Articles

Cloud-Based Analytics: Helping Banks Drive Digital Transformation

by Jatin Sharma Writer

Most organizations have digital transformation as the core of their present corporate strategy. The same is true for the retail and corporate banking sector. At the heart of this transformation is the ability to develop actionable insights. The aim is to gain useful, smarter, and accurate insights at a faster pace in the competitive world and translate the same into action for the business.

How can that be achieved, you may ask?

Big data consulting services help organize all your data in a manner that is accessible at any time, from any location, and in context for a specific user. With smaller and agile providers entering the banking market, the demand for a higher level of service facilitated by digital experience that acts as a guide to make quick, smart decisions has increased.  

Data-Driven Digital Transformation:

Embedding data-driven decision making and fostering digital business transformation require redesigning of both internal and customer-facing processes. The integration of intelligent automation and decision capabilities into their operations can help the banks eliminate paperwork as well as manual processing. This enhances customer service experience while also reducing the cost-to-serve to a bare minimum.

The creation of data-driven services is dependent on the ability to build, design, test, and deploy processes that embed predictive models via new artificial intelligence learning techniques and well-established statistical methods. The process involves trying different approaches, testing the results, and iterating on the candidates offering maximum potential.

Problem with Legacy Infrastructure:

Bank’s traditional IT architectures that are built around legacy on-premises systems are designed in a manner that makes it difficult to forecast the type of infrastructure the bank will require for upcoming projects. Different machine learning algorithms, for instance, run best on hardware that has been specifically optimized for that particular category of model building. A cluster of servers with a particular configuration of memory and processors might only work well for a small subset of work. Any attempt to change the approach might lead to high fixed costs and longer lead time to get the right infrastructure.

Cloud-Based Analytics Promise:

 The cloud gives you the freedom to spin up any infrastructure in literally no time. It also enables scaling or shutting of the business within minutes basis the results. You are freed from dependencies on departmental silos and other quirks of your internal network when working in cloud environments. Allowing the cross-functional teams to collaborate freely enables you to build models that combine domain knowledge from different areas of the bank and create opportunities that were impossible in the past.

The Right Tool for the Job:

A seamless transition can be achieved in a hassle-free manner with the help of the right data migration assistant. The banking industry has leveraged cloud for its unrivaled elasticity, scalability, and advanced analytics. When transforming analytics into the cloud, many banks are concerned with the effort, cost, time, and the risk involved.

Impetus has helped over 100 banks in successfully transforming and securing their business on the cloud and provides one of the best solutions for the job.

 


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About Jatin Sharma Advanced   Writer

6 connections, 0 recommendations, 120 honor points.
Joined APSense since, August 9th, 2018, From New Delhi, India.

Created on May 26th 2020 00:59. Viewed 113 times.

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