Banking on the ‘IQ’ of Robots
The future of Robotics automation seems to point towards a confluence of enterprise systems and intelligent automation.
Photo Credit : perspectives.icicibank.com,
The surge of machines and technology transformed the operating models across the landscape of business and industry. The Industrial revolution of the 18th and 19th century gave way to novel methods of producing goods. Since then, industry has come a long way to the present era of robots and smart assistants as virtual workforce. We have seen robotic mechanisms in the manufacturing world performing various physical tasks, however, the “robotic” presence within the digital world is a relatively new spell for a new journey for everyone on the planet. Here comes Robotic Process Automation (RPA), which is all set with quotients to “think” and “act” as we humans do.
Increasing the IQ of your Business with Robotic Process Automation (RPA)
According to a study by Transparency Market Research, the RPA market is estimated to grow at a compounded annual growth rate of about 60 percent worldwide through 2020 which is profound statistics for the industry.
In the recent years, the RPA industry has evolved extensively and has begun to integrate with more intelligent and self-learning techniques such as artificial intelligence, machine learning, deep learning and natural language processing (NLP) with machine vision. With the advent of artificial intelligence, the RPA industry has evolved from employing rules to crunch data into interpreting and predicting varied forms of data.
This phenomenon is being buzzed as Intelligent Automation (IA).
McKinsey & Company reported that up to “45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies.”
Let us take for example, cash machines or ATM’s. They replaced human bank tellers, are cost effective and easy to maintain. However, they cannot go beyond the coded logic of dispensing cash or statements. The biggest characteristic of Intelligent Automation is that it provides businesses with the ability to ‘think’ as humans do. As enormous amounts of data are fed into these software applications, they are able to crunch, analyse, interpret and even decide the best course of action.
Today the interest to adopt the RPA process is driven by a lot of factors.
- The Gen Y(s) are the customers of tomorrow. These customers will engage in more digital transactions and will expect a better experience. Connectivity Landscape is multiplying rapidly - By 2020, there will be approximately 927 Satellites and 50% of them will enable high-speed Broadband Internet and Wireless Network, Automated guidance of machines, real-time monitoring, logistics etc.
- The future markets will have business models that will blur the current geographical boundaries. New business models with data, analytics, and experience drivers will service new channels that function with open APIs, Robotics and IoT.
- The digital ecosystem is driving a new form of human experience for businesses. The systems are more agile and can continuously provide solutions applying cognitive principles and creative intelligence
The bottom line is that business of the future will be creating differentiators towards "ZERO" - Zero defect, Zero wait time, Zero processing time, Zero Overhead, Zero queue, etc.
Driving RPA in BFSI
The simplest use cases for RPA are within the accounting and finance industry. The automation can be applied to invoices, payment orders, accounting entries etc. Scalability is a huge advantage that is provided by Robotic Automation. Services are today available 24/7 and the volume of digital transactions is growing every day in investments, loan management, credit card, fund transfers and payments. In a move to get out of legacy systems, banking industry is looking at RPA as the solution.
How would RPA assist in banking?
- RPA would be the best fit for back office work which requires efficient and intelligent data-mining. This will assist in onboarding, selling, rewards, comparison, queries, transaction initiation, preference management with high degree of personalization.
- Machine learning can help explore new services, meeting personalization demands and channel optimization. It can also help in cleaning data and giving meaning insights.
- Robotic advisors for Individual / Institutional financial lifecycle management with runtime live Predictive capability.
- Establish bridge between consumers and businesses using Virtual robots and Natural Language Generation with advanced Artificial Intelligence.
- Automate investment portfolio generation and keep changing as per individual preferences anytime including insights on taxes, retirement planning and future plans. Real time advisory on stock market trading might be another powerful offering.
The future of Robotics automation seems to point towards a confluence of enterprise systems and intelligent automation. In this entire cycle, some banks will adopt faster and others will be slower to experiment. But eventually the world will bank upon the transforming enterprises, they will determine the future of banking.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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