retail analyticsData is at the heart of the modern world. With data all around us, most of us have stopped noticing how prevalent it is. Just about every single industry across the board has benefited from advances in data science, especially the advent of big data, and the financial industry is no exception.

Big data is changing the finance industry in a number of different ways, and here are just a few of them.

Personalisation

Personalisation has been an emerging trend in a number of different industries, with the financial industry among them. Consumers like personalisation because it makes them feel special and acknowledges them as an individual rather than just part of a collective.

Across the world, we have seen new banks disrupting the market by introducing a more modern sensibility to traditional banking methods. A common thread that runs through all of these banks is their use of personalisation to improve customer engagement.

Understanding the habits and behaviour of users to the degree necessary to offer them personalised services is best achieved with a data-driven approach. Big data enables banks and financial institutions to much more accurately define and profile their userbase, which in turn makes it possible to target services and messaging at them much more precisely.

Security

Fraud is a big problem in the financial industry. As our methods of detecting financial fraud, especially at a systemic level, have grown more complex, criminals have grown craftier. It is now relatively easy for anyone who wants to hide money to do so under layers of shell corporations. Similarly, by funnelling money through multiple transactions, it can become all but impossible to trace or identify the original source of lots of money.

Big data analytics enables financial services watchdogs to identify patterns of behaviour that would be very difficult for a person to spot. These algorithms can pick out suspicious transaction patterns that warrant further investigation.

Investing

Automated investing is becoming increasingly common. There are now a variety of ways that new and experienced traders can automatically invest their funds. Some of these methods involve mirroring the trades of other people, but there are also a growing number of algorithmic solutions. Big data analysis has enabled the development of reliable trading algorithms that are capable of reliably making money for their owners.

Risk Mitigation

Big data can be used to reduce the risk that financial lenders are exposed to when they offer their services widely. When someone applies for a loan, the lender will generally consider their present situation and their financial history. Big data has enabled lenders to identify key metrics and data points that can be used to determine algorithmically whether they should lend to someone or not.

Risk mitigation isn’t just important for banks giving out loans. It is also important for lenders who offer loans for bad credit UK borrowers like simplepersonalloans.co.uk and for insurance businesses who want to assess the risk involved in providing cover to someone. Big data enables us to analyse and understand data on a level not previously possible, with big implications for how we think about risk mitigation.

Big data is transforming the financial industry for the better. From minimising risk to lenders to preventing fraud on the part of borrowers, big data has a key role to play.

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