The way business is conducted is changing drastically for financial services companies, according to a new report from Celent; and “when sensibly integrated with core, channel and decision support systems, [big data] holds the promise for enabling the survival of financial service companies within this epic transformation,” Celent said.
To help companies take advantage of big data, Celent outlines steps insurers can take to shore up capabilities, the different data types insurers should plan for, the big data ecosystem that all companies need to be aware of and function in, and lastly, a case study of Taishin International Bank for firms already engaging big data and looking for innovative possibilities.
Whatever level of capability an organization has now, Celent said, there is an achievable, affordable route for that organization to start experimenting with more powerful tools and technology, to understand the value of the data it has, and the benefits that can be derived from the data.
Celent’s advice boils down to examining your current capability, evaluating where you should be or want to be, and investing appropriately to close the gap. To help companies answer the first two questions, Celent defines five tiers of capability: spectator, experimenter, practitioner, innovator and scientist, specifying the tools, people, attitudes and activities that align with each step.
The report takes pains to emphasize getting past the spectator step. To do so, a new business culture that embraces the leveraging of data must be crafted, along with an enterprise data strategy and roadmap. Other first steps that need to be taken include training and recruiting internal talent as well as sourcing and partnering with outside talent for some services. And lastly, decisions need to be made regarding the tools and data necessary for your specific industry and company needs. Within these steps there are options such as experimenting with technology and solutions, data sandboxes and vendor trials.
The big data ecosystem presented is made up of four parts: the technology tools and software; solutions providers offering packages, consulting and Data as a Service (DaaS); the company, including the culture, people and market positioning; and the context of the industry at large.
“Firms that ignore the forces of the industry and solutions/technology and do not use them to gain a competitive advantage will do so at their own peril,” Celent said.
Celent also outlines five data sources that come together to make big data:
- Social media
Public filings, content available in the public domain through agencies or subscriptions
Documents and e-mails, including both structures and unstructured texts
Digital devices and sensors, including location-based, smartphone, weather and telematics data
Data as a Service (DaaS) providers, including providers of data available for resale from services such as Lexis/Nexis.
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