Most corporate back-office functions, such as marketing, sales, and security, have a range of SaaS applications to help their teams be more efficient and productive. But corporate finance and accounting departments have been underserved in that respect. Finance has remained stuck in the past with its use of legacy technology.
While other business departments have quickly adopted the digital transformations across the enterprise, finance needs to be faster to expand past its legacy technology of traditional Robotic Process Automation (RPA) and Optical Character Recognition (OCR). Much of the finance team’s time is still spent on mundane tasks that impede them from pursuing more value-added business activities.
But business today is at a significant crossroads. Automation is gaining traction across the enterprise, so it’s no longer an option for finance teams to possibly embrace a new solution. It’s a necessity. Understanding the limitations and hidden issues of legacy technology is the first step to embracing the future of finance.
Automation is gaining traction across the enterprise, so it's no longer an option for finance teams to possibly embrace a new solution. It’s a necessity.
Limitations of Legacy Technology
RPA initially provided significant gains in efficiency for enterprises. The preconfigured software uses business rules and predefined activities to choreograph and automate the execution of repetitive processes, transactions, and tasks involving one or more software systems. While some legacy technology, such as Robotic Process Automation (a tool programmed to execute high-volume, repeatable tasks), might be used in a few finance workflows, its current impact is limited.
The problem?
RPA is highly regimented. Every activity must be explicitly scripted. An engineer must reconfigure the RPA code if the business rules or predefined activities change and the execution of repetitive processes, transactions, and tasks involves one or more software systems.
Additionally, RPA bots require precise instructions to extract relevant, contextual information from an input. This lack of flexibility becomes frustrating as time passes, making RPA a simple, quick-fix technique for automating and digitizing processes rather than a long-term solution.
Optical Character Recognition (OCR) is in the same legacy technology boat as RPA. OCR is used to help organizations extract data, to solve complex finance and accounting challenges. However, OCR is no longer enough.
This hold-over technology cannot distinguish between certain characters (S vs. 5, O vs. 0, I vs. 1), erroneously identifying letters or numbers. OCR engines only process documents with printed text and may fail to read handwritten notes or other contextual elements.
The list of challenges goes on and on. However, these limitations aren’t the only ones regarding legacy technology.
Hidden Issues of Legacy Technology
While, at first glance, a unique system designed to fulfill the needs of your business seems beneficial, legacy technology has its limitations. Bespoke RPA and OCR come with a bevy of hidden costs and issues regarding implementation, maintenance, and overall risk.
First, the organization must ensure that the RPA and OCR solutions run on the latest, most updated software system and that any security holes are patched. These activities place all responsibility on the organization—and significant demands on IT personnel to maintain the code.
Updates, revisions, patches, and fixes on legacy tech place all responsibility on the organization—and significant demands on IT personnel to maintain the code.
Additionally, when updates to a customized RPA or OCR instance are issued, it’s essential to ensure that connected applications are not impacted negatively and continue functioning as required. This ongoing legacy technology maintenance is tedious and time-consuming, especially when IT is busy with many projects.
Even worse? Many businesses need more skilled employees to handle legacy technology maintenance, security, and operations consistently.
The limitations of legacy technology are numerous. So, what’s next…
The Future of RPA and OCR
The bottom line? Legacy technology alone is insufficient for handling complex business objectives, unstructured inputs, and the intricate processes typically found in today’s complex finance office.
Instead, the key to taking the legacy technology of RPA and OCR to the next level and unlocking the benefits lies in RPA enhanced by AI-powered technology and OCR plus Computer Vision. This next-gen detection technology retrieves digital information, then adds artificial intelligence and machine learning algorithms to identify fields and additional elements from the image automatically.
AI systems outpace RPA and OCR on their own thanks to AI’s ability to combine cognitive automation, machine learning, reasoning, hypothesis generation and analysis, and natural language technologies to produce insights and automate actions. With AI, the most advanced computer systems become widely available to all parts of the organization, primarily to finance where needed most.
Enhancing legacy technology with artificial intelligence helps to accurately address and resolve the labor-intensive aspects of the finance office and frees teams to focus on more impactful, meaningful work.
Enhancing legacy technology with artificial intelligence helps to accurately address and resolve the labor-intensive aspects of the finance office and frees teams to focus on more impactful, meaningful work.
Auditoria.AI promises finance teams an intelligent, AI-enhanced autonomous finance back office that elevates the legacy technology already in place.
Don’t let your finance office be held back by the limitations of legacy technology. It’s time to identify your back office’s limitations and hidden issues and start embracing the future of AI-enhanced automation in the finance office.