Using next-gen PFM to reinvent your relationships with customers

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Winning the customer of the future will require a level of personalisation and insight that doesn’t currently exist in banking. But it’s coming – and we’re building the platform that will deliver it. This next generation of PFM uses machine learning to offer tailored, prescriptive advice that guides customers to the financial future they envision – and creates long-term relationships.

It wasn’t all that long ago that bankers and customers had a relationship, one that would continue for decades – through moves, marriages, children, divorces, lost jobs, new jobs, retirement. Digital has largely erased that it – and that’s a good thing. Smartphones have replaced that connection, and if customers want a better experience they can simply jump to a new service that offers it.

Personal Finance Management (PFM) services are a prime example, categorising a user’s financial data and offering insights to help them better understand and manage their money. It pulls all of their accounts into one multi-banking app, where they can do everything they would have done at a bank – pay bills, make transfers, save money.

All of this is great for consumers but it’s erasing the banks’ competitive advantage, since the technology is out there to allow any player to offer these services – bank or not. So when everyone offers the same product, how will you differentiate yourself?

PFM of the future is personal and prescriptive

Winning this new game is about winning back customer loyalty. One of the ways to do that is using the next generation of PFM service – and the relevant, actionable, data-driven advice it will offer – to re-establish the relationship between banks and consumers.

People are still people; they want personalised services, advice that guides them to their financial goals – and they want to feel that whomever (or whatever) is providing it is acting in their best interests. PFM today doesn’t do that – it looks back instead of forward; it summarises instead of synthesizes; and it offers static advice based only on financial behaviour.

The PFM of the future – the one we are developing – offers advice that’s personal, predictive and, most importantly, prescriptive. It will use Actionable Insights – bite-sized insights powered by algorithms that continually learn from a wealth of financial data, user preferences and recurring behaviour to help people optimise their finances, one step at a time.

When you can steer your customers to better financial health with advice and insights that are tailored to some of the most personal, high-stakes data a person has (their finances), your offer will have something that no one else’s has – the human touch.

There are a lot of PFM services out there, but you need one that creates long-term relationships with your customers – and makes them feel understood. Here’s how we plan to do it:

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Step one: Start off small

Trust falls are simple tests – one person falls back and expects the other to catch them. When they do, they can feel confident that next time the other person will catch them again. It’s the same idea with Actionable Insights.

Customers have a feed, let’s say, and are asked to respond to a couple of actions or insights on a regular basis. In the beginning, they’re simple: we see that you paid an insurance bill – was this for your car or home? They engage when they feel it’s relevant – and it creates a gratification loop that primes them to respond to the insights you offer next time.

This relevance is what builds trust in the service over time – and allows you to deepen the relationship.

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But these small steps in the beginning will also create a valuable feedback loop for Tink – and your bank. We’ll be able to see based on a user’s engagement what they care about, with every action – or lack of it – providing input on their preferences. Maybe they get an insight about paying a high interest rate on their mortgage and decide to challenge it. Or they ignore an insight about opening a savings account to put away 10% of their income.

Their financial behaviour is just one factor. It’s how the user interacts with the product that determines what’s relevant for that particular person. This kind of data can help create a solid profile of each user so the feed is adapted to them – resulting in relevant, personalised advice.

Step two: Give the best advice

Simple PFMs can see if a user is keeping money in a savings account with no interest, and guide them to a better investment. But the future of PFM that we envision is using a machine-learning algorithm that works continually to understand a customer’s broader financial picture – and offer advice that is tailored specifically to them.

Say they want to buy a holiday house. Instead of helping them reach this goal in a set period of time and socking away money each month, we can analyse their spending, how successful they’ve been meeting their goals in the past, and how much money they have left each month. Then we can determine if their goal is a realistic one – and make it clear what steps they need to take to achieve it.

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Like having a coach, Actionable Insights will be able to draw conclusions and offer advice that truly reflects the customer. And we can do this because we have their full financial picture with aggregation. When they enroll through a bank’s app, they should feel confident that it will tell them what will happen going forward, guide them in the right direction – and give them the means to do something about it.

Step three: Solidify the relationship

The effect of building trust through small, steady actions and following that up with concrete advice that’s highly individual is a relationship – and one that’s much better than the old banker/customer one. They get a best-in-class financial advisor – and tools that do the heavy lifting, analysis and optimisation of their finances long term. Their only job is to make the final call: yes or no.

It’s a relationship that makes them more likely to use your PFM and the financial services you offer. Because when the connection between you feels personal, your offer is much harder to ditch. Think about it like a relationship with a therapist – when so much time has been invested and information shared, you stay because you get honest and trustworthy advice that puts you on a better path.

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With more customer trust, you can even put some Actionable Insights on autopilot. If you really know your customers, you can automatically set up budgets and notify them. Or you can auto-generate low-balance warnings based on past behaviour rather than asking them to set it. You’ll be building these valuable relationships and improving their financial health on autopilot too – imparting the feeling that your advice is even better and more personal than it was yesterday.

This future isn’t here yet, but it’s coming. And we’re building it. One with deep relationships built through automated and data-driven advice that truly makes customers feel listened to and cared for.

As the power balance moves even more from banks to customers, it’s vital to offer the best advice and the best experience to keep winning business – and hold onto it.

All mockups are examples only.

Isabelle Österlund