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What is AI in Finance?

What is artificial intelligence (AI)?

Artificial intelligence refers to systems or machines that mimic human intelligence to perform tasks. AI is intended to significantly enhance human capabilities and contributions, making it a very valuable business asset.

What is machine learning (ML)?

Machine learning is the subset of AI that focuses on building systems that learn—or improve—performance, based on the data they consume, without necessarily requiring various human interventions, such as programming and coding.

What is ERP finance?

Finance can be defined as the activities associated with the management and study of investments and money. Under the concept of money management in finance, the associated activities include issues touching on lending, borrowing, saving, budgeting, forecasting, investing, and assets and liabilities. For businesses, finance is the backbone of the organization, handling all of the necessary economic activities that keep businesses running, including purchasing assets and raw materials, paying employees and suppliers, and planning future business investments.

Specific software, such as enterprise resource planning (ERP,) is used by organizations to help them manage their accounting, procurement processes, projects, and more throughout the enterprise. Examples of back-office operations and functions managed by ERP include financials, procurement, accounting, supply chain management, risk management, analytics, and enterprise performance management (EPM).

For many IT departments, ERP systems have often meant large, costly, and time-consuming deployments that might require significant hardware or infrastructure investments. The advent of cloud computing and software-as-a-service (SaaS) deployments are at the forefront of a change in the way businesses think about ERP. Moving ERP to the cloud allows businesses to simplify their technology requirements, have constant access to innovation, and see a faster return on their investment.

Safra Catz thumbnail

“Artificial intelligence and machine learning are radically transforming how business operates, especially finance. Routine tasks are being automated so that finance professionals can focus on what matters most–identifying the next growth markets.”

Safra Catz Chief Executive Officer, Oracle

How is AI driving continuous innovation in finance?

Traditionally, financial processes, such as data entry, data collection, data verification, consolidation, and reporting, have depended heavily on manual effort. All of these manual activities tend to make the finance function costly, time-consuming, and slow to adapt. At the same time, many financial processes are consistent and well defined, making them ideal targets for automation with AI.

The advent of ERP systems allowed companies to centralize and standardize their financial functions. Early automation was rule-based, meaning as a transaction occurred or input was entered, it could be subject to a series of rules for handling. While these systems automate financial processes, they require significant manual maintenance, are slow to update, and lack the agility of today’s AI-based automation. Unlike rule-based automation, AI can handle more complex scenarios, including the complete automation of mundane, manual processes.

Increased automation also means improved accuracy across your financial processes. High volume, mundane processes, such as invoice entry, can lead to fatigue, burnout, and error in humans. Computers, however, don’t have these same limitations. They can also process drastically higher volumes of transactions in a given period. The end result is better data to work with and more time for the finance team to focus on putting that data to use.

Examples of AI in finance

Today, companies are deploying AI-driven innovations to help them keep pace with constant change. According to the 2021 research report “Money and Machines,” by Savanta and Oracle, 85% of business leaders want help from artificial intelligence.

Here are three common ways companies are putting the power of artificial intelligence to work. First, companies are automating manual processes, such as accounts payable processes, by using the power of artificial intelligence to deliver on smart classification and smart recognition. ERP systems with built-in AI technology can now scan physical invoices, identify the key information, for example, supplier name, materials purchased, and associated cost, and enter it into their ERP systems automatically to detect fraud, reconcile accounts, and expedite approvals.

Second, automated financial close processes enable companies to shift employee activity from manual collection, consolidation, and reporting of data to analysis, strategy, and action. Smart prediction relies on scenario modeling and unbiased forecasting. Using our own solutions, Oracle closes its books faster than anyone in the S&P 500—just 10 days or roughly half of the time taken by our competitors. This leaves our financial team with more time focused on the future instead of just reporting the past.

Finally, companies are deploying AI-guided digital assistants that make it easier to find information and get work done, no matter where you are. For example, finance organizations can leverage digital assistants to notify teams when expenses are out of compliance or to automatically submit expense reports for faster reimbursement. Today’s digital assistants are context-aware, conversational, and available on almost any device. Employees don’t have to remember complex query language or transaction codes. Instead, they can interact with the ERP system using plain, natural language.

Benefits from AI in your finance department

An ESG research report conducted with Oracle (PDF) compiled the top AI benefits reported by 700 finance and operations managers and executives who are regular users of ERP, EPM, and/or SCM applications:

Productivity
  • Faster analysis/insights
  • Reduced time to produce narrative/statutory reports
  • Increased employee productivity
  • Reduced time to generate and audit financial statements
  • Reduced time to complete monthly financial close
Accuracy
  • Reduced errors in automated tasks
  • Improved forecast, planning, and modeling accuracy (e.g., sales forecast)
  • Reduced risk/security events
Business value
  • Improved understanding of why the business is performing at the level it is
  • Improved profitability by identifying more/less profitable areas of the organization
  • Improved workforce planning (e.g., assessing talent gaps, predicting salary costs, etc.)
  • Created a competitive advantage/differentiation

What are the risks of not implementing AI in finance?

According to the “Money and Machines” report mentioned earlier, 87% of business leaders believe that organizations that don’t rethink finance processes will face risks, including:

  • Falling behind competitors 44%
  • More stressed workers 36%
  • Inaccurate reporting 36%
  • Reduced employee productivity 35%

Companies that take their time incorporating AI also run the risk of becoming less attractive to the next generation of finance professionals. 83% of millennials and 79% of Generation Z respondents said they would trust a robot over their organization's finance team. Millennial employees are nearly four times more likely than Baby Boomers to want to work for a company using AI to manage finance.


Getting started with Finance and AI

Investing in AI for finance processes can have a big impact on your organization’s ability to make data-centric decisions and keep pace with continuous change in your industry and marketplace. Here are a few things to consider before you get started:

Custom-built AI app vs. cloud ERP system with AI built in

There are two primary approaches to infusing your ERP system with AI: create custom AI apps from scratch or use a modern cloud ERP system with AI built in. If you already have a team of data scientists and developers familiar with AI, building custom apps might be an easy way to test the waters. On the other hand, a modern cloud-based ERP system makes it easier to expand your footprint and integrate AI across different aspects of finance. It also transfers the development risk to the ERP cloud provider.

Top machine learning tasks

Either way, you should start with a well-defined use case for artificial intelligence and expand from there. According to the “Money and Machines” report mentioned earlier, the top four tasks for which business leaders seek support from machine learning are:

  • 43% approvals
  • 39% budgeting and forecasting
  • 38% reporting
  • 38% compliance and risk management

Which skills we do need with AI?

With AI poised to handle most manual accounting tasks, the development and proficiency of higher-level skills will be imperative to success for the next generation of finance leaders. Finance professionals will still need to be proficient in the fundamentals of finance and accounting to oversee the algorithms and be able to spot anomalies. However, their day-to-day work will increasingly focus less on crunching the numbers and more on data interpretation, business analysis, and communication with key stakeholders. Skills, such as business strategy, leadership, risk management, negotiation, and data-based communication and storytelling, will help to complement the abilities of AI in finance.


Access to new AI innovations?

Modern cloud ERP, delivered in a software-as-a-service (SaaS) model, makes it easy to adopt artificial intelligence. You receive access to innovations regularly, without the challenges typically associated with traditional ERP upgrade projects. In the case of Oracle Cloud Enterprise Resource Planning (ERP), you’ll receive access to new innovations, such as artificial intelligence every 90 days. This means you’re always on the latest version and never have to worry that outdated technology is holding your business back.

AI-related questions to ask when choosing an ERP vendor

The advantages of adopting AI in finance are clear. But before investing, it’s important to make sure that your vendor’s AI capabilities can live up to their promises. Here are a few key AI-related questions you should ask your ERP solution provider when choosing your ERP solution:

1. Are the ERP applications cloud-enabled?

Robust compute resources are necessary to run AI on a data stream at scale; a cloud environment will provide the required flexibility.

2. Is AI already embedded into the ERP features?

Prebuilt AI solutions enable you to streamline your implementation with a ready-to-go solution for more common business problems. Oracle’s AI is embedded in Oracle Cloud ERP and does not require any additional integration or set of tools; Oracle updates its application suite quarterly to support your changing needs.

3. Is the ERP vendor’s solution also focused on human improvement? Or is it only focused on process improvement?

The value of AI is that it augments human capabilities and frees your employees up for more strategic tasks. Oracle’s AI is directly interactive with user behavior, for example, showing a list of the most likely values that an end-user would pick.

4. AI Ethics—Does the solution support the responsible use of AI?

AI can help companies drive accountability transparency and meet their governance and regulatory obligations. For example, financial institutions want to be able to weed out implicit bias and uncertainty in applying the power of AI to fight money laundering and other financial crimes. Read more about how Oracle promotes responsible use of AI.

Your finance department is at the core of the AI transformation

The finance department has taken the lead in leveraging machine learning and artificial intelligence to deliver real-time insights, inform decision-making, and drive efficiency across the enterprise. This is why finance will be one of the first areas to see the impact of these technologies on day-to-day activities—in everything from automating payments to calculating risk—with detailed analytics that automatically audit processes and alert teams to exceptions.