The banking system is facing complex and pressing challenges nowadays. The whole macro-economic system is hardening, banks are suffering from tighten regulatory pressure, both locally and globally speaking, and political uncertainties in many countries rise. All these factors are deeply affecting the environment in which financial institutions work. Moreover, there is a strong competitive pressure given by external actors (above all technological enterprises and innovative Fintech startups) offering bank alike services that are able to better serve clients due to a more flexible and personalized value proposition. Such an environment is pushing financial institutions to change their business models, pursuing effectiveness in serving new customers’ demands and trying to reach a higher livel in terms of cost-effectiveness. The digital revolution that is characterizing the banking system could be a good answer to such challenges. Historically financial institutions have been able to collect a lot of valuable information about how the clients behave and about their prefernces. However, such information becomes worth if banks are able to extract them from data and put them down to work on concrete business processes. Starting from this assumption, Big Data Analytics could help to get those insights and better the commercial offering and the operating processes through the visibility they enable to reach and their potential to automatization. This study is developed right in this context. It first tries to evaluate the current state-of-the-art in Big Data Analytics adoption in financial sector. The analysis takes into consideration 128 Big Data projects in world-wide based financial institutions. Furthermore, the study is trying to develop a strategic framework to approach Big Data Analytics in banking, highlighting what are the main functional areas in which these technologies could create a concrete competitive advantage, which data and models could be employed and, finally, what kind of organizational and data governance implications the successful implementation of such technologies have.
Le sfide per il sistema bancario sono oggigiorno sono sempre più incalzanti e complesse. Il difficile contesto macro-economico, i vincoli normativi sempre più stringenti a livello locale e globale e situazioni politiche incerte in alcuni fra i Paesi più importanti a livello internazionale stanno mutando profondamente il contesto operativo che gli istituti finanziari devono affrontare. A questi fattori si aggiunge poi la forte spinta competitiva portata da attori esterni (attori tecnologici e startup innovative su tutti), sempre più coinvolti nel lancio di servizi bank alike che incontrano il favore di una clientela le cui esigenze sono cambiate, sia in relazione alla modalità di fruizione, sia in relazione al contenuto dell’offerta stessa. In un simile scenario, gli istituti finanziari dovranno quindi adattare i propri modelli di business, ricercando efficacia nel rispondere a quanto il mercato richiede ed efficienza operativa. Una risposta a queste esigenze di cambiamento è data dalla rivoluzione digitale che sta interessando il mondo bancario. Storicamente gli istituti sono stati depositari di un patrimonio informativo sul cliente di grande valore laddove vi siano le capacità di estrarre informazioni che abbiano un impatto concreto sulle attività di business. Ecco quindi che le nuove tecnologie di Big Data Analytics possono contribuire a migliorare l’offerta commerciale degli istituti e, al contempo, rendere più efficaci ed efficienti i processi grazie alla visibilità e alla potenziale di automatizzazione che abilitano. E’ proprio in questo contesto che si inserisce il presente studio, che cercherà innanzitutto di valutare lo stato dell’arte nel settore finanziario a partire dall’analisi di 128 progettualità Big Data nel mondo finanziario. In seguito si cercherà di dare una risposta a come gli istituti possono concretamente sviluppare un approccio strategico a queste nuove tecnologie di analisi sui dati, andando ad evidenziare quali sono gli ambiti in cui possono creare un concreto vantaggio, quali sono i dati e le modalità di elaborazione e analisi che possono essere sfruttate e, infine, quali sono le implicazioni organizzative per poter sviluppare con successo queste nuove tecnologie.
A strategic framework to approach big data analytics in banking
FRIGO, MATTEO
2015/2016
Abstract
The banking system is facing complex and pressing challenges nowadays. The whole macro-economic system is hardening, banks are suffering from tighten regulatory pressure, both locally and globally speaking, and political uncertainties in many countries rise. All these factors are deeply affecting the environment in which financial institutions work. Moreover, there is a strong competitive pressure given by external actors (above all technological enterprises and innovative Fintech startups) offering bank alike services that are able to better serve clients due to a more flexible and personalized value proposition. Such an environment is pushing financial institutions to change their business models, pursuing effectiveness in serving new customers’ demands and trying to reach a higher livel in terms of cost-effectiveness. The digital revolution that is characterizing the banking system could be a good answer to such challenges. Historically financial institutions have been able to collect a lot of valuable information about how the clients behave and about their prefernces. However, such information becomes worth if banks are able to extract them from data and put them down to work on concrete business processes. Starting from this assumption, Big Data Analytics could help to get those insights and better the commercial offering and the operating processes through the visibility they enable to reach and their potential to automatization. This study is developed right in this context. It first tries to evaluate the current state-of-the-art in Big Data Analytics adoption in financial sector. The analysis takes into consideration 128 Big Data projects in world-wide based financial institutions. Furthermore, the study is trying to develop a strategic framework to approach Big Data Analytics in banking, highlighting what are the main functional areas in which these technologies could create a concrete competitive advantage, which data and models could be employed and, finally, what kind of organizational and data governance implications the successful implementation of such technologies have.| File | Dimensione | Formato | |
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2017_04_Frigo.pdf
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https://hdl.handle.net/10589/133314