Smarter spending insights, powered by AI

Most people do not want a dashboard with forty charts. They want a clear answer to a simple question: where did my money go, and is anything off. That is the problem we set out to solve when we added AI to mightbank. The goal was never to impress you with the technology. It was to make the everyday work of understanding your spending faster, calmer, and more accurate.

mightbank is a financial technology company, not a bank, and we move money across 30+ currencies in 180+ countries. That scale produces a lot of transactions, and transactions are messy. A coffee in Lisbon, a subscription billed in dollars, a refund that lands a week later under a different merchant name. AI is genuinely good at making sense of that mess, and that is exactly where we have chosen to use it.

What the AI actually does

Three things, mainly. It categorises transactions automatically, so a payment to an airline lands under Travel without you tagging it. It powers an in-app assistant you can ask plain questions, such as how much you spent on groceries last month or whether a recurring charge went up. And it surfaces insights you did not ask for but probably want, like a flag when a free trial is about to convert to a paid plan.

These features are designed to reduce work, not create it. Categorisation runs quietly in the background and improves as you correct it. The assistant answers in your language and points to the underlying transactions so you can check its working. Insights are framed as observations, not instructions, because the decision is always yours.

• Smart categorisation that learns from your corrections and respects manual overrides
• An assistant that answers spending questions in plain language and links to the source transactions
• Proactive flags for things like upcoming renewals, unusual charges, and duplicate payments
• Multi-currency awareness, so converted amounts are shown alongside the original, with FX from 0.2%
• Monthly summaries that compare against your own history rather than someone else's benchmark

What it does not do

It does not move your money, approve payments, or make financial decisions for you. The AI can highlight that a subscription has increased, but it will never cancel it on your behalf without an explicit action from you. We have kept a human-in-the-loop principle at the centre of the design: the model suggests, you decide, and anything consequential requires your confirmation.

It also does not promise returns or steer you toward products. Where our Earn feature appears in an insight, we are clear that yield is variable and not guaranteed. We would rather show you a slightly less exciting screen than imply a certainty that does not exist. There are no rewards or cashback claims woven into these insights, because that is not what they are for.

Good financial AI should feel less like a robo-advisor and more like a sharp, honest colleague who shows their working and never spends your money for you.

How we keep it explainable and private

Every automated category and every insight can be traced back to the data that produced it. If the assistant tells you that dining spend rose by a fifth, you can tap through to the exact transactions behind that number. We avoid black-box outputs precisely because money is the area where people least tolerate being told to just trust the machine.

On privacy, the principle is restraint. We process the minimum data needed for a feature to work, we do not sell your transaction data, and you can turn AI insights off without losing access to your account. Models are used to interpret your activity for you, not to profile you for someone else. When we are uncertain, we default to showing less and asking before we infer more.

Where this goes next

The version available today is deliberately modest in scope, and that is by design. We would rather ship features that are accurate and explainable than features that sound impressive in a launch post and frustrate you a week later. Categorisation, the assistant, and clear monthly insights are the foundation, and they will keep getting more precise as the system learns from real corrections.

As we expand, the rules stay the same: the AI assists, you decide, and the reasoning is always visible. If a feature cannot meet that standard, it does not ship. That is the quiet contract behind smarter spending insights, and it is the part we are most committed to keeping.