The Personal Financial Management is software that enables customers to manage their finances. This blog explores smart spending analytics in PFM and how revolutions in the field of data have enabled customers to manage their spending using such tools.
An overview of change in PFM
We live in a world which is drowning in data. And making sense of this data gives power as it gives insights into hitherto unknown answers. However, is this data powerful enough to enable a rebirth of PFM tools? PFM tools are not new and have been around for about three decades. When the idea of PFM first came up, it received a lot of attention but early PFM tools did not gain widespread adoption due to their complicated and fussy features. The share of PFM users was only till recently, around 10 –12 percent. The answer to the question is a yes. Revolutions in data have enabled the resurrection of PFM into a completely different form.
A new way of money management
In the coming years, millennials are going to inherit the largest share of personal wealth and their annual spending would be unprecedented (about 1.3 trillion dollars). Nevertheless, according to statistics, only 53 percent of them would budget their future expenses and of those who do, 36 percent would use manual tools like spreadsheets. This involves a lot of manual effort which could be easily solved using PFM tools. Recent advances in data analytics are a perfect solution to these challenges.
Advances in AI and ML have enabled a new form of PFM. The ideal PFM software should be able to recognize patterns in spending habits of the customers and give timely insights wherever needed. Frankly, which millennial would want to look at charts and graphs and figure out how much and where to spend? New versions of PFM would give alerts to the customer whenever they have spent too much like on eating out, taking Uber too much, etc. This is certainly possible and is being implemented in the new PFM tools and also bank apps which have integrated PFM into their products. The ideal PFM software would also identify periods of excess spending like Christmas, New Year etc.
Alerts when needed
Barclays, in spite of being one of the oldest banks around, integrated PFM with advanced analytics which can define long term spending and saving goals such as buying a house or a car, etc. The smart spending feature of PFM should be able to give alerts when appropriate and turn off entire spending categories for budget conscious customer such as gambling or online shopping. This could even be helpful for customers battling serious debt or financial control issues. This system of smart PFM could certainly bring about a change in the smart spending analytics in PFM and be a game-changer in the industry. Banks like Bank of Georgia and Barclays are examples of real-world instances of smart spending analytics in PFM.
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