Big Data in Finance: Boost Your Business Through Data
- What is Big Data in Finance
- Big Data in the Financial Industry
- Benefits of Big Data in Finance
- How To Use Big Data in Finance
- How Plain Concepts Works With Big Data
- Explora las posibilidades del big data
Stock purchases and sales, transfers, loans… There are numerous banking and stock market transactions that take place every day. This generates a large amount of information that, properly treated, can be beneficial for financial companies and also for their customers. We are talking about financial big data.
In this post, we share with you everything you need to know about the management of these large amounts of information and why, if you work in a company in this sector, you should know about it.
What is Big Data in Finance
Big Data in finance is the large amount of data that companies and financial institutions can use for their business: analyzing future trends, getting to know customers better, saving costs…
Big Data in the Financial Industry
Millions of financial and banking transactions are made every day. This generates a volume of data that, mixed with other sources of information, is used to make new investment and savings decisions, but also to offer better products and services to customers.
Benefits of Big Data in Finance
Among the benefits of Big Data for the financial industry are:
Faster analysis of large amounts of information (such as real-time stock markets) reduces or eliminates manual processes: report generation, data analysis, etc. At the same time, it saves time for employees and money for the company.
Prediction of Non-payments, Fraud, and Other Risks
With predictive models trained with Machine Learning and Big Data, plus Artificial Intelligence, it is possible to gain security and work to prevent some of these situations. Likewise, when detecting these possibilities and if employees think it is necessary (money laundering, for example), they can contact security forces to prevent or stop behaviors. Among the suspicious behaviors that could be analyzed with these technologies are purchase patterns, and strange uses of credit and debit cards…
On the other hand, the analysis of certain customer data can be used to conclude the risk of granting a loan or insurance and make a decision based on it.
By analyzing large amounts of data and making decisions based on it, new products or marketing plans are created that translate into more satisfied customers who find what they need or discover new advantages that make them more loyal to the company.
New or Increased Revenue Opportunities and Cost Savings
Therefore, by analyzing big data and having more loyal customers, the company obtains higher profits. At the same time, it saves costs thanks to the mechanization of tasks.
Cost savings, in addition to mechanization, also occur in the modernization of systems or in the optimization of other tasks: data can be used to know what to improve in certain areas.
How To Use Big Data in Finance
When using big data in finance, the first thing to do is to define the data strategy and which departments will be affected: systems, business intelligence, marketing… With this information, the ideal data platform for the project is chosen; we must consider whether it will only be used to store data or if we also want processing and analysis capabilities.
How Plain Concepts Works With Big Data
At Plain Concepts, we have collaborated with the financial sector to develop big data projects. We have also created tools that help them in some of their processes.
One of our latest projects is Helix 2, a big data and artificial intelligence platform that helps companies look for financing. To train the tool, we had to identify commercial and bank credit risk factors. To this end, data was taken from 3,600 Spanish SMEs, insolvency legislation from EU countries and the UK, and scientific articles. All this crystallized in a predictive model of default risk.
Another project was the creation of BBVA’s Valora View app, which helped in the search for apartments to rent or buy. By combining big data, Xamarin, and Augmented Reality, the app provides the user with information on the future value of a house, possible offers based on historical data, and mortgage calculators, among other services.
Estos son tan solo dos ejemplos de lo que se puede hacer con big data financiero. Si quieres ahorrar dinero en tu empresa, mejorar el rendimiento de los diferentes departamentos o tener clientes más satisfechos, investiga todo lo que te ofrecemos desde Plain Concepts.