Can AI help you manage your personal finance?

Theodore Twombly walks through a crowded city, speaking softly into an earpiece. There is no screen, no interface, just the voice of Samantha, an AI operating system. She listens, organises his day, manages his e-mails, even senses his moods before he fully registers them himself. The scene, from Spike Jonze’s Her – starring Joaquin Phoenix and the voice of Scarlett Johansson – felt like a portrayal of a distant future when it was released in 2013. Just over a decade on, that distance has narrowed. AI is no longer a future-facing experiment – it is infrastructure.

In Singapore, more than $1 billion is being invested into AI, embedding it into systems that shape how the country runs and plans ahead. AI-powered tools are also finding their way into mainstream conversation, often through social media, where creators increasingly frame automation and optimisation as part of everyday money management.

So how much can AI really help with personal financial decision-making, from budgeting to tracking and managing everyday spending?

How to use AI for personal finance

At its core, managing money comes down to behaviour – habits, discipline, emotions and priorities, says Reginald Koh, founder of The Financial Coconut, Singapore’s first personal finance podcast network. “It begins with a goal, an awareness of where you are, reframing the mind, discovering the habit that can get to your goal, then rinse and repeat until it sticks,” he adds.

Where AI – and even earlier intuitive automation tools – can help is to streamline the mechanics. “On a personal level, basic budgeting automation is still good enough,” says Reginald.

As Daan van Rossum, founder and CEO of Lead with AI, states: “AI makes us five times more efficient. It handles repetitive tasks, freeing us to focus on creativity and strategy.” However, he warns against complete reliance on AI for anything financial. “My advice is to build an AI assistant on a platform you trust, such as ChatGPT or Claude, and keep the data secure.”

In practice, this positions AI as a controlled assistant rather than a decision-maker – useful for consolidating information, identifying patterns and surfacing insights, while keeping control firmly with the user.

Levelling up with AI

Where AI may begin to differentiate itself is not in day-to-day budgeting, but in how it processes and connects information over time, say experts.

“Beyond the obvious use cases, AI can help demystify areas that are typically opaque, such as insurance. By layering data sets, it becomes possible to estimate a ‘fair value’ for premiums, giving individuals a clearer sense of whether they are overpaying, underinsured or adequately covered,” shares Reginald.

The adeptness of AI in parsing large volumes of information becomes more compelling when extended into investments. Voices such as Sonia Shenoy (@_soniashenoy), The Weeblings (@theweeblings0) and a growing regional cohort of financial content creators are bringing markets, money management and digital tools into everyday conversation, making once-specialised insights far more accessible.

Financial institutions are already building AI into the way customers interact with their money – not as a replacement for decision-making, but as a layer of guidance. This could improve the “nudging process” for the broader middle group of people who are not financially savvy, says Reginald.

As AI becomes more embedded in personal finance, the conversation shifts from capability to trust. As Reginald puts it: “AI is fundamentally built on the inputs we feed it with, and in the realm of engaging professional services, are we going to provide AI with the full picture and blindly follow whatever it says?”

Rather than defaulting to blind trust, users can anchor themselves in existing guard rails. Frameworks set by the Monetary Authority of Singapore, alongside industry bodies like the Life Insurance Association Singapore and Investment Management Association of Singapore, as well as the Consumers Association of Singapore, offer a clear reference point for navigating AI-enabled financial tools with greater confidence and accountability.

Using AI to influence spending behaviour

Money decisions are often assumed to be rational, but research in behavioural economics shows they are largely driven by emotion. Can AI meaningfully influence behaviour?

“I believe it can, but you will need to feed it with more information,” says Reginald. With tools like Hume AI or other bio-data devices, if users allow access, AI could “read your pulse, your heart rate and proxy data that shows a certain emotional reaction”, and respond in real time – whether by blocking payment features, sending prompts, or even locking your phone so that you can “break the action”. In doing so, it creates a buffer against impulse, helping to ensure that you don’t make emotional decisions in the moment.

Another way of deploying AI into personal budgeting is by letting it read years of budgeting data. “It should be able to derive insights on how your spending patterns have changed over the years, marry that with your changing life circumstances and some form of well-being framework, and potentially inform you on where you should spend more to spark joy, where you are doing too much, and essentially list a few parameters to enhance overall well-being,” explains Reginald.

This is perhaps the closest real-world parallel to the intelligence imagined in Her – not just a system that tracks or predicts, but one that understands context. Even as adoption accelerates, the line is clearly drawn: AI is meant to support human decision-making, not replace it.

The difference, for now, is that unlike Samantha, it still requires us to decide what to listen to – and what to ignore.

AI tools for smarter money management

• Seedly. A home-grown platform that aggregates accounts and categorises spending, with the added layer of community-driven insights. It is particularly relevant for Singapore users, though bank integrations can occasionally be inconsistent and the interface less refined than some global counterparts.
• DBS digibank. One of the most advanced local banking apps, with built-in AI features that automatically track and categorise spending, while offering personalised nudges. It works seamlessly within the DBS ecosystem, though its functionality is largely limited to DBS accounts and offers less customisation than standalone tools.
• OCBC Digital. A clean, intuitive app that provides useful breakdowns of spending and cash flow, helping users manage their finances more effectively. While easy to use, it offers fewer advanced analytics and limited visibility across accounts outside the OCBC ecosystem.
• YNAB (You Need A Budget). A global budgeting tool centred on intentional spending, encouraging users to assign every dollar a purpose. It offers detailed insights and a strong behavioural framework, though it requires more manual set-up for Singapore users and operates on a subscription model.
• ChatGPT/Claude. Not purpose-built finance tools, but increasingly used as personalised assistants, analysing budgets, summarising expenses and identifying patterns when given the right data. They are highly flexible and powerful, but require manual input and depend on users to manage data privacy carefully.