6 Ways to Achieve Autonomous Finance in 2024 & 4 Benefits 

Autonomous finance is an umbrella term devised by industry analysts like Gartner and Forrester and adopted by vendors. This term refers to the use of advanced technologies like Artificial intelligence (AI) / machine learning (ML), generative AI, blockchain technology, hyperautomation and other emerging tech supporting finance digital transformation. Purpose is to automate financial processes, decision-making, and services to enhance the efficiency and effectiveness of the finance function or financial services firms.

Autonomous finance¹ eliminates inefficiencies and inaccuracies in manual finance processes.

The article

• First covers the issues of traditional finance
• Explores the importance of autonomous finance, tools for implementing autonomous finance, and its benefits. 
• Includes what autonomous finance means for the finance business unit and separately what it means for the financial services industry.

Challenges in traditional finance

Though traditional finance has its merits, it comes with its own set of challenges. To capture why is it crucial to implement autonomous finance solutions, let’s have a look at some of these challenges:

Inefficiency

Traditional financial processes demand intensive manual work and consist of demotivating, repetitive tasks. Example processes include:

• Reconciliation procedures involve matching numerous account payables with transaction data. That is why financial closing solutions are growing in popularity because they reduce a process that used to last weeks to mere hours.
• In enterprises, accounts payable process involves processing hundreds of thousands of invoices shared in the form of PDF files and paper. Large enterprises either employ tens of clerks in their shared services centers or outsource this work to their suppliers.

CFO can not effectively lead efficiency initiatives when their own units require the collaboration of hundreds of employees on low-value added tasks that can be automated.

For some of the accounts payable solutions, see:

• Dynamics 365 in Accounts Payable Automation: In-Depth Review
• NetSuite Accounts Payable (AP) Automation in 2024
• Blackbaud Accounts Payable (AP) Automation in ’24: In-Depth Review
• Sage Accounts Payable (AP) Automation in ’24
• 7 Vic.AI Alternatives to Automate Accounting in 2023
• Top 10 ReadSoft Alternatives / Competitors
• Top 10 Kofax Alternatives/Competitors in 2023
• 14 Rossum AI Competitors/Alternatives in 2023

Errors

Manuel processes are error-prone. In invoice processing, we have witnessed up to 3% error rate in manually extracted data.

Slow decision-making

Decisions in traditional finance are frequently delayed and lower in quality because of slow manual data management. This slows data-driven decision making, which then limits the company’s agility and dynamism.²

58% of medium-sized and large  businesses still use spreadsheets to plan and budget, but 41% of Excel users say spreadsheets can’t handle the amount of data they have.³

Another IBM report shows  that each year, planning data costs time and creativity. Without a central platform, organizations can: 

– Spend up to 20% of their “planning and analysis” time gathering data

– Dedicate up to 30% of that time making sure that data is correct.⁴

3 Ways to enable autonomous finance in the finance function

Businesses can lead their organizations to autonomous finance leveraging several paths:

Automation via artificial intelligence (AI) and machine learning (ML):

Example processes that require machine intelligence include:

Accounts Payable Automation: Invoices shared as PDF or paper were mostly manually processed until accounts payable AI platforms. Use cases of AI in AP are not limited to invoice automation. When trained, machine learning models have the dynamic ability to understand relevant data, thereby speed up the automation process. Employing models capable of continuous learning, particularly those fine-tuned with data specific to a company, enhances the speed and efficiency of automation. Other automation steps include:

• Data capture
• Coding
• Approver identification
• Categorization of documents sent along invoices
• Three way match
• Inputs to balance sheet forecast
• Sanctions screening
• Fraud detection
• Identification of errors

You can also check out our comprehensive, data-driven list and research articles on the topic:

• Accounts Payable AI Platforms
• 10 AI Applications in Accounts Payable (AP) Processes for 2023
• Finance Automation in ’23: What It Is, Best Tools & 6 Processes

Automation of rule-based tasks via robotic process automation (RPA)

According to a research, ⁵ 80% of finance directors have either deployed robotic process automation (rpa) in finance operations or intend to do so. One main reason behind this is RPA’s ability to automate routine tasks (Figure 2) like:

Financial close & reporting: RPA bots can handle month-end and year-end closing tasks by collecting and combining financial data from many different sources. Additionally, it can help with the creation of financial reports.

Adopting an agile mindset that promotes experimentation:

Gartner claims that one of the most important steps in the transition to autonomous finance is the mindset shift, especially regarding CFOs. ⁷ Amongst the company’s proposals to achieve it, key recommendations for CFOs include:

• fostering an experimentation mindset to test new technologies and harness the benefits of autonomous finance
• seeing AI technology as an autonomous tool capable of executing and resolving complex cases without human involvement in certain processes

3 Ways to enable autonomous finance in financial services

Blockchain technology

Blockchain can bring transparency and security to financial transactions, reducing the risk of fraud and error (Figure 3).

• Fraud prevention: The immutability and transparency of blockchain technology can increase the security and reduce the risk of fraud in financial systems. Security is increased considerably because every transaction is recorded on a decentralized ledger that cannot be changed retrospectively.
• Cross-border processes: Blockchain technology speeds up and reduces the cost of cross-border transactions. Traditional international transfers can be expensive and time-consuming, but blockchain technology can process them quickly and with no cost.

Decentralized finance (DeFi): By eliminating middlemen from financial transactions, DeFi has the potential to improve efficiency. Users are able to trade, earn interest, lend, borrow, and more without the need for a central authority.

Digitization and cloud adoption in traditionally manual financial services

Cloud software enables the analysis of and accessibility to financial info in real time, which makes it easier to produce decisions. Cloud software uses API to connect and integrate different apps together to bring data on a visible dashboard that transmits real-time information.

• Investment management: Cloud-powered “robo-advisors” can offer automated investment management services. They can suggest a portfolio based on the investor’s risk tolerance and financial goals and can automatically rebalance the portfolio as needed (Figure 4).
• Lending platforms: Cloud-based platforms can automate and expedite the lending process by instantly conducting due diligence on their riskiness, credit history, etc. Learn more about loan processing automation

Learn more about RPA use cases in treasury management. 

Machine learning in financial services

Predictive analytics: Machine learning (ML) can analyze massive volumes of financial data algorithms to forecast future trends, from the market’s general direction to specific credit risks. Financial organizations and individual investors can use this information to make better judgements. For instance, companies like Amazon use and provide predictive analytics tools to forecast product demand and sales which helps in managing resources efficiently. ⁸

4 overall benefits and practices of autonomous finance

Increased process efficiency

Autonomous finance can help streamline financial processes and make them faster and more efficient. For example, a business could use RPA to automate repetitive tasks like processing invoices or balancing accounts. This would give corporate finance teams more time to focus on other tasks, such as:

• Improving strategic planning and decision making
• Risk management and scenario analysis
• Relationships with clients

Example: A company might use RPA to automate its accounts payable process, reducing the time it takes to process invoices and make payments from several days to a few hours.

Improved accuracy

Autonomous finance can increase accuracy of financial processes by minimizing manual error possibility. Machine learning algorithms can automate matching activities to the right accounts in a company’s general ledger. This would reduce the chance of mistakes in financial reports.

Example: A bank might use machine learning to transaction verification, reducing the chance of errors that could lead to regulatory issues or financial losses.

Personalized services

Autonomous finance can give each person customized services based on their spending habits and financial goals. Robo-advisors can use AI and machine learning to give personalized investment advice that can effect business growth.

Example: Using a robo-advisor, an individual investor can manage their investment portfolio and receive customized advice and automatic adjustments. This can automatically change an investor’s investment portfolio based on the investor’s risk tolerance and financial planning.

Cost savings

As mentioned, autonomous finance can lead to cost savings by automating manual processes and reducing the need for human intervention. These cost savings can come from reduced labor costs, faster processing times, and fewer errors.

Example: Blockchain, AI, and machine learning could speed up loan application verification for financial firms. Blockchain’s transparency and immutability eliminate middlemen and reduce costs, saving money. This novel solution requires less human intervention, reducing transaction costs and application processing time.

If you have further questions regarding the topic, reach out to us:

External links:

• 1. “What is Autonomous Finance?” Gartner. June 13, 2023. Retrieved on June, 10, 2023.
• 2. “The future of financial planning and analysis with digital transformation” IBM. June 13, 2023. Retrieved on June, 10, 2023.
• 3. “Spreadsheets are holding you back” IBM. June 13, 2023. Retrieved on June, 10, 2023.
• 4. “Modern Planning Platforms Drive Business Agility and Better Outcomes” IBM. June 13, 2023. Retrieved on June, 10, 2023.
• 5. “Robotic Process Automation (RPA)” in Finance, Gartner, June 13, 2023. Retrieved on June, 10, 2023.
• 6. ”Development of Evaluation Criteria for Robotic Process Automation (RPA) Solution Selection” Kim, Seung-Hee. MDPI. June 13, 2023. Retrieved on June, 10, 2023
• 7. “3 CFO Mindset Shifts for Autonomous Finance, With Emily Connelly.” Spotify. June 13, 2023. Retrieved on June, 10, 2023.
• 8. “Analytics on AWS” Amazon. Retrieved on June, 13, 2023.