The arrival of generative artificial intelligence will have significant consequences for virtually every sector of the Earth. One of the biggest impacts will be felt in company-wide financial management, with a level of efficiency that can reduce costs and optimize existing processes.
Chances are, you already know a lot about generative AI. Unless you’ve been living under a rock, you’ve probably seen or used ChatGPT and gotten a taste of the technology’s limitless potential.
This is just the beginning. Predictions suggest that generative AI will radically change 52% of jobs as we know them today and technology has the potential to improve a number of existing roles through automation.
With the ability to actively interpret masses of data and generate actionable documents, insights, and recommendations based on these unstructured data sets, GenAI will become an asset in finance and accounting across numerous industries.
What might this mean for your financial management? Let’s explore four examples of how the generative AI boom is set to change your operations forever:
The era of predictive analytics
Generative AI can analyze large data sets, which can directly improve finance departments’ ability to uncover insights and create detailed financial reports that are not subject to human error.
Based on machine learning insights, Accenture data suggests that 42% of companies saw profits from their machine learning and AI initiatives that exceeded expectations, while only 1% expressed disappointment.
When using unstructured data, generative AI models can use predictive analytics identify patterns into historical data within your business model and offer deep insights into financial trends to offer actionable recommendations based on possible future outcomes.
New applications in accounting
These innovations can help transform accounting as we know it into a more proactive part of business operations. Instead of keeping records, business leaders can access smarter decision-making that can help ensure financial health across departments.
We are already seeing globally focused companies like EY use generative AI systems to improve efficiency within their accounting. The consulting giant has also incorporated large-lingual models (LLMs) to resolve international employee salary questions, which rely on complex legal and regulatory data sets to provide accurate and efficient answers without relying on human response times .
For startups, this information can prove invaluable when it comes to funding and resources can be allocated more appropriately to ensure financial sustainability.
Next generation documentation
Because of generative AI’s ability to process, summarize and extract the relevant data From extensive financial documents such as annual reports, quarterly earnings and other financial statements, the technology is an excellent tool for targeted analysis and decision-making guidance.
This means that GenAI algorithms can generate shortened reports for ease of reference and provide the necessary headlines for stakeholders to use without having to spend time sifting through the information when faced with a deadline.
KMPG data suggests as much 65% of reporting leaders they are already using AI and generative AI solutions in their workflows. Furthermore, 71% expect AI solutions to become indispensable in the future, while 48% have already adopted these solutions.
Adopting generative AI workflows offers leaders numerous benefits, from the efficiency and ease of workloads for staff to more accurate data and cost-saving insights.
Incisive reporting
The data extracted from the documents can also be used to independently create new essential documentation and can be used together invoice generators to accurately and real-time deliver invoices to contract staff, freelancers and small business owners without the risk of errors in the data entry process.
Thanks to its unprecedented capabilities, Deloitte’s generative artificial intelligence analysis suggests we may see financial reporting that transcends text-based insights. Instead, speech and audio can be generated to provide high-quality narration and voice-overs on videos and presentations, images and videos can be used to provide hyper-realistic insights and graphics based on text input, and 3D objects can be rendered from 2D inputs to create data-driven virtual environments.
Perpetual compliance
Companies using generative AI can also leverage the technology’s machine learning capabilities to create an intelligent regulatory and policy compliance monitoring tool to ensure consistent operational efficiency.
Technology can stay on pay attention to regulatory changesprocedural requirements and policy changes to alert stakeholders when a rule change puts the business at risk or whenever compliance breaks down in certain operational areas.
While remaining on the lookout for compliance mismatches, generative AI can automate financial compliance on a perpetual basis for businesses, saving countless departmental hours in the process.
An example of perpetual compliance in action can be found in LeewayHertz’s generative AI platform, ZBrain, which seeks to optimize compliance processes while providing regulatory compliance for businesses and optimizing governance practices.
By using customer data to train advanced LLMs such as GPT-4, Vicuna, Llama 2 or GPT-NeoX, ZBrain can integrate regulatory compliance into business processes to increase efficiency without the risk of running into problems.
This tool, along with any properly trained generative solutions, can be especially useful for internationally oriented companies that may need to monitor compliance across borders in real time.
Real-time analysis
While human financial analysis can be a long process, generative AI offers real-time insights that can be actioned and delivered in seconds.
The implementation of AI solutions in financial reporting is nothing new and KPMG data suggests that almost three-quarters of companies are already using AI in financial reporting, and this figure is expected to grow. rise to 99% in three years.
As AI solutions in financial analytics continue to rise, decision makers must commit to exploring how generative AI can drive efficiency today, rather than tomorrow.
This ability to offer up-to-date information about a company’s financial health can help quickly alert decision makers to anomalies within the data, emerging trends, and possible risks to the company’s bottom line as they occur.
In addition to predictive analytics, real-time monitoring of financial trends gives businesses the ability to react more quickly to issues with their data to protect against problems and leverage more informed decision-making.
Efficient applications
This can be a particular advantage when it comes to protecting yourself from financial crime. For example, risk management company NICE Actimize has developed a GenAI tool to support human personnel in investigating financial crimes.
The tool was capable of reduce investigation times by 50% and saving up to 70% in terms of filing suspicious activity reports (SARs).
Beyond financial crime, we are also seeing rapidly emerging use cases surrounding financial analytics. Deutsche Bank, for example, is test Google Cloud’s generative AI and LLMs at scale to provide new insights to financial analysts, helping to improve real-time execution speed and operational efficiency.
Implementing generative AI management
Generative AI will have a lasting impact on the financial management of businesses. While we see use cases emerge frequently, the journey from the ideation stage to the implementation stage of the technology will drive innovation across the industry.
With GenAI’s ability to predict and monitor performance in real time, decision makers will no longer have to fear unexpected and unpleasant surprises in expenses or the harmful effects of loss of compliance with regulators.
More importantly, the technology’s generative capabilities will save finance and accounting teams countless hours. We help deliver greater precision and efficiency in one of the most important operational areas for all businesses.