The overseas money transfer industry has seen considerable changes since the turn to the last century, mainly because of technological advances. Once the domain of banks and high-street forex brokers, it has witnessed the arrival of several FinTech companies. Where there’s FinTech, can the use of big data be far behind?

Xoom, an overseas money transfer company headquartered in the United States, analyzes all the data linked to its transactions with the help of big names in the world of big data. The system successfully spotted an anomaly in 2011, one that may have gone unnoticed otherwise. It saw a pattern of a high number of Discover Card transactions from New Jersey, and while they seemed perfectly legitimate, they were the doing of a criminal group. Analysis of big data, in a way, saved the day.

What Other Purpose Can Big Data Serve?

Considerable information goes into processing an overseas money transfer. This information includes complete names of the sender and the recipient, names of both countries, the amount being transferred, the currencies involved, and the mode of payment. There’s a good chance the service provider will know the reason behind the transfer too.

By using big data international remittance companies may identify underlying patterns easily and use the results to formulate suitable strategies. For instance, an overseas money transfer company may benefit by finding out how much money their customers transfer, how often they carry out transfers, whether they send money to multiple recipients, and why they favor using a particular service.

Aggregation of big data also brings with it information about devices, locations, and timestamps. An example of how this information may be used is determining if customers initiate transfers from their homes or offices.

Take this example into consideration. Kenya-based M-Pesa is a mobile phone-based small-value money transfer operator. Originally launched to simplify money transfers, it has expanded into micro-financing, payment of salaries, and purchase of goods and services. The company has around 78,000 agent locations in the country and around 85% of the country’s population uses its services. The company can use its big data to get vital information about indicators such as remittances and disposable incomes.

Using big data to collate different types of information might seem like a daunting task, especially if a business already has a significant customer base. However, since a number of money transfer companies now aim to offer highly personalized services, analyzing big data in the right way can bring with it valuable information.

The Smart Way of Looking at Big Data

The information that comes with big data is voluminous, so being able to discern what’s useful and what’s not is crucial. Overseas money transfer companies who turn to big data should have specific points of focus with the aim of creating personal connections with their customer base. Identifying and acting on prevailing trends will remain important for FinTech companies such as OFX, WorldFirst, CurrencyFair, TransferWise, and WorldRemit. Consumers, on the other hand, will feel more empowered by being able to voice their needs.

Conclusion

Big data gives FinTech money transfer companies the ability to gain deep and accurate understanding of their customers. When used in the right manner, big data offers insights into aspects such as preferred modes of payments and transfers, why people carry out transfers, and the frequency with which people carry out transfers. Incidentally, using big data will benefit overseas money transfer companies and their customers alike.

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Dave O'Neill
Dave O’Neill is the Managing Editor at iCompareFX.com. iCompareFX compares and reviews the best international money transfer companies from across the globe. Uniquely, iCompareFX also does an indepth comparison of each money transfer company against each other. When not being the head bottle washer, Dave enjoys mountain biking in the Blue Mountains and nerding it up with the latest tech gadgets. Onya Dave! Follow @iCompareFX on Twitter and Facebook.

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