Using automated image recognition it is possible for large organisations to streamline financial departments while reducing overheads believes Intervate’s Gia Thom.
As a business entity grows in complexity and size, so delivering a consistent level of service and performance to key clients becomes a more challenging ideal to realise. With thousands of approved providers, processes and supply chain considerations to take into account, remaining agile and responsive can become increasingly troublesome.
Nowhere is this more keenly felt than within the financial department. Tasked with conducting many of the organisation’s most delicate and yet vital business functions, this division is often inundated with requests, queries and daily obligations.
Without careful administration, finance can easily fall behind. According to professional auditing group, KPMG, this sector is a key focus area for improvement of performance and service delivery within many large entities.
This is not for a lack of professional capability or willingness to meet internal targets. All too often, those responsible for daily accounting tasks are simply strapped for time.
Sorting, checking and processing thousands of invoices and reconciliations in a limited timeframe is a laborious process. This is just one of the many daily expectations levied upon large account payable teams.
The most commonly cited failure point in KPMG’s South African Sourcing Pulse Survey of 2012 is an inadequacy of enabling IT systems. This means that despite their presence within the business administration environment, many financial management and response solutions are deficient.
To solve this challenge several global organisations have turned to automated platforms that employ image recognition software to process formal documents. Although local groups are somewhat behind the curve, many have begun to embrace solutions of a similar yolk to ease the burden on financial staff.
Nonetheless, the misperception that these offerings are usually accompanied by a significant price tag still exists.
The reality is that many domestically available automation platforms may in fact reduce operational overheads – freeing up valuable financial and professional resources to address more pressing tasks.
Furthermore, the reliability of these solutions is unparalleled. In many instances automated software is more effective at detecting and addressing anomalies or deviations than its human counterparts.
It really is simply a matter of time. In the race to improve service delivery while eliminating unnecessary cost, image recognition may be the most logical approach.
