Expert Analysis: Using Big Data To Make Better Decisions in Financial Institutions

Increasingly, the emergence of wireless technologies, intelligent products and businesses defined by software play a key role in the exponential growth of data worldwide. This is corroborated according to a study conducted by EMC Corporation and IDC, which states that the Digital Universe is doubling its size every two years and will increase tenfold between 2013 and 2020 – from 4.4 trillion gigabytes to 44 trillion gigabytes.

‘But what does this mean for my company? What is the challenge?’ The answer is simple, to get value from Big Data, a key aspect is to apply statistical techniques and predictive analytics to large volumes of heterogeneous and unstructured data that support enterprise platforms, and to make better use of information resulting in more conscious and realistic decision-making.

While there may be a slowdown in expectations because of doubts about how organizations should implement Big Data strategies and how to generate value from it, this year´s forecasts remain strong and we can expect between 15% and 20% growth, as companies need to focus not only on transactional or structured information, but, in the current context with widespread use of mobile devices and apps, social networks, forums, videos, etc. organizations must also manage unstructured information, which is generated in many cases through the customer’s interaction points according to the services provided.

Fully one-third of CIOs have no Big Data strategy or plan.

Under these characteristics, Big Data, with its innovative paradigm facilitates business processes to make them faster and more efficient, helping to improve and accelerate decision-making from the implementation of solutions that are able to interrelate and categorize all corporate information to transform data into value.

Although 79% of CIOs surveyed by EMC think that Big Data will improve decision-making, fully one third don’t have a Big Data strategy or plan. This highlights the fact that many companies still don´t feel prepared to adopt the various processes that are enabled by Big Data, so one of the main challenges is deciding how best to implement “the promise of Big Data.”

A common mistake is to address the strategy from a completely technological point of view to identify, within the range of technological options, which one best suits the need of capturing and analyzing both structured and unstructured data. This is not enough for successful implementation because companies must find a comprehensive and integral approach that mixes technology with other elements that warrant consideration.

• It is important to have an analytical layer to extract value from large volumes of data
• You must use predictive models of risk and fraud to implement strategy in order to ensure success by managing large volumes of information
• You should considerate an organizational dimension and change management to introduce new roles and processes that go hand in hand with implementation. In these cases we can highlight the role of the Scientific and Data Analyst as an essential profile to be able to develop analytics solutions that can extract value from data. In addition to this role, it is necessary to introduce other roles that take care of the infrastructure, architecture solutions and the generation of new service opportunities based on analytics.

The holistic approach is essential to carry out the correct transition towards Big Data and thus, to enjoy the benefits of increased productivity and cost reduction that this technology brings. Organizations that accept this challenge will understand how their customers perceive their services, and will be able to achieve and define predictive models that enable and anticipate market behavior.

Using these rules, your company can develop strategies that add value and differentiation from the competition, which will always result in an increase in service quality and customer experience with your products or services.