How Machine Learning Can Help You Achieve Your Financial Goals

You’ve undoubtedly heard a lot about AI in recent years, as it’s perpetually at the forefront of discussions about what can be achieved through technology.

To some, those two letters seem nearly magical: they envision the structure of the human brain recreated in electronic form (as in the above image) with massively expanded capabilities.

Beyond that, of course, they think about the practical and ethical consequences of a sentient AI, fearing something akin to Skynet.

That impression is hugely inaccurate, of course, because the type of AI that we can use at this point isn’t even close to that science-fiction concept.

It’s minimal, though that doesn’t detract from its power. It’s called machine learning: creating systems that can adjust what they do based on the feedback, thus imitating the learning process of an intelligent creature.

Machine learning is now used extensively throughout the world to automate and enhance valuable processes. Whenever a sequence can be clearly defined with results that can be analyzed, a machine learning algorithm can be created — and the financial world is full of such arrangements.

In this post, we’re going to look at some ways in which machine learning (the variety that’s already being used) can help you achieve your financial goals.

Let’s get started.

1. It can find you an outstanding mortgage

One of the biggest drains on the average person’s budget is accommodation, whether they’re paying rent or making mortgage payments.

In the long run, owning property is much more financially advisable than renting it because you gain an asset. Still, getting on the housing market (and not just when there’s a pandemic getting in the way).

Using machine learning can make it a lot easier to compare mortgage options.

The mortgage broker Breezeful does just that, factoring in your credit rating and considering offers from numerous providers to form the best array of options. Arranging an optimal mortgage can make a big difference to your financial situation, giving you more of a buffer to build up savings.

2. It can help you handle your spending

We don’t always make logical decisions regarding financing, even when we have great intentions. We’re just not great at keeping track of some things. It’s not so bad when you’re thinking about one big purchase, but all your everyday buys add up frustratingly.

How can you know when you should hold back and when you can afford to proceed?

That’s where you can take advantage of a service like Cleo, an AI-powered financial assistant that can answer your pressing money-related queries.

What can you afford to spend on food this week?

How much does an individual subscription cost you every year?

You can create specific financial goals that Cleo can help you pursue, telling you when to stop spending.

3. It can protect you from fraud

If you’re a regular consumer, only making payments (online or offline), then machine learning is already helping you in the background through the security systems devised by big financial institutions.

If you run a business that takes payments, though, you can significantly benefit from implementing an AI-driven system to protect you from fraudulent charges.

Consider a system like Ravelin: besides providing at-a-glance payment metrics, offering support from experts, and processing payments (if needed). It uses machine learning to predict and prevent fraudulent orders without you needing to do much. If you often run up against fraudulent payments that waste your time and mess up your stats, it might be the solution.

Conclusion

There are many other ways machine learning can assist with financial management: we’ve just looked at a few here. It could help with choosing investments, valuing assets, protecting supply chains, preventing cyber-attacks, etc.

It can also help you achieve your financial goals by offering automation in general — the less time you spend on your everyday tasks, the more efficiently you can work, and the more money you can make.

Based on what we’ve discussed here, think about how you might take advantage of machine learning. The industry is only getting bigger, so it’s something you’ll need to consider sooner or later. Why not make a start now?