Analyzing data and making meaningful decisions based on it is common practice for banks and financial institutions, so why exactly is big data being trumpeted as this paradigm-shifting force?
Big data is the title through which analytics are becoming worldwide famous and applied in any kind of industry worldwide. Digital giants like Google and Amazon are leading the pack on what to do and how to turn massive amounts of data into real value by shaping processes and products around information and insight, putting the results of this work into smartphones and mobile devices that we use so much every day.
Looking at it from this perspective it would be a big, and perhaps unrealistic, challenge for any company in any industry to understand how to act on big data analytics following the footsteps of these global giants. Moreover consulting, software and hardware firms are pushing big data so much that there is a real risk of being unpractical and entering a never-ending whirlwind of complexity. With this white paper we would like to shed some light on how to make first steps into the big data world, while keeping your feet on the ground and positioned towards achieving a positive return on big data investments as fast as possible.
The Digital transformation and the Big Data hype
It is not by chance that big data analytics are coming along with the Digital revolution: the rapid spread of processes and knowledge and the exponential importance of non-physical channels across all industries are leaving data along their trail. In fact, when we think even of the most traditional process, the impact of digital technologies can redefine the value chain and the adoption of these technologies can lead to massive amounts of new data, for example:
- On the operations side: tracking work capacity and technical health of production machines with small sensors rather than keep an eye on financial stability and health of suppliers;
- On the sales and marketing side: using beacons to perceive customers walking in and around a bank branch rather than using a mobile APP to pre-qualify a lead in order to propose a more effective offering.
In addition, digital environments are flourishing and are allowing consumers to generate data (e.g., social networks, online review platforms, etc.), which is providing every business the potential to better listen to customer preferences and interests, monitor competition and thus drive enhanced product and service design and communication.
What does Big data mean for financial institutions?
All banks and financial institutions are used to analyzing data and making meaningful decisions based upon the evidence provided by data. Regardless of whether the amount of data used for making decisions can be small (like a single credit report) but also very large (like the entire set of payments received from every account in the bank), it is clear that data is an essential part of the day-to-day processes of every financial institution.
In most recent years, there has been a great interest about how this situation can move to a “big data” scenario and how financial institutions can leverage this new kind of data. This has happened because the internal data of the bank can be integrated and augmented (with some regulatory and legal implications that vary across countries) with data from outside the bank, like social media, web site scraping and other forms of public data.
What to do with all this new data?
Above all, that’s for sure the most underestimated question during the current hype on big data technologies: everybody can take for granted that data or efficiency in managing them is not an answer to any business issue, while the actionable knowledge that can be extracted from data using analytics is the critical outcome. In particular when we are referring to predictive and prescriptive analytics.
Eventually the big data hype will deflate and solid business use cases will emerge, and in our perspective use cases are what financial institutions should seek out, such as innovating processes in areas like:
- Marketing & Sales Analytics;
- Credit & Risk Analytics;
- Corporate Functions Analytics.
Download the full paper for a full overview of how to make big data work for you.
