Did you know McKinsey says financial services leaders can fully automate 42% of your finance activities—and mostly automate 19% more? That’s big news if you’re looking to de-risk important decisions by improving the speed and quality of your financial reporting and controls. But to do it effectively and efficiently now and in the future, you need to understand which kinds of financial automation are right for you.

The 3 main types of financial automation

1. Robotic process automation (RPA)
Companies use robotic process automation (RPA) to build, deploy and manage software robots (“bots”) that emulate how humans interact with software and digital systems. It’s a way to more quickly and consistently complete easy, mundane, repetitive tasks and processes like logging into IT systems or copying and pasting structured data across systems.
RPA is based on “if/then” rules—“If true, do ABC. If false, do XYZ.” That means it can’t “learn” on its own; if you need to rename
a form field or change a data source within a specific task, for example, you will have to reprogram the tool, so it functions as desired.

2. Machine learning
A type of artificial intelligence (AI), machine learning (ML) uses data and algorithms to imitate the way humans learn. It uses image recognition to automatically identify different types of documents (e.g., timesheets vs. expense reports vs. invoices) and process electronic documents.
Unlike RPA, ML’s accuracy improves as it learns without anyone explicitly programming it to do so. Amazon, for instance, uses ML to automatically recommend books to you based on what you’ve viewed or purchased.

3. Artificial intelligence
Gartner defines AI as advanced analysis and logic-based techniques used to interpret events, support and automate decisions, and take actions. AI thinks and learns from data patterns and its own mistakes, getting smarter and making more accurate predictions over time.
Artificial intelligence is the only way to automate more complex, human-like actions, such as classifying ambiguous unstructured data, matching transactions and detecting outlying data points. Its power and potential are largely why 73% of CFOs surveyed at the Gartner CFO & Finance Executive Conference and the CFO Leadership Conference said a vendor’s AI strategy and roadmap is an important/very important factor they consider when purchasing a financial management system.

How the 3 types of automation relate and compare to each other

All three types of automation can simulate human behaviour, but only ML and AI can learn as they go. And only AI can mimic or simulate human thought.
You can think about RPA, ML, and AI as an automation continuum where RPA represents the first level of advanced automation capabilities and AI represents the most advanced.

McKinsey has identified some of the financial tasks that lend themselves to automation, which include the following:

Accounting
Automating complex journal entries
Performing account reconciliations
Managing and applying allocations
Maintaining fixed-asset accounts

Accounts Payable
Entering unstructured data
Performing two or three way matching
Processing expense-approval requests
Completing AP audits

Accounts Receivable
Generating and validating invoices
Applying cash
Analysing and processing disputes
Creating reports

Financial Analysis and Planning
Building standard reports
Consolidating and validating budget and forecast inputs
Gathering and cleaning data for analysis

Payroll
Flagging time-sheet errors and omissions
Auditing reported hours against schedule
Calculating deductions
Matching data across multiple systems

Spotlight: Detecting Outliers Using AI

Artificial intelligence is particularly impactful for finance professionals when it comes to the renowned, tedious task of outlier detection…

Find out more by downloading the whitepaper below.

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