reporting (GCR) that spans across hundreds of regulations from a variety of different countries. AI can interpret, differentiate, and create compliant reports in a matter of seconds that once took hours to complete. This helps save companies time and money—lowering their risk and the likelihood of penalties accrued from noncompliance. 

Robotic Process Automation to run ERP for Finance

When automating financial processes, there tend to be several gaps in document process automation and financial process automation between independent systems. These gaps used to require repetitive manual labor from humans such as entering data and cutting and pasting info from one program, such as an online loan application, into the next, such as verifying the applicant’s info and running a credit report, and so forth. Robotic process automation (RPA) can manually login to all of these programs and enter and retrieve data from one application to the next. Such gaps in financial departments include procure to pay automation gaps, quote to cash automation gaps, and record to report automation gaps. 

• Procure to Pay Automation Gaps: These types of gaps occur with supplier on-boarding, price comparisons, portal queries, market intelligence, and contract terms. Numerous companies have portals that streamline digital invoicing, but when it comes to on-boarding new suppliers, this process is still manual. Finance AI by means of RPA uses robotics to examine new suppliers and obtain credit reports, tax data, and anything else needed. This technology can also connect various portals of suppliers by automatically logging in, transferring data, and connecting all of the necessary info. It can also track prices and compare them between vendors, evaluate them periodically, and validate contract terms such as compliance measures. 

• Quote to Cash Automation Gaps: Companies oftentimes provide customers with quotes and this involves comparing the prices of various suppliers. This can be time-consuming without the use of RPA which can automatically gather and deliver such info. It can also conduct price checks and verification, check and approve orders with delivery notes, examine new customers, and on-board their data. 

• Record to Report Automation Gaps: Financial close and reporting operations such as closing out sub-ledgers and creating and delivering financial filings to the appropriate regulating authorities requires numerous departments, team members, and systems. ERP software can take over the tedious tasks involved in manually entering data from one Excel sheet to the next between systems, gathering and consolidating transactional data, and integrating it into the ERP for finance. It can also process and deliver financial and operational performance data promptly in order to give companies insights into their businesses. This saves a great deal of time and allows companies to boost productivity and profits by eliminating risk and reducing the amount of time spent by employees conducting repetitive, manual tasks. 

Automating Recurring Processes in ERP for finance departments 

Financial departments can become bogged down with daily repetitive accounting tasks that can be automated with financial AI. Tasks such as categorizing invoice data into numerous accounts, differentiating between various types of payments, and conducting monthly, quarterly, and yearly processes can all be automated now. An ERP AI can compare account balances between various systems, verify statements and reports, and learn from different human inputs to make better judgments and adapt to behavioral patterns of various people. This can free up employee time spent conducting office tasks and allow them to focus on more important duties. This can help reduce costs, save time, and increase productivity. 

Retrieving Reports and Invoices

Searching for and retrieving reports and invoices on an ERP can take upwards of three minutes each time a query is initiated. However, voice-activated AI programs such as AIVA (AI Virtual Assistant) can retrieve specific pieces of data in just ten seconds. That’s a 94% decrease in the time spent retrieving the info without ERP AI. When applied to repetitive tasks that occur each day, AI can save a considerable amount of employee time that could be spent onboarding new clients or increasing sales, thus increasing a company’s productivity and profit potential. 

Fixing Errors and Incomplete Data

Finance AI embedded into ERPs can sort through data across applications and check for discrepancies and missing information. While most applications can match incoming payments to outstanding accounts, things can become tricky when there’s incomplete data, partial payments coming in, or multiple payments sent at once. This can cause errors that take time and effort to sort through. ERP AI is able to identify and resolve these discrepancies—making companies much more efficient and accurate while increasing customer satisfaction. 

Forecasting and Planning

Artificial intelligence is able to improve upon a company’s predictive and prescriptive financial forecasting. Currently, these tasks can be compromised due to human bias, but AI can improve upon cash-flow forecasting, revenue forecasting, balance-sheet planning, and cost and expense planning. This allows companies to better plan and prepare. The degree to which a company can benefit from such ERP AI varies from one industry to the next, as well as from one company to the next. For instance, a large multinational firm in a low-margin, competitive industry is more likely to benefit from cash-flow forecasting while a company offering a variety of products will benefit most from revenue forecasting. A small corporation in a high-margin industry, on the other hand, is likely to see less of an impact. 

Finance AI is becoming a game-changer for the financial departments of companies across the globe. The benefits of implementing such technology include reduced costs, increased productivity, and higher revenues. Given the incentives, it’s pretty safe to say that this technology of our future is here to stay and will change the way financial departments conduct daily business for good. For Focus Softnet, the future of ERP AI technology is here. Focus is at the forefront of implementing AI technology into enterprise software. By delivering a more advanced and effective software solution for less than the cost of competitors such as Oracle Netsuite and SAP, we’re paving the way for the financial AI industry of the future.