Top 10 Technologies Enabling Finance Digital Transformation in 2024
Per Google Trends, there has been a sustained rise in interest in finance automation. Since the COVID outbreak, around 88% of finance and insurance executives have reported an increase in the implementation of AI technologies 1.
One possible reason for this phenomenon is workload reduction: Gartner claims 2 that automation solutions, such as Robotic Process Automation (RPA), can save finance departments 25,000 hours of work annually. But what specific financial tasks and procedures are being automated? And what technologies are being used for those purposes?
RPA are bots programmed to undertake repetitive tasks. RPA bots are being used in finance because they can reduce the workload of accounting teams, by automating numerous tasks, such as journal entries or intercompany reconciliations, and only requiring a final review from them.
Their other benefit is their consistency. For periodically-repetitive procedures, such as journal entries during financial close, these bots can be scheduled to work as commanded (i.e. recording sales data on journals as they come in), thus minimizing the possibility of missed deadlines.
Artificial intelligence covers a variety of technologies that can be used to enhance financial tasks, such as credit extension.
For example, in the order-to-cash (O2C) process, once an item is added to the cart, retailers have to assume that the customer has the money to pay for the good, so that they can set the logistical wheels in motion. That “assumption” is basically extending the customer a line of credit (LC) until it comes to payment processing.
Financial solutions leverage AI to evaluate applicants’ credit history more quickly, efficiently, and accurately. There are pay-as-you-go credit agencies that can do that for you. So the automated financial solution and the credit agency collaborate with each other to gather credit score on one end, and send it to your ERP on the other, thus allowing the wheels of the O2C process to be set in motion.
3. Workload automation
Another technology used in financial transformation is workload automation. Workload automation uses software to schedule and initiate workflows automatically, thus requiring minimal human intervention.
Workload automation use cases tend to focus on backend processes like file transfers. For example, financial organizations may need to transfer thousands of files on a daily basis to track information about their branch operations. Primary user of workload automation tends to be IT.
Blockchain is a distributed ledger for recording all decentralized transactions.
In finance, it can be used to improve the transparency and security of data, thus reducing the possibility of fraudulent tampering. For instance, a company’s financial documents and statements can all be secured on blockchain. This lowers the feasibility of any employee or executive to make changes to the data on the sheets once they are on the chain because they become instantly verifiable by auditors.
In a survey by Duke University 3, 78% of high-level executives exhibited a preference to tamper with quarterly reporting in order to soothe stakeholders’ sentiment. Blockchain will eliminate that possibility because all adjustments are recorded and verified in real-time, not just at the end of quarters.
5. Cloud computing
Cloud computing is the practice of having data storage spaces without on-premise IT infrastructure. This technology is useful for most automation solutions as the back-end processes and functionalities do not require on-premise infrastructure. All that responsibility is passed on to the developers. Moreover, cloud functionality makes for 24/7 remote and online accessibility by all authorized personnel. This will mean that the progress of financial tasks, be it close to O2C or S2P, can all be remotely monitored independent of location.
Data privacy is another benefit that cloud computing offers financial services. Gartner claims that through 2020, public cloud infrastructure as a service suffered 60% fewer security incidents than those in traditional data centers. So, as they argue, “security should no longer be considered a primary inhibitor to the adoption of public cloud services.”
Security of financial data is of the utmost importance, and leveraging cloud solutions can offer enhanced protection of data and documents.
6. Document automation tools
Document automation is a technology for creating electronic documents, such as invoice issuance for processes in accounts payable, accounting, and tax filings. The software can gather sales data such as, order quantity, price, customer information, and other usable data from underlying ERP systems such as order management software or CRM systems to automatically, and accurately, create an invoice in real-time based on the data it can create thanks to OCR technology.
7. NLP & reporting automation bots
NLP is a sub-field of AI that gives computers the ability to understand and interpret human language. NLP has many use cases in finance, but is arguably most efficient and effective for extracting large volumes of data across different silos and giving it to RPA bots that are specialized in reporting. These bots, then, will generate periodic financial reports, such as P&L statements, tax reports, and other financial statements.
The benefit of NLP being used complementary with reporting bots is that generating reports will be automated and shorter to complete. In addition, because financial reports are meant to educate high-level executives and investors on the financial state of the company, it will mean that they are provided with the most possible accurate sets of data.
Orchestration is a tool that allows for the automatic coordination of different financial ERP systems found in the infrastructure of a modern enterprise. Much like an orchestra conductor, orchestration automates the sequential undertaking of processes.
In financial close, for instance, there is an eight-step process in the checklist that should be carried out before the close is achieved. Automated solutions leverage orchestration tools to allow all these different tasks in the checklist, such as balance reconciliation and intercompany accounting, to be in progress.
9. Process mining
Process mining is an analytical tool that helps businesses understand and analyze the speed and efficiency of their everyday processes by detecting patterns in process event logs. It’s through process mining that businesses would identify the bottlenecks in their financial department that could be remedied with automation.
For example, in the purchase-to-pay process, it’s claimed that sourcing, procurement, and accounts payable have their own specific department, with each optimizing their functionality subjectively. Businesses can leverage process mining software to get a more accurate estimate of how long each purchase-to-pay cycle takes.
- Learn more about the use cases of process mining in finance.
- Discover how to use process mining in p2p and order-to-cash processes.
10. Web scraping
Lastly, automation tools are not only for back-end financial procedures. They can also be used for investment.
Let’s say a company wants to invest in a business or even a financial automation product. They can use web scrapers to scrape the internet for public reviews, prices, and capabilities of the product. Alternatively, they could scrape publicly available financial documents and other factors of interest regarding the investment project that they are interested in.
- Learn more about using web scrapers for investment.
For more on FinTech
If you are curious to learn more about the technologies being used in the finance sector, read:
- Real-Time Asset Valuation With Asset Accounting Automation
- Top 8 Chatbot Use Cases & Applications in Finance
- AI Credit Scoring Models: In-depth Guide [2022 update]
If you would like to leverage a FinTech solution for your business, we have prepared a data-driven list of vendors.
And if you believe your business would benefit from a digital transformation software, we have a data-driven lists of digital transformation consultants.
And we will help you find the best one suitable for your business:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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