Artificial intelligence in the financial services industry
So far, we know for sure that:
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Generative AI is expected to bring in $2.6 trillion to $4.4 trillion annually to the global economy.
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AI technology enables the automation of up to 70% of business processes.
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The banking industry could see an additional $200 billion to $340 billion annually if generative AI technology is fully implemented.
Although difficult to believe, this is just the beginning of the AI revolution in the finance industry.
While AI certainly brings some of the most innovative changes in finance and accounting, the most critical question CFOs must ask themselves is:
How will AI affect finance?
In this article, we'll look at significant areas for CFOs and finance leaders to explore when considering AI applications in finance. These include:
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Compliance and security
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Fraud detection
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Risk assessment and management
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Cash flow forecasting
What is AI in finance?
In finance, AI refers to using technologies and algorithms such as Machine Learning for financial operations, including banking, trading, and accounting.
Many companies have fully embedded AI and machine learning within their operational model over the past few years. The result is that it has become an accepted part of everyday life — so much so that many people aren't aware of how they use it.
In finance, one clear example is interacting with helpdesk software for credit applications. While this represents only the tip of the iceberg, we predict that automation will be increasingly used to process documents such as invoices and reports and manage expenses and budgets.
With that being said, what is AI in accounting , and how can it help CFOs and finance professionals enhance complex processes and operations?
Where AI in accounting will come into its own is the ability to work out what to do with documents without being given rules by human managers.
AI in accounting and finance is particularly suited for identifying patterns. It marks the end of data analytics, as we’ve come to know it, by processing vast volumes of data with unmatched accuracy and producing reports faster than ever.
Finance automation will likely continue its march this year, meaning that finance professionals will feel the effects of the increased use of AI and machine learning for routine tasks, including reporting and cash flow forecasting.
What are the advantages of using AI for finance professionals?
There's no doubt that AI requires time and money investment for any business looking to develop and implement an operational solution.
Thankfully, AI brings many perks to the financial industry, justifying the resources needed for implementation and training. Some of these advantages are the following, in no particular order:
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Increased long-term efficiency — more resources for finance professionals
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Faster and more accurate reporting — become closer to real-time than ever before
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Processing vast volumes of data — AI can conclude much larger data sets, improving the output quality.
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Spotting trends — effective pattern identification producing insights that human analysts may miss
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Better connectivity — linking a variety of data sets to enrich the depth and breadth
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Predictability and finding patterns — spending time collecting and analysing data is a real drain; by letting a financial system do the work for you, you can get both the data and the saved time.
In terms of finance trends for 2024, we expect to see a significant increase in AI adoption. The near future of AI looks solid, with emerging developments appearing rapidly with the potential to become disruptors. Large language models such as OpenAI's GPT5, Meta's Llama 3, Anthropic's Claude 3, and Inflection AI's Pi 2 are all slated to arrive in the next 12 months, for example.
Examples of AI in finance
In what specific instances may we see AI in the world of finance? Below, we explore six main areas where AI claims the spotlight and how CFOs can use it to improve team dynamics and stay ahead of the competition.
Enhancing compliance and security
Audit, compliance, and security are three major finance sector areas that could benefit from AI applications. AI tools can streamline auditing to ensure the company complies with the latest laws and regulations and simplify the process for finance individuals, who can now concentrate on core activities.
Additionally, all businesses, regardless of size, must protect themselves with the latest systems to avoid becoming vulnerable to cybersecurity threats.
Cloud applications tend to be much more secure, with the software provider taking care of encryption and access control rather than the company. Old accountants will be able to tell many war stories about the old days when accounting software was last in line for IT security patches.
As cloud computing has evolved, one of the biggest winners has been the accounting sector, and there are a series of excellent reasons why cloud computing is so suitable for finance applications.
Detecting fraud
It comes as no surprise that AI is already making incredible progress in fraud detection. AI technologies enable us to spot patterns and analyse vast quantities of data rapidly and effortlessly.
But how does AI for fraud detection work?
For example, Fraud.com points out that users can use "natural language processing (NLP) to analyse unstructured data sources such as emails, chat logs, and social media posts" to enrich the data already in company systems and monitor any suspicious activity that could affect the finance department.
Assessing and managing risks
Regarding suspicious activities, AI can also greatly assist in risk management, identifying and assessing risks and developing mitigation strategies.
For larger companies, it is always worth investing in software-based compliance systems that help colleagues identify and control risk. When allied with an AI approach, these systems can be incredibly powerful.
Artificially intelligent machines can analyse much more data about potential suppliers and partners, for example, than humans can. With Artificial Intelligence, you can also monitor the company exreal-time in real-time and run it through many different algorithm combinations. Insight extraction is about to get more accessible than ever.
Cash flow forecasting
Data collection is just the tip of the iceberg when forecasting the future. The rise of artificial intelligence in finance is an exciting one, and it could well lead to all sorts of insights for businesses in the coming years.
AI-powered systems can allow users to conduct a deep dive into report lines down to the transactional level. Accurate ‘on-demand' information is the way to allow users to self-serve information to answer their queries and make predictions quickly and accurately.
While we have concentrated on more transactional work, AI will also make inroads into the higher-level tasks that finance manages, such as forecasting and planning.
AI can learn how cash flow works in any particular organisation, forecast balances, and develop methods of improving cash flow.
Challenges of using AI in finance and accounting
The recent Bletchley Declaration on safe AI development and deployment shows that governments are taking the possibility of negative impacts from technology seriously. This suggests that the growth in the use of AI won't be entirely unfettered.
For instance, one mistake many businesses make when looking at cybersecurity is thinking that it is a purely technological problem with a corresponding tech solution when so much of cybersecurity focuses on human interaction with systems.
At an operational level, new roles may need to be created, either for pure AI and tech experts or for people with one foot in the finance camp and one in the latest tech realms. Traditional finance skills will remain crucial as the finance team helps to lead the business into a positive future.
Additionally, as tech quickly changes, companies and finance departments, in particular, will need people to manage the implementation process and ensure that their investment is fully leveraged.
In short, as the developed world experiences personnel shortages, there will be a concerted drive to bridge the gap by leveraging AI and upskilling current employees.
Ultimately, the world may be increasingly uncertain, but it's also increasingly exciting – especially regarding technological innovations in the financial sector. There's a lot on the cards, from data analysis tools to futuristic artificial intelligence tools.