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4 Ways the Generative AI Boom is Transforming Business Financial Management


The arrival of generative AI is going to have significant ramifications for virtually every industry on Earth. One of its biggest impacts will be felt in financial management at an enterprise level, with the level of efficiency on show capable of cutting costs and optimizing existing processes.

The chances are that you know plenty about generative AI already. Unless you’ve been living under a rock, you’re likely to have either seen or used ChatGPT and had a taste of the limitless potential of the technology.

This is only the beginning. Forecasts suggest that generative AI will fundamentally change 52% of jobs as we know them today and the technology has the potential to enhance a number of existing roles through automation.

With the ability to actively interpret masses of data and generate documents, insights, and actionable advice off the back of these unstructured datasets, GenAI will become an asset in the field of finance and accounting across a number of sectors.

What could 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 Age of Predictive Analytics

Generative AI can analyze large datasets, which can directly improve the ability of financial departments to uncover insights and create detailed financial reports that aren’t subject to human error.

Built on machine learning insights, Accenture data suggests that 42% of companies experienced profitability from their ML and AI initiatives that exceeded expectations, with only 1% expressing disappointment.

When using unstructured data, generative AI models can use predictive analytics to identify patterns in historical data within your business model and offer rich insights into financial trends to offer actionable advice 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. Rather than record-keeping, business leaders can access smarter decision-making that can help ensure financial health throughout different departments.

We’re already seeing globally-focused firms like EY utilize generative AI systems to improve efficiency within their accounting. The consulting giant has also incorporated large-language models (LLMs) to solve international payroll queries from employees, which draw on complex legal and regulatory datasets to offer accurate and efficient answers without relying on human response times.

For startups, these insights can prove invaluable when it comes to funding rounds, and resources can be more appropriately allocated to ensure financial sustainability.

Next-Generation Documentation

Because of generative AI’s ability to process, summarize, and extract relevant data from extensive financial documents like annual reports, quarterly earnings, and other financial statements, the technology is an excellent tool for focused analysis and driving decision-making processes.

This means that GenAI algorithms can generate abridged reports for ease of reference, and provide the necessary headlines for relevant parties to use without having to spend time sifting through information when up against a deadline.

KMPG data suggests that 65% of reporting leaders are already using artificial intelligence and generative AI solutions in their workflows. Additionally, 71% anticipate that AI solutions will become imperative in the future, while 48% have already adopted these solutions.

The adoption of generative AI workflows offers leaders several benefits, from efficiency and ease of workloads on staff to more accurate data and cost-saving insights.

Incisive Reporting

Data extracted from documents can also be used to create new essential documentation autonomously and can be used alongside invoice generators to accurately deliver invoices to contract staff, freelancers, and small business owners on the fly without the risk of error in the data entry process.

Because of its unprecedented capabilities, Deloitte’s analysis of generative AI suggests that we could see financial reporting that transcends text-based insights. Instead, speech and audio can be generated to supply high-quality narration and dubbing on videos and presentations, images and video may be used to deliver hyper-realistic insights and graphics based on text inputs, and 3D objects can be rendered from 2D inputs to create data-driven virtual environments.

Perpetual Compliance

Businesses utilizing generative AI can also tap into the technology’s machine-learning capabilities to craft an intelligent regulatory and policy compliance monitoring tool to ensure constant operational efficiency.

The technology can stay on the lookout for regulatory changes, procedural requirements, and policy shifts to alert relevant parties when a rule change puts the business at risk or whenever compliance lapses in certain areas of operation.

While remaining on the lookout for compliance misalignment, generative AI is capable of automating finance compliance on a perpetual basis for businesses, saving countless departmental hours in the process.

One example of perpetual compliance in action can be found in LeewayHertz’s generative AI platform, ZBrain, which seeks to optimize compliance processes while offering regulatory adherence for businesses and optimizing governance practices.

Using client data to train advanced LLMs like GPT-4, Vicuna, Llama 2, or GPT-NeoX, ZBrain can integrate regulatory compliance into enterprise processes to boost efficiency without the risk of running into issues.

This tool, along with all appropriately trained generative solutions, can be especially useful for internationally-focused businesses that may need to monitor compliance across borders in real time.

Real-Time Analysis

While human financial analysis can be a drawn-out process, generative AI offers real-time insights that can be actioned and delivered in a matter of seconds.

The implementation of AI solutions in financial reporting is nothing new, and KPMG data suggests that almost three-quarters of businesses are already using artificial intelligence in financial reporting, and this figure is set to rise to 99% in three years.

With the rise and rise of AI solutions in financial analytics, decision-makers need to get to work on exploring how generative AI can drive efficiency today, rather than tomorrow.

This ability to offer up-to-the-minute insights on the financial health of a company can help quickly alert decision-makers to anomalies within the data, emerging trends, and possible risks to the bottom line of the business as they occur.

Alongside predictive analytics, real-time monitoring for financial trends provides businesses with the ability to react faster to issues in their data to guard against issues and leverage more informed decision-making.

Applications in Efficiency

This can be a particular asset when it comes to safeguarding against financial crime. In one example, risk management firm NICE Actimize developed a GenAI tool to support human staff in investigating financial crimes.

The tool was capable of cutting investigation time by 50% and saving as much as 70% when it came to suspicious activity report (SAR) filing.

Aside from financial crime, we’re also seeing rapidly emerging use cases surrounding financial analytics. Deutsche Bank, for instance, is testing Google Cloud’s generative AI and LLMs at scale to deliver fresh insights for financial analysts, helping to improve real-time execution velocity and operational efficiencies.

Implementing Generative AI Management

Generative AI will have a lasting impact on financial management for businesses. Although we’re seeing use cases emerge frequently, the path from ideation to the implementation phase of the technology will drive innovation throughout the sector.

With the ability of GenAI to predict and monitor performance in real-time, decision-makers will no longer have to fear unexpected, nasty surprises in expenditures, or the damaging effects of losing compliance with regulators.

Most importantly, the generative capabilities of the technology will save countless hours for financial and accounting teams. Helping to deliver greater accuracy and efficiency throughout one of the most important areas of operations for all businesses.





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