Big Data and Fintech Era: what perfect combination for the year 2018? With technological innovation, a new form of wealth has increasingly established itself. We all know it as the science of Big Data or “big data,” affecting all business sectors (banking, finance, manufacturing, insurance, PA, etc.)
Big Data and Digital Transformation are increasingly affecting how users interact with banks, credit intermediaries, insurance companies, and companies operating in manufacturing and retailing. We cannot deny that all companies are going through a real “4.0 revolution,” which must necessarily pass from the Data Analysis activity.
“The real bet is to increase the competitiveness of our economic system,” affirms the former President of the Youth of Confindustria Marco Gay, “the digital transformation has begun, but an acceleration is needed to create value within the country-system.” How important is Digital Transformation for corporate business? What is the relationship between Industry 4.0 and Big Data? Let’s find out in this guide the three main ways to excel, thanks to the analysis of company data.
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Fintech era and Big Data: where are we?
Digital transformation has brought significant changes to the world of finance and banking. Among these, we can highlight the reduction in the number of bank branches, banking disintermediation, the increase in the commercial offer of credit products (loans, mortgages, salary-backed loans, etc.), the decrease in the use of cash, the role of new customer relationship channels and the advent of Robo Advisors.
Thanks to the use of Big Data and Data Science, the Fintech sector is experiencing a phase of full expansion, and the dynamism of Fintech Start-Ups continues. Unfortunately, few innovative business units have embarked on an objective process of disruption or a new way of operating, doing business, competing in the market, and acquiring new digital skills.
Alongside this phenomenon has been the birth of different ecosystems linked to the Blockchain or the “value chain.” Bitcoin, the cryptocurrency by definition, represents the maximum technological expression in the digital payments market and has introduced new intelligent systems to manage transactions.
These contextual factors are increasingly characterizing the economic scenario and are affecting the awareness that banks and financial institutions represent an enormous data mine. The Big Data Analytics market has grown by about +22% in the last year. In the Finance world, Artificial Intelligence tools, Machine Learning, and the development of API-based solutions are increasingly competitive factors for success.
Why do companies choose Big Data?
Big Data Analytics appears increasingly essential to seize the various commercial opportunities and manage development phenomena. For example, Industry 4.0, Smart Retail, Digital Banking, or to support regulatory compliance processes such as the issuance of the GDPR.
Both large companies and SMEs bet on the potential of data analysis, and the following expenditure items absorb the investments that have the greatest impact on company budgets:
- Costs for purchasing software (databases, data processing tools, data analysis, budgeting, and reporting platforms). These are software that includes advanced support services for corporate marketing, product and service promotion, customer assistance, administration, finance, and control functions;
- Expenses incurred for business services (customization of software systems);
- Costs to implement the corporate infrastructure.
Big data investments are growing increasingly in the Insurance, Banking, Telco, Large-Scale Retail, and Healthcare sectors. If we look at the corporate sectors, the banking, financial, and insurance sectors continue to be the most attentive and sensitive to this type of investment. It follows Industry 4.0 and Manufacturing, the Telco sector, the PA, the world of Smart Health, and large-scale retail trade.
Towards the fourth industrial revolution
Big Data represents the main resource for companies investing in Industry 4.0. “The next three years will be important to ensure that our startups and companies are positioned to play their game globally. They can make a difference, but there’s not much time left. […] But we have the stubbornness and the ability to get the results we deserve », underlines Marco Gay, President of Anitec-Assinform.
The fourth industrial revolution will depend heavily on the use and analysis of data and will necessarily require a cultural change. “The digitization of the production of goods or services is at the basis of a new way of looking at the country’s economic development, […] those who have been involved in technology and innovation for years cannot fail to be satisfied when they see that some issues are becoming general interest“.
The fourth industrial revolution requires an actual economic, social and cultural change involving all those involved in the entrepreneurial fabric. “Small and medium-sized Italian enterprises are not ready yet because they do not yet fully understand the scope of this opportunity. They don’t understand that they either ride the change or risk being overwhelmed. The beautiful and well-made is no longer enough”, underlines Gay.
Within the fourth industrial revolution, Big Data will increasingly be the main protagonist of Industry 4.0: in the manufacturing sector, companies will save millions of euros and improve efficiency, effectiveness, company productivity, and product quality/ offered services. “Those who do not innovate not only fall behind but risk remaining in a niche for the few,” underlines the President of Anitec-Assinform.
Data analysis will make specific professional profiles more efficient, but at the same time, it will represent a severe threat. For example, the decrease in the demand for workforce and changes in the skills required to be part of the workforce of a company. Some professions and professions will disappear, but new ones will be created.
Business & Big Data Analytics: 3 ways to excel
Every company must be able to plan better its corporate strategy using Big Data. This will keep up with the times and take advantage of data analysis.
Here are the steps to follow to create value:
It is essential to know that researching and obtaining customer data is comparable to a real gold rush. The first step that all companies must take is to acquire the proper awareness of the importance of the data they possess. This enormous amount of data comes from the most disparate sources that most companies need to consider. Thanks to new technologies, data acquisition is possible via the internet (website, social media) and wireless networks, mobile devices, heat detectors, and NFC.
Analyze the data
Once the company data has been collected, it is necessary to analyze and catalog them by variable to standardize and homogenize them. Each business unit must be able to set specific objectives to be monitored and then improve results thanks to data analysis. Through Big Data Analytics tools, it is possible to create dashboards, reports, and graphs that allow you to view and study the collected data.
Evaluate data and decide on business strategy
Once collected and analyzed, it is necessary to carefully evaluate the available data to decide the corporate strategies to be pursued (at Top Management, Middle Management, and Executive level). It is essential that every human resource within the business unit can benefit from the data at their disposal to obtain useful information to operate at their best.
The role of the Data Scientist in the company
We have highlighted that Digital Transformation and Industry 4.0 will create new professional skills: the development of Big Data Analytics will increasingly determine the importance of the figure of the Data Scientist. It is a valid professional who adopts a multidisciplinary approach, possesses purely digital skills and abilities, computational and mathematical calculation, business and market analysis, and good use of machine learning tools.
Shortly, companies will be looking for Data Scientists to be included in their staff. Thanks to his broad multidisciplinary background, the Data Scientist aims to organize and analyze a large amount of data using ad hoc designed software. The final results, deriving from the company data analysis and evaluation process, must be concise and easy to understand for all stakeholders. The challenge is completely open, and the Big Data Analytics activity will become increasingly strategic to keep up with the competition.