Financial Services — Customer Intelligent & Insights
For the financial services industry, digital transformation is a critical, if not mandatory, process that
institutions must undertake in order to survive. A large component of digital transformation, and one of the four main pillars of IDC's 3rd Platform IT architecture, is Big Data and analytics. For most institutions, this focus on analytics is split between back-office (enterprise) analytics (e.g., risk management and regulatory compliance) and front-office analytics such as customer marketing.
In a survey to financial services institutions performed by IDC in 2015, "understanding the customer" was unanimously reported as the main business objective for deploying front-office analytics. However, most banks self-reported a lack of maturity in this area for a variety of reasons including: a lack of appropriate metrics, a lack of skilled IT resources, a lack of complete and accurate data, and the challenges of a siloed business organization.
In September 2015, TCS Digital Software & Solutions Group launched its CII solution for retail banks. The solution itself is a set of data and analytics components focused on customer centricity, including prebuilt use cases that institutions can deploy in whole or in part that can ostensibly kick-start a more holistic customer analytics initiative at the bank.
The main components include:
- An open data architecture built on Hadoop that can accept structured and unstructured data
- An industry-specific data mart, customized for banking
- Preconfigured metrics (KPIs) for prebuilt customer analytic functionalities
- Real-time decision support
Smart Cities — Intelligent Urban Exchange
Smart Cities are an approach by which state and local government organizations use digital technologies as a platform to transform operating models, provide improvements on current products and services, and deliver new products and services to citizens, visitors, businesses, and other departments. This Smart City transformation involves workers from different government departments, various technical systems, and data formats as well as a broad ecosystem of advisors and suppliers. As more and more cities embrace the Smart City concept, they are confronted with complexity in: IT and operational systems, the connection between digital and physical environments, creating the supporting regulation and policy, and effecting behavior change to meet desired goals.
The challenge is to address these challenges while adhering to the procurement and budget rigidity that exists in local government and implementing new solutions without high costs and risks associated with large, customized projects. The majority of midsize cities are looking for less complexity — solutions that can get up a running quickly, do not require specialized skills to operate, that leverage existing systems and data, have lower up-front costs, and can demonstrate quick results. More and more cities are focused on open source and standards-based systems to reduce reliance on proprietary technologies and the risk associated with vendor lock-in.
Data affects every aspect of digital transformation, from the consumer experience to the business
decisions to the efficiency of operations. The key to digital transformation success, then, is the most effective use of the data, whether internal or data from external services. Aggregation, analytics, and action are the critical processes that will distinguish organizations that thrive from those that will be challenged to survive.