New types of software vendors are building intelligent applications that use AI in finance to solve common problems. Our research shows that leading AI finance organizations are 71% more likely to purchase software platforms with embedded AI features. A growing number of vendors are differentiating themselves by building intelligent finance applications that natively leverage AI in common back-office processes like accounts receivable, accounts payable and audit.
Robotic process automation uses software scripts with if-then rules to execute defined processes leveraging structured data. RPA can have a huge impact on the finance function, as much of the work that finance teams do follows clear process steps and a defined set of rules. Programming a robot, or team of robots, to undertake this work can eliminate the risk of human error and, in many cases, complete the task in half the time it takes a human.
RPA does have limits. RPA is designed for “doing” and is therefore inappropriate for complex, dynamic processes that require analysis and judgment. Also, each RPA deployment is stand-alone, designed to automate a specific process and not scalable beyond its original use case. However, for most organizations, the use of RPA for finance is a cost-effective way of improving accuracy and increasing productivity, which is central to finance’s long-term strategy. And unlike traditional finance IT solutions such as an ERP installation or upgrade, implementing RPA doesn’t require a “standardize then automate” approach. In fact, RPA can automate individual tasks or components within a process that make the overall process more efficient.
日本 最新ニュース, 日本 見出し
Similar News:他のニュース ソースから収集した、これに似たニュース記事を読むこともできます。
ソース: DailyFX - 🏆 305. / 63 続きを読む »
ソース: PistonHeads - 🏆 553. / 51 続きを読む »