Financial decision-making and the role of financial technology
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Date
01/07/2020Author
Lukas, Marcel Fabian
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Abstract
The overarching theme of this thesis is: "Financial Decision-Making and the
role of Financial Technology”. The thesis uses new forms of data to test existing
assumptions in the areas of behavioural and household finance. It improves our
understanding of how we can use technology to debias financial decision-making. The
thesis is based on three academic journal articles, each answering an individual
research question.
The first paper: “Transparency and Investment Decisions” analyses a novel
data set from a social trading platform called wikifolio.com. The users of this platform
create equity portfolios and by showing their complete trading history as well as all
current holdings, try to convince other users to invest money into their own portfolio.
Using proprietary data from this social trading platform, I follow a difference-in
differences approach, analysing trading behaviour within and between portfolios as
they become publicly visible. Portfolio managers on this platform go through three
different stages of trading. Each phase is characterised by an increased level of
transparency towards potential followers of the portfolio manager. In the last phase,
the investable phase, all past trades and all current holdings of the investor are visible
to the public. I find that the tendency of investors to forgo loss realisation in favour of gain realisation, known as the disposition effect, is considerably reduced in a
transparent trading environment, i.e., when investors move through the phases. I find
strong presence of the disposition effect in my sample, consistent with prior literature,
but, I also show that the effect diminishes by about 36% when holdings and trades are
publicly revealed. My findings are robust to survivorship bias, learning, and level of
assets under management. This significant reduction in the disposition effect
highlights the role of saliency and transparency of information in investing.
The second and third chapter use data from one of the UK's largest banking
transaction aggregation app, Money Dashboard (MDB). The data set is comprised of
approximately 400 million banking observations from more than 300,000 individuals
based in the UK. The transactions are automatically tagged by MDB with the type of
expense (groceries, mortgage payments, dining and drinking, etc.). In addition, user
login data and demographic data such as gender, age, income and address are stored.
Since MDB collects historic data once users sign up, banking transactions are available
for up to one year before an individual joined this service. This allows the present
research to compare user behaviour before and after joining MDB. One of the
functions provided to users is a budgeting tool. Users can set budgets for 270
categories and MDB automatically tracks and allocates their expenses to the individual
budget.
The second chapter titled: "The Influence of Budgeting on Spending” uses data
from the budgeting tool and analyses the effect of spending goals on spending
behaviour. This study is the first in the field to examine the influence of budgets on
consumer spending using real world budgeting and spending data. The data reveals
that budget compliance is weak: on average, consumers spend 21% more than they budgeted. On the other hand, the data also suggests that budgets do influence spending.
Average spending in the month after budget creation is 11% lower than pre-budget
spending. The effect is stronger for those users who log in frequently. The effect is
surprisingly persistent; six months after setting a budget, spending is still significantly
lower than pre-budget levels. These within-subject results are further supported by a
quasi-experimental propensity score matching procedure that compares the spending
of consumers with budgets with consumers without budgets. Taken together, these
findings provide evidence that the influence of budgets on consumer spending is
economically meaningful when actively tracked.
The third chapter, "Payday - Dashboard Effect on Consumption Smoothing",
studies the extent to which individuals are smoothing their consumption across the
month. Economic theory suggests that the timing of a predictable future income should
not influence the way individuals spend on that particular day. In contrast to this, I find
that individuals spend 53% more on discretionary items three days after payday than
they do during the rest of the month. This effect is commonly known as the payday
effect. It seems that additional saliency of historic and present transactions helps
individuals to smooth their consumption. Average spending for discretionary items
was on average 65% higher around payday before individuals joined money dashboard
and only 50% higher than usual after they joined.
Once users frequently check their financial situation, they significantly change
their spending behaviour and show smoother consumption patterns. This suggests that
increased attention on spending patterns supports consumption smoothing. I find that
if users log in once per month they only spend 28% more on discretionary items three
days after payday and only 21% more if they log in at least six times in the respective month. However, only limited learning seems to take place, with users reverting to old
habits of increased spending activity around the payday once they stop logging in.
These findings suggest that once individuals pay less attention, they start spending
more money on discretionary items. These findings contribute to the public debate on
whether financial technology can help improve consumer financial decision-making.
It also contributes to the neo-classical economic theory and suggests that individuals
might require additional support structures to ensure smoothed consumption patterns.
Overall, this thesis contributes to the behavioural and household finance
literature by providing large-scale evidence for behaviour change after introducing
new forms of financial technology. It explores three main areas of financial decision
making: investing, budgeting and spending. While biased decision-making may
persist, the thesis suggests that financial technology may be helpful in improving
individual financial decisions. It appears that especially the framing and saliency of
financial information supports behaviour change, but only if individuals pay attention.
This thesis also informs policy makers and financial technology companies by
showing that increased saliency and transparency of financial information helps to
debias decision-making. Policy makers might want to use these insights and make sure
that financial information from financial institutes has to be provided in a more salient
way by aggregating the required information disclosed to clients. In addition to this,
debt management programs and similar advice agencies might want to use the
presented insights and ensure that their clients use financial technology to better
understand their past and present financial decisions. The present results in the thesis
suggest that financial technology, if used sensibly, might help individuals improving
their investing, budgeting and spending behaviour.