It's raining possibilities with cloud computing.For more than a decade, the cloud has powered various industry verticals for its virtue of cost-effectiveness and scalability. Today, cloud computing has become the venue for hosting an increasing number of technology solutions bordering on analytics, machine learning, and AI. There have been innumerable use cases on cloud-based solutions and the prominent ones being the BFSI sector. The two prominent reasons that drove the robust adoption of the cloud as a platform in the year 2020-2021 are as follows.

• First, the ongoing pandemic pressed the banking sector to increasingly offer digital services and employ analytics to improve operational efficiency and optimize business processes.

• Second, there was a sudden proliferation in online transactions and the launch of newer payment gateways and wallets. 

Scaling-up in terms of innovation was the need of the hour while there was no scope for any hefty investment for managing in-house data warehouses. This pushed the BFSI sector to explore and adopt cloud platforms as the best possible environments for building and hosting technology stacks for business agility. 

Learning from KeyBank

Based out of Cleveland, KeyBank is one of the largest bank-based companies offering diverse financial services. KeyBank had invested in Teradata for high-power analytics. After a decade of leveraging the services, the bank realized the need to upscale as the storage capacity was nearing its pinnacle. Renewing an on-premise data warehouse was a costly affair. This propelled KeyBank to explore the cloud as a possible breakthrough as a scalable and smarter analytics platform. The management board explored and ran trials for Google Cloud’s BigQuey with ETL time, performance, and query time as major parameters for benchmarking. 

While the primary goal of the bank was to derive the superior performance of on-premises data warehouse at an affordable cost point and that too on a single platform. One of the key premises was not just to sit on the storage space month on month but to have the flexibility to choose cloud plans that were flexible for upscaling and downscaling. 

With seamless migration on BigQuery, Google's Cloud-based Big Data Analytics platform, the query performance improved manifold times. The scope for leveraging analytical capabilities improved without interrupting the ongoing innovation projects. BigQuery also empowered KeyBank with advanced data transformational tools that helped them garner business-critical insights and unlock new potentials.

So, from the KeyBank case study, it is clear that analytics powered by the cloud has great possibilities for the financial sector. 

Key benefits delivered by cloud-based financial analytics

1. Superior connectivity 

2. Robust data reporting and monitoring 

3. Smart Data mobility

4. Improved data accessibility

These four benefits delivered by cloud-based analytics enable financial institutions to make well-informed capital decisions by adopting appropriate data strategies. It is important to note that an enormous amount of data is generated by IIoT tools operating in the domains of insurance and finance. The cloud-based platforms make it easier to run analytics on the data derived from IOT devices. 

Financial analytics is the backbone of the BFSI sector. To be able to set in motion, a transformative approach to finding solutions, it is crucial that executive leadership has a firm grasp of financial analytics and reporting. One of the recommended methodology to gain significant insights is exploring programmes like  the Executive Programme on Business Analytics offered by IIM Calcutta in collaboration with Hughes Education. This program has been devised to help new-age leaders build competence in analytics and in the ability to handle big data.