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Differences in Digital – RPA, AI, and Analytics
Robotics Process Automation (RPA), artificial intelligence (AI), analytics, digital solutions…after a while, it all starts to sound like one big buzz word. It’s no surprise then, that according a recent Accenture survey, three in four organizations have either taken their financial systems digital or plan to do so in the near future.
Utilizing natural language processing (NLP) in conjunction with the adaptive learning capabilities of AI, financial tasks such as creating and editing journal entries, reporting, and ensuring regulation compliance can now largely be automated. For example, Accenture’s journal entry app can review a company’s journal entries for errors or fraud with up to 98% accuracy, even when the information is incomplete or IFRS reporting guidelines have changed.
Learn more about streamlining your data entry processes here.
Regarding compliance standards, AI has demonstrated the ability to reduce false positives that might indicate illegal financial activities by up to 30%. This helps finance professionals waste less time chasing bad leads.
Automating Finance’s Core Functions
Of the eight primary finance functions, five can be automated by up to 80%. Which five?
- Transaction processing
- Exercising control
- Ensuring compliance
As for the other three (analysis, advisement, planning), significant human intervention is still mandatory. These strategic-level functions have become more important than ever, and process automation only serves to empower human employees to focus their efforts specifically in these domains.
The big takeaway from the report is that digital solutions are not merely for automating repetitive tasks. To fully unlock their potential, managers should look to gear these solutions toward specific outcomes and utilize automation to bolster their human talent.
Read the full report “Digital Finance: Beyond the Hype” here.