Spenny is a budgeting software that looks to use statistical analysis and macroeconomic data to guide spending and saving decisions to help you control your future.
What it does
Some applications can create budgets but don’t guide consumers into deciding how much to save. Spenny fills the gap by giving more effective suggested budgets based on macroeconomic data. The use of this data means budgets are better tailored to the economic climate.
Who would use it
There are a vast range of uses for Spenny. For example, it could be used by anyone who needs help in planning for the future. In general, households may be unaware of what most people in their earnings situation and region spend. This could affect immigrants who are new to the country and are becoming familiar to differences in cost of living, particularly entrepreneurs. Spenny will allow them to make more informed purchasing decisions -- in future, could be expanded to SpennyBusiness: business level budgeting for inputs purchases. We have made a particular effort to be inclusive with regards to visually-impaired people: by using Nexmo’s API to develop a call-based data input for the service.
Data Sources & Methodology
One source was an OECD database of real short term interest rates including a one-year projection. This was used in order to build savings function: the savings function estimates real interest rates for up to a 5-year period by polynomial regression on the OECD data in order to allow consumers to accurately adjust savings decisions. More specifically, one's total savings increase by both how much is saved each week but also by the effect of inflation-adjusted interest on savings that they already possess.
A second source was ONS data of the Family Expenditure Survey for 2017-18. We examined expenditure habits across: income deciles (10% segments of society by dispoable household income) and different regions e.g. Northwest England or Greater London (tpeople living in different regions). We processed individuals’ data to give information about their budgets in terms of their expenditure on the most commonly-consumed 650 goods in the UK.
Challenges we ran into
We could have made use of Nexmo's API to allow full use improved accessibility features: such as audio input of information as well as output of budget details Add facilities to track payments Could implement Monzo’s API for logging of expenses Could also connect to a consumer’s banking services to do this in real time Adding more visualisation techniques for the budget eg more graphs Adding multiple savings goals at the same time, for named projects Adding multiple expenditure levels: “Frugal, Moderate, Spenny” affecting higher spending
Access to Raw Data for FES Survey would allow inclusion of more complex budget factors: Current data accounts for approximately one representative individual but income could be “equivalised” to include the effects of multiple dependents and earners in a family on standard of life and, accordingly, budgeting.
Data has already been equivalised so this is not currently feasible, as the process cannot be reversed with the available information about household composition. This would remove the need to infer which factors affect expenditure habits: all 26000 households could be examined and we would not lose accuracy caused by having access to data only relating deciles or only averages of regional income As the averages had to be used, this may have led to loss of accuracy. However, this data was inaccessible to us as it requires a human response time from the UK Data Archive, which meant it was infeasible in the time frame of Hack The Burgh V.
Access to better actual macroeconomic projections from think tanks would be ideal in forecasting future real interest rates, but might need to be commissioned; we did not have according funding for this.
Accomplishments that we're proud of
Three of our main targets of this application were to improve diversity and increase minority entrepreneurs' representation across the UK; promote inclusivity of those with different accessibility needs; create an intuitive and useful financial app. These targets relate to several targets respectively.
BlackRock and Functionality
Best financial hack: helping people from all walks of life better understand how to budget and save in any economic climate. We make use of sophisticated statistical and macroeconomic data to allow individuals to contextualise their spending.
JP Morgan and Diversity
Improving diversity by helping acclimatise immigrant populations to local market prices, and this could be marketed specifically to immigrant minority entrepreneurs through British consulates and embassies when individuals make visa claims as businesspeople: eg Tier 1 (Entrepreneur) visa
Nexmo and Accessibility
Inclusivity of visually-impaired people by allowing them to use audio input for data on the site and reading out budgets
What's next for Spenny
While there is plenty we want to pursue, we are already very excited with the stage of Spenny: it is intuitive, intelligent and effective. As time constraints lift we will be able to implement all the changes we have mentioned and hopefully we will eventually be able to help you Fly To Your Financial Freedom.