Artificial Intelligence and Machine Learning
are very hot buzzwords right now. To alleviate some of the confusion surrounding them, let’s make sure we’ve adequately defined the terms.
- Artificial Intelligence (AI). The broader concept of machines being able to make decisions and perform “smart” tasks that normally require human intelligence. This includes learning (the acquisition of information and rules for using that information), reasoning (using the rules to teach approximate or definite conclusions), and self-correction.
- Artificial Superintelligence (ASI). If AI is the ability of computers to mimic human thought, ASI goes a step beyond, where a computer’s cognitive ability is superior to a human’s.
- Machine Learning. A current application of AI based around the idea that when we give a machine access to data, it can continue improving its performance without humans explaining exactly how to accomplish tasks.
- Algorithms. A process or set of rules that describe how to perform a task, solve a problem or reach a specified goal.
How these technologies are being used
Accounting and finance have been leading the charge in leveraging AI and machine learning to deliver insights, inform decision-making, and drive efficiency. Here’s how it’s being used currently:
- Data security. Malware is a huge problem for IT departments everywhere. But the institutional intelligence company Deep Instinct says that malware tends to have much of the same code as previous versions. Only two to ten percent of the files change from iteration to iteration. Their software’s learning model can handle those variations and predict which files are malware with great accuracy. Other companies make use of machine learning algorithms to look for patterns in how cloud-based data is accessed. They can then report anomalies to predict and prevent security breaches.
- Fraud detection. Machine learning is getting better at spotting potential fraud. PayPal uses machine learning to fight money laundering. Their tools compare millions of transactions and can distinguish between legitimate and fraudulent transactions.
- Transaction coding. Accounting software providers are using machine learning and detailed statistical analysis to learn how a business categorizes its invoices so it can code transactions to the correct chart of accounts codes.
- Contract review. AI-based systems are cutting the hours it takes to review contracts in the finance industry. Software can now sift through thousands of commercial loan contracts. This can reduce the time taken by humans to do so from hours to seconds.
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