JPMorgan’s Global Think-Tank Uses Big Data To Read US Economy
By Megan Murphy
May 20, 2015 — For decades policy makers and economists have sought data that would allow them to better understand how changes in financial behaviour affect the economy. Now they are getting a boost from a new and unexpected research partner — JPMorgan Chase.
The bank launched a global think-tank this week — the JPMorgan Chase Institute — aiming to combine the power of big-data analytics with information culled from 30m of its own customers to build a more granular snapshot of the US economy.
Mapping financial shifts in real time has long been considered a holy grail for policy makers looking to respond more effectively to the ups and downs of an economic cycle. But the data on which they rely are often extrapolated from recurring public surveys and government records.
What if they had access to the actual daily transactions of tens of millions of Americans?
For its debut report, the institute analysed the income and spending habits of 2.5m account holders over a more than two-year period between 2012 and 2014, to gauge how individuals responded to earnings fluctuations on a weekly and monthly basis in the wake of the financial crisis.
As has been widely feared by economists, the study shows that far too few US households would have enough savings to weather a large unexpected expense — such as a medical bill or a household repair — at the same time as a significant loss of income.
The institute found that while the typical middle-income family would need a "buffer" of about $4,800 to sustain the kind of monthly fluctuations in earnings seen in its account sample, that level of savings is unavailable to all but the highest earners.
In fact, while the median household holds about $3,000 in assets that could be tapped, the lowest-income households would probably have to take on debt or liquidate some of their assets to deal with a significant loss of earnings in the same month as an unexpected expense.
But perhaps the report’s most surprising finding is just how volatile households’ income and spending habits are at both ends of the wealth spectrum.
Policy makers have long tried to model how vulnerable low-income families are to financial shocks in trying to develop social programmes that can help prevent households from tipping into a crisis when faced with a single unexpected event or expense.
However, the institute’s data show that households in the highest income quintile experience just the same high levels of both income and spending volatility as the lowest-earning households.
For example, individuals at the bottom end of the income spectrum of the sample — those earning less than $35,300 — experienced near double-digit jumps in their monthly income 25 per cent of the time and equally large drops another 25 per cent of the time.
But those month-to-month swings were even wider among top-earning account holders — those with incomes of more than $100,000. Across the sample, individuals in every income quintile experienced significantly more volatility in consumption than in income, with spending and earnings frequently not moving in tandem.
What those data suggest is that while financial shocks may be more disruptive for low-income families, no earnings group is immune to the impact of such fluctuations.
"How exposed are individuals to income and consumption volatility over time? Do earning and spending patterns differ across the income spectrum? How much of a financial buffer do households need to weather their exposure to volatility?" said Diana Farrell, the woman who was brought in to head the institute from Mckinsey’s centre for government.
"With this kind of analysis, the institute will be able to answer the questions to help policy makers make more informed decisions."
The institute’s use of customer data is unlikely to be free from controversy, given the negativity still surrounding the banking sector and JPMorgan’s involvement in an array of scandals that has cost it more than $20bn in fines in recent years.
JPMorgan says strict privacy protocols have been put in place to safeguard its customers’ privacy.
For example, before the institute receives any data, all unique identifiable information — including names, account numbers, addresses, dates of birth, and social security numbers — is removed.
Only aggregated data — rather than individual — can be published.
The bank also acknowledges that its data set is skewed away from America’s poorest households, many of which remain effectively unbanked. Account holders included in the sample must have $500 in deposits every month and hold a credit card from the bank. The sample is also limited to a geographic footprint of the 23 states where JPMorgan Chase has physical branches.
But it will be a closely watched project, and one that ultimately may be able to provide a more data-rich analysis of economic shifts as they happen.
From the Financial Times. May 20, 2015. JPMorgan’s global think-tank uses big data to read US economy. Megan Murphy.
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