{"id":19857,"date":"2020-11-03T13:00:17","date_gmt":"2020-11-03T12:00:17","guid":{"rendered":"https:\/\/relaunch.striped-giraffe.com\/?p=19857"},"modified":"2021-06-18T11:59:48","modified_gmt":"2021-06-18T09:59:48","slug":"data-analytics-for-the-financial-industry","status":"publish","type":"post","link":"https:\/\/www.striped-giraffe.com\/en\/blog\/data-analytics-for-the-financial-industry\/","title":{"rendered":"Data Analytics for the Financial Industry"},"content":{"rendered":"

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Advancing digitization of the financial industry makes it easier for banks to gather comprehensive information about their customers, while state-of-the-art data analysis methods provide valuable insights which let financial institutions stay sustainable and competitive.<\/h3>\n

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Financial institutions have always gathered a lot of information about customers \u2014 their incomes and savings, where, when and how they spend their money, the financial products they use, etc. Digitization of the banking and financial sector has not only facilitated the collection of this data in electronic form, but has also enabled collecting even more detailed information.<\/p>\n

Not so long ago, most of this priceless data was only stored and used in certain situations, e.g. to proceed transactions or handle customer\u2019s requests. Fortunately, this is changing rapidly and more and more financial institutions are recognizing the potential of advanced data analysis and realizing that it gives them the power to better understand their customers\u2019 behavior and meet their expectations.<\/p>\n

The most modern methods of data analysis allow financial institutions and fintechs to evaluate customer interactions based on numerous factors, not only structured transactional data, as it was until recently. For advanced data processing solutions it is no longer a problem to integrate structured, unstructured and mixed data coming from a variety of different sources and in various formats.<\/p>\n

Major challenges<\/strong><\/h3>\n

However, a significant challenge for data management in the financial industry is exponentially growing volumes of data, which results not only from the increasing number of products and customers, but also from constantly emerging new data sources, especially external ones like new websites, discussion forums or social media.<\/p>\n

To create an intelligent customer 360\u00ba view \u2014 which demonstrates the full spectrum of customer interactions with the financial institution and provides accurate insights \u2014 it is necessary to identify all relevant data sources and develop a comprehensive solution that combines data integration, data quality, and advanced analytics<\/a>.<\/p>\n

Choosing the right set of technologies and tools, as well as combining them into a single platform integrated both with other systems and identified data sources is one of the biggest challenges in such a project.<\/p>\n

However, the benefits can be countless and include:<\/p>\n