Beyond RPA

Disruptive forces playing in the market economy will enforce organizations to re-invent 4 quarterly rolling planning/ bi-weekly CEO reviews. IA is set to principally change what we do, just as process automation (RPA) did when it was introduced into the world of customer experience, employee experience, business ops, applications, infrastructure, and data.  Collaboration between intelligent automation technology and AI is a movement meant to spotlight and anthropomorphize the system to ALT 

“Adopt,” “Learn,” “Think.”

This is helping us develop smarter, more customized BOTs, improve the performance of global operations (business ops, application, infrastructure, and data) and enhance customer experiences and new revenue in many industries.

  Things are looking promising:

But, there is still a long way to go before we have systems that do better at decision-making, display emotional and ethical capabilities. 

First Wave, Second Wave, Third Wave of IA Continuum Organizations continue to invest much time and effort into “systems that do,” such as RPA, but they are really eager for “systems that think and learn” to add a more pragmatic element to our daily lives.

DO: RPA works best with structured inputs and hardcoded business rules as the primary automation capability if a system is able to execute and decide autonomously. 

Think: IT service automation systems are able to analyze a user-generated request or trouble ticket for a keyword or other event triggers, based on embedded algorithms and logic, programmatically thinking and making decisions. Their performance even improves over time as a comprehensive history of resolution data grows to help programs improve logic and future decision-making.

Learn A range of fast-evolving AI technologies to transform systems to analyze vast amounts of dynamic and unstructured input and execute processes that are highly dynamic and non-rules based. In a sense, these learning systems apply rules based on context and make optimized adjustments for it. This improves the human side of an organization’s operations, with people more empowered to think creatively. The speed of advances in automation through Artificial Intelligence is phenomenal and certain. Coforge Tech is uniquely equipped to develop a system with a smart and humanistic approach to IA.

Where does the rubber hit the road with this delicate balance?

In the US the Fed has cut Fed Funds rates and pumped in excess of $1.5 Trillion into liquidity relief for banks to keep them viable. Other central banks including the European Central Bank have infused liquidity in similar ways, but ultimately consumers will only care about how this affects them. We feel that this consumer sentiment will be a key indicator of which financial service.  

Why is IA part of our daily lives today?

IA, part of our daily lives In the French banking sector, IBM’s Watson solution has been rolled out in Credit Mutual to almost 20,000 customer advisers. The aim is again to optimize employee productivity, suggesting answers that advisers can offer on questions about savings and insurance products and processing emails more quickly thanks to customizable replies. 

The current wave The development of new algorithms, described as machine learning, put AI back on the menu in the 1990s. Then, in March 2016, deep learning – a variant of machine learning – became a buzzword in the wake of AlphaGo, AI developed by Google subsidiary DeepMind, beating one of the best players in the world at a strategy game called Go.  AI is now focusing on specific areas, such as medical diagnosis, bank fraud detection, assisted driving, and the development of personal assistants. It has become a driving force behind some highly practical, and commercially exploitable, innovations.

Key points

How Coforge can help?

How will IA evolve? Types of learning “do” systems have in use:

For e.g, our HR virtual assistant bots have a CV, an HR file, and even a telephone number in the Coforge  Tech internal directory. They have the capability to deliver a first contact resolution rate of 78%, the next 13% requests with help from colleagues and the last 9% are through only human intelligence.   Predictive analysis to anticipate the future, log in using biometrics, and receive support from intelligent virtual assistants to reduce operational cost with better quality & better experience involving:

Customer services make possible other activities beyond answering questions, such as the simplification of identity authentication processes through face or voice recognition.

Coforge Tech Business Ops Bots have a microservice, a composable architecture, and even a choice of cloud provider (MAG) footprint within our IA platform. They deliver an accuracy rate of 83% and the next 16% with precision help from human colleagues for deep learning. 1% is the error rate.

Key points

How Coforge can help?

Can IA revolutionize?  

Business KPIs can be Improved 

Fully leverage machine and human collaborations 

[illustrative]

IA Case Study: Customer Experience, Cost Reduction The claim experience journey [insurance carrier]

Client overview:  Our client, one of Australia's largest airlines initially started offering seven return flights a day between Brisbane and Sydney and this has since been expanded to cover all the major Australian cities and many holiday destinations

Drivers/Challenges:

Key points

The Coforge Tech differentiators