According to a survey by the Hackett Group, 91 percent of respondents rated digital transformation and competitive cost structure maintenance as highly important or critical to their finance teams’ 2019 objectives. This clearly demonstrates how companies are focusing on optimization, and the Finance and Accounting (F&A) function is no stranger to this transformation. As operating budgets go down and revenue growth projections increase, Artificial Intelligence (AI) and automation will be the answer to doing more with less.

Businesses are increasingly seeking new technologies that can amplify the scope of automation in the F&A function, and Robotic Process Automation (RPA) has been one of the frontrunners in this segment. RPA imitates human actions to carry out rule-based tasks such as copy-pasting, data-gathering and consolidation and entering data from one application to another. While certain productivity levels are achieved through this basic level of simple automation, a substantial level of human intervention is still required in almost 100 percent of the transactions.

The next level is deep automation wherein transactions can be completely digitized to enable extremely high productivity gains and free up time for finance professionals for analytical and strategic work. In this scenario, all transactions are routed through automation engines, thereby restricting human interaction to managing exceptions / fall-outs.

For example, invoices digitized through optical character recognition are automatically matched against purchase orders and receipt lines. These invoices are then posted in the enterprise resource planning system for payment processing, thereby limiting manual intervention to handling cases such as quantity / price mismatch and missing receipts. Deep automation can be scaled up further with Machine Learning (ML) and complex algorithms for organizational development.

However, to meet evolving customer expectations while keeping pace with changing regulatory norms, companies require optimum accuracy and standardization. This brings us to the ultimate stage in the automation journey – intelligent automation. Using technologies such as AI and ML, intelligent automation unearths newer trends and enables adoption of business rules to improve both productivity and compliance.

The deployment of intelligent automation is based on the potential benefits in terms of improved quality rather than cost. For example, intelligent automation enables transformation of the traditional financial closing practice by shifting to on-demand, real-time and data-driven decision-making where AI techniques automate reconciliations and inter-company reporting by drawing patterns and insights from past data. Intelligent automation, when combined with the right approach and powerful set of technologies, paves the way for a faster, precise and cost-effective F&A function.

Automation is a highly scalable technology, which can help finance professionals realize their peak efficiency levels. It therefore needs to be used as a lever to re-invent the F&A machinery rather than just changing the tire. Organizations need to begin with RPA, combine it with AI and other digital enablers to develop intelligent automation and, in turn, re-imagine end-to-end processes to transform operations.

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