Increasingly complex and volatile supply chains have put procurement teams under pressure to adopt more agile management processes using AI solutions.
Thanks to the increase in technology, today’s businesses have previously unprecedented opportunities to capture data across myriad digital touchpoints. That data is the key to making informed decisions instead of acting on emotion or educated guesswork. Moreover, data-driven insights can inform practically every business area, from marketing to procurement.
Unfortunately, translating data into actionable insights remains very challenging. The problem is the enormous scale of today’s data sets, which has far superseded people's abilities to make sense of them. We need modern solutions powered by artificial intelligence and machine learning.
What are artificial intelligence and machine learning?
Artificial intelligence (AI) and machine learning (ML) have become two of the most commonly used terms in computer science. Although they are often used interchangeably to describe an ‘intelligent’ software application, they are not quite the same thing. That said, they often work together to achieve a broader goal.
We can define AI as any system that performs tasks that emulate human intelligence, such as thinking, reasoning, or learning from experience. AI is the chief technology behind automation solutions, such as personal assistants or industrial robots. ML, on the other hand, is a subset of AI that deals specifically with learning from data rather than being explicitly programmed. Examples include product recommendations and email spam filtering.
How are these technologies changing fintech?
As a core component of any business, financial operations generate a wealth of valuable data. By leveraging AI and ML to analyse and manage such data at scale, finance departments and firms can make informed decisions at a speed that is simply impossible when relying purely on manual processes.
In finance, AI and ML have proven especially valuable in operations related to information security, fraud detection, credit risk assessments, and compliance automation, all of which are critical to procurement and other key business operations. The fintech sector is thus leveraging these technologies to enhance efficiency and make it easier to do business in today’s often unpredictable and rapidly evolving economy.
AI and ML continue to spread across other sectors, such as business process control and optimisation. It is already well-established in sales, marketing, and customer support due to its ability to make the entire customer journey faster, easier, and safer. This also applies to B2B transactions, where supply chains have become ungovernably large when relying on manual processes.
How can spend management software help organisations with the use of artificial intelligence?
Procurement is a vital part of any organisation, but evolving regulatory environments, a rising threat of cybercrime, and dizzyingly complex supply chains have made it notoriously difficult. To address these challenges, we need smarter solutions, hence why AI and ML are central to long-tail solutions like Mazepay.
Thanks to AI and ML, Mazepay can automatically read data from invoices, receipts, and other documents to identify trends and insights at scale to largely automate long-tail supply chain management while reducing risk. Mazepay also monitors transactions, using AI to identify those that may require manual review. It is a powerful long-tail solution for managing the bulk of procurement transactions.
In the future, we plan to implement guided buying for procurement teams. With guided buying, AI will automatically guide procurement personnel to best fulfil purchase requirements. In other words, it will further expand the ability of procurement teams to automate even more of their operations, thus freeing up time for them to focus on strategic supplier relationships.
Mazepay is an all-in-one enterprise spend management platform that significantly simplifies long-tail supply chain management. Get in touch today to find out more.
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