How to use APIs to help your customers see the future
Data modelling & machine learning offers a tantalising possibility - that by gathering enough data inputs you can predict what will happen in the future based on current information. ML Models are commonly used in the context of business decisions, such as assessing investment outcomes or growth performance, where they can add significant value.
They’re rarely used in the realm of human experience for two main reasons. Firstly, humans are famously irrational and hard to predict using the few data points available. Secondly, the cost of traditional data modelling means that it only makes economic sense in a business context.
But easy-access APIs are changing both of these to provide more data and improve model accuracy. To see why, we’re going to talk about babies.
A £150K Baby
Before having kids, Andres Korin thought he was good with money. But this went out the window when he and his wife had their first child. As he explained by his business partner Bruce Pannaman at a recent Finastra developer meetup, babies are extremely expensive, costing on average £150K over their lifetime.
The pair decided to do something about this and so StorkCard, a financial planning platform for parents, was born. One of the key goals was to make the process of parenting more transparent.
StorkCard helps parents predict child related costs going forward years in advance, based on their financial data and the budgeting and family lifecycle data on their platform, so they know what is going to happen in advance. This in turn, helps reduce debts from surprise costs while also enabling StorkCard to cross sell different financial products to help parents plan ahead. And all their predictions are based on API data.
The API Crystal Ball
Data modelling is most effective when tracking repeatable systems. While humans themselves can be hard to predict, they do operate within plenty of repeatable systems. Think of a small business, with tax deadlines, busy and quiet seasons and staff holidays, for example.
StorkCard applies this thinking to the lifecycle of a child, looking ahead to clothing costs, big ticket items such as prams and cots as well as childcare and education fees so parents can plan ahead, while also matching it with insights on other parents’ past spending.
While humans are theoretically capable of planning this, the time and effort it would take to gather all the data and process it means it’s not worth the trouble. With APIs, however, it’s instant. Your app can quickly gather all the data your customer needs to make a decision and either present it for their review, or make the calculation for them.
Data Solutions for Human Problems
The world is full of problems that could be solved with the right data. Most people just don’t have the time to do the research, testing and computation they would need to achieve this.
Plug-and-play APIs open up the field of app development by drastically reducing the cost of app development so you can focus on solving specific issues. The wide array of financial data now available can transform the experience of users if it’s combined in the right way to suit their needs.
For StorkCard, they could bring together:
- Parental spending data
- Key milestones in a child’s lifecycle
- Average costs from other parents
- Live prices of relevant goods and services
For a parent getting little sleep for the first year of their child’s life, the app can do the financial thinking for them.
Closing the data gap
The goal is to close the data gap - a combined set of inputs that, combined with the right personalisation - give users the information they need to plan for their future, now.
By finding the right API data sources and matching them to a human experience, you can close that data gap to help your customers see the future.