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Planning your financial future is for a lot of people, not the most engaging activity, especially for further future situations. For students and people at the beginning of their career, this is, even more, a distant future. Planning can however help to guarantee unpleasant surprises. Financial service providers and especially pension providers aim to help people to plan their financial life healthy by offering tools for planning ahead. These tools are however financially focused and based on straightforward financial models. Would it be possible to use the new technologies of machine learning and AI, combined with networked services, to define a financial scenario that better represents the future?

Predictive knowledge in networked products

In the model of predictive relations, a research topic within Cities of Things Lab, we aim to generate insights on future behavior by using the characteristics of networked products that can embed the knowledge of similar situations in the network and predict the behavior of the action in the now. In this approach, the future is not predicted by forecasting a future life as a fortune teller, but the hypothesis is that there are always comparable situations elsewhere that can be seen as a future situation. As both the used product, as the product with a comparable future situation are in the same network, the comparable future becomes available as predictive knowledge in the use of the product. The focus is here on the interactions of the user and the product.

In the case of pension planning the product is a composition of your life; what are the choices you make in certain situations. It is the expectation that this method of mirroring future interactions can be a base for understanding future life profiles. This principle might be a method for generating predictive knowledge in understanding future life situations that are the basis for profiling pension. There is a larger gap than usual between the current and predicted situation, there might be a special approach needed for matching the profiles. Next to that in more general terms, it is interesting to understand if introducing predictive knowledge gives the user of the pension planner more trust in their choices.

Designing trust in future planning

What is needed to trust this designed future? How can this be a co-designed future with intelligent technology? Can the future made tangible to increase trust?

These questions are the basis for this graduation project. Can you design a planner based on a simulation of the future that uses networked predictive knowledge that really maps on your current future?

In this project you work together with pension organization PGGM and the Cities of Things Delft Design Lab of industrial design. The project will be based on research through design approach and use co-design methods to design together with the end-users a planning workshop to match predictive knowledge in the current planning decisions.

For this graduation project we are looking for a student that likes to explore future finding methods with service design practice. We expect that workshops with the target group (students) are an important part of this project.

Lab Director
Iskander Smit