Banks, what are the advantages of data analysis?


The English data scientist and mathematician was already in 2006 Clive Humby defines the data “The New Oil”. Banks have a lot of internal and external data. However, I can’t always use them optimally. We have put together recommendations on the topic George DossenaPre-sales manager from Qlik Italy.

What data can banks and financial companies use to their advantage?

Banks and other companies in the financial world today have a huge amount of internal and external data; however, according to the data of World Retail Banking Report developed by Efma 73% of finance executives say they struggle to turn data into actionable insights. In practice, there are several areas where the use of data should support developments for banks and financial services companies today. Many realities already use data in a structured way Inner available, while their integration with external sources is less widespread, be it open data or elements coming from open banking openings. This is because there are still various limitations, mainly related to data protection regulations, which impede the use of external data and consequently prevent building a well-structured path to truly data-driven banking at 360 degrees.

What seems more natural concerns the use of data by banks and financial companies developing the way to relate to or interact with customers, generally aimed at creating new services. If the limitations related to the privacy policy prevent excessive customization, in the presence of adequate consents and analysis and visualization tools, The use of data should be the useful basis for examining developments in the offerespecially in the direction of digital services.

What benefits can they derive from data analysis?

Data analysis today can represent a necessary tool to improve customer awarenesshelp banks and financial companies to optimize banking processes to make them more agile and faster, also through theautomation. In fact, through data analysis, it is possible to construct the customer journey in such a way as to map out the main events that characterize people’s choices and preferences and, consequently, the specific financial needs at that particular moment. Precise determination is possible with current data analytics technologies significant patterns in customer behavior and therefore generate useful knowledge to propose the most interesting financial products. However, the situation in this case is still very advanced, since the data collection from the various channels has only partially reached a sufficient level of maturity and the still limited dissemination of methods of a uniform customer view requires more organized processes in the management of data protection management. The monitoring of the different channels with an analytical and maybe even predictive logic is not yet consolidated.

Another area where the impact of a correct development in the field of data analysis could be quickly measured could be that of fraud prevention, in itself a very sensitive issue in the banking world. In fact, the topic is treated as a classic protection problem and is tackled with canonical behavior analysis tools instead of systematic and selective data use.

How far are banks and financial institutions in data analysis?

In recent years, banks and financial institutions have undoubtedly performed well big investments Introduction of integrated management systems capable of efficiently designing internal processes and controlling budgets. On the contrary, there are aspects that still need to be strengthened, such asApplication of these analytical technologies to evaluate processes with the aim of improving them. In fact, data analysis in the banking sector can make it possible to identify problems in internal processes and thus examine what is required to achieve significant improvements for customers and for the bank itself.

On the other hand, we are observing some interesting developments on the sustainability front: the issue IT G It has only recently penetrated the banks, leading to the creation of entities dedicated to studying the operational reality and opportunities associated with the PNRR. In large institutions in particular, structured plans have already been developed and the use of internal data is already aimed at achieving goals on this front as well. In some cases, participation in or the existence of an initiative to reduce environmental pollution is used as a distinguishing criterion for lending and, if favorable conditions are available, the data is used to investigate the climate sensitivity of customers, also for the purpose of providing advice.

How can banks derive value from data and create a successful data strategy?

Today, data is a valuable element for organizations and every company has large amounts of it. In order to use all the information available in organizations, it is necessary to a Solid data culture, with which you can extract values ​​and potential from information in order to be able to act strategically. The aim is make data-driven decisions, but also to refine the forecasting skills that can make the difference in uncertain times. There data literacy, That said, the ability to read, understand, create and communicate data as information must be the foundation of this strategy.

As is so often the case, the support of technology is only a enabler for a data-driven project. What is fundamental is a process that enables anyone with preparation and skills shared across the organization to capture the value of data.

How can lenders strike a balance between cloud and legacy?

However, the perception of the benefits in terms of scalability and the ability to effectively manage large amounts of data is there The evolution of banks towards the cloud is taking place very carefully with the goal and need to find the right balance with a legacy component that is still predominant. Few of the leaner organizations have taken significant steps in this direction, but the existence of hybrid environments can be taken for granted.

Certainly, the elements that are not accelerating the adoption of the cloud are all the regulations related to data protection and GDPR, which require additional efforts from all financial institutions.

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