RPA- robot process automation is being integrated into corporate finance

When it comes to robots, most people think of Star Wars or the automobile assembly line, the assembly line, mobile heavy huge agile machine parts, welding or fixed bolt is fixed on the chassis.
Now software robot process automation (RPA) is entering the field of enterprise financing.

In terms of finance, we have realized automation through the implementation of general ledger and enterprise resource planning (ERP) system and Microsoft Excel and other spreadsheet programs.
Financial process, however, many enterprises still stays in the 20th century, the enterprise finance team spent about 80% of the time manually collecting, data verification and consolidation, and advanced tasks such as for analysis and decision-making leaving only about 20% of the time.
RPA will bring a new wave of digital transformation for enterprise financing.
Instead of using programming software to automate certain tasks, RPA USES artificial intelligence (AI) to train and teach software robots to handle transactions, automatically monitor compliance and audit processes.
Machine learning is a form of artificial intelligence, by building can, according to new data and experience in study and improve the system automatically, without the need for a dedicated programming to implement the financial automation, thus further realize financial automation.

According to the Grant Thornton, according to a recent survey shows that the enterprise's financial executives are adopting some of these new forms of financial Shared department implementation process automation, arrange and advanced artificial intelligence analysis in their highest priority project investment, and many people have begun to digitize transformation.

In transaction processing, the cfo can use RPA to optimize its accounts payable and accounts receivable processes.
Companies collect information from customers on how to affect cash flow and customer satisfaction.
A CFO's company may have done well, but AI has added this expertise to allow the company to gather information as quickly as possible while maintaining good customer relationships.

At the same time, the customer may be repeated payment, incorporating more than one invoice for a payment or pay the wrong amount, manual correction in the general ledger system, may cause the error will need a lot of time to sift through invoice, find out the source of the error or tracking customers to solve the problem.
Artificial intelligence and machine learning can support financial teams by automatically tracking information, finding the source of general ledger problems, and suggesting which payments match which invoices.

Artificial intelligence can also reduce financial risk by stopping the wrong payments to suppliers almost in real time.
Companies that pay $500m a year, for example, could leak anywhere from $500,000 to $2.5m from mistakes, fraud and abuse.
Today, large organizations rely on manual sampling audits of invoices and payments to reduce risk.
However, these sample audits contain only a small number of transactions, so errors or waste are rarely found in the process.
However, ai can expand the scope of compliance monitoring and analysis, save millions of dollars, prevent duplicate and fraudulent payments, and curb the risk of cash outflows.