Wall Street bank JPMorgan Chase has unveiled a new think tank that will use big data analytics to help better understand how changes in consumers' behaviour affect the US economy.

The organisation introduced the JPMorgan Chase Institute earlier this week to combine the power of big data with information taken from its 30 million customers to develop a more granular snapshot of the economy, the Financial Times reports.

It was noted by the publication that the ability to map financial shifts in real-time has long been considered the 'holy grail' for policymakers when they are looking to respond more effectively to ups and downs in the wider economy. This has been difficult to achieve in the past, as the only data available has to be extrapolated from sources such as government records and customer surveys.

However, the ability to access the actual daily transactions of tens of millions of users, coupled with fast real-time analytics technologies, can finally give economists the insight they have been demanding for years.

Head of the institute Diana Farrell, who has been brought in from McKinsey's centre for government, explained there are a wide range of questions that the technology will be able to provide insight on.

For instance, she said: "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?"

Mas Farrell added: "With this kind of analysis, the institute will be able to answer the questions to help policymakers make more informed decisions."

JPMorgan has also taken steps to reassure customers who may be concerned over the bank's use of their personal data, with the company insisting there are strict privacy protocols in place.

For instance, all unique identifiable information, including names, account numbers, addresses, dates of birth, and social security numbers, is removed before the institute receives any data, while only aggregated data – rather than individual – can be published.