Platforms of the Future

Banking Frontiers|June 2020

Platforms of the Future
At Technoviti 2020, CIOs and CTOs share their perspectives on selecting and leveraging a variety of platforms that suit their respective organizations:

Low code platforms accelerate new product engineering

Shashank Sathe, Senior Vice President- IT, Edelweiss Financial Services:

Edelweiss Financial Services has an 8-12-year-old legacy system. We have challenges like reducing the technology spends and adopting new frameworks. Our approach is to go for open stack, full-stack, and application development, which have near-zero cost of ownership. We have chosen this as a roadmap, and we are working on it. Additionally, we are moving on to low code platforms. We are trying not only to have the infra and networking elements but also to adopt low code engineering platforms, which allow a significant amount of effort from an engineering perspective. From my experience, it saves 70% of coding/engineering time and effort while building a product.

We are currently halfway through our digital transformation; our infrastructure runs on the data centers and we are making efforts to move as many of these into a survivalist framework. Our systems are 30% on cloud, 50-60% on AI & analytics, and we are using RPA technology in 35-40% of our operations. We have adopted infrastructure and cloud as a core model, and we are getting benefits as it adds a phenomenal amount of savings in our operations. We have already started adopting serverless computing.

We have tried to automate the entire documentation supply chain management system. We have also started overhauling our document management system, which was based on our legacy setup. We have started moving onto an in-house developed solution which is a huge cost saving for us. In most of our engineering projects, we have frontend development, middleware, back-end analytics, and MIS delivery. We have applied multiple models in alternative fashion to gain inside out, which leads us to the data lake-related activity.

We have approached this problem in a dual-purpose mode. Relational data is something that is analyzed and used by our business teams for gaining business intelligence about the customer. Unstructured and non-relational data helps to enhance and better our products.


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June 2020