https://www.analyticsinsight.net/top-10-artificial-intelligence-ai-trends-watch-2021/
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App development and automation with AppSheet’s no-code platform
RPA Challenge with Open RPA
Typical Robotic Process Automation (RPA) Use Cases
Technological Innovations and Pandemic Analysis Till 2030: Robotic Process Automation Market – The Daily Chronicle
Using cognitive tech to connect customers to business operations
Creating an engaging customer experience is more readily achieved by embedding increasingly sophisticated digital and cognitive technologies into the very fiber of an organization’s processes, from its front office right through to its back office.
Successful organizations are both strategic and nimble, leveraging the power of real-time data to reduce inefficiencies and enhance their effectiveness. Agile businesses predict their customers’ needs before their competitors do. More importantly, they have the ability to act on those predictions, which is essential for getting ahead in today’s global digital economy. Investment in cognitive technologies (those which mimic human thinking and have the capability to learn) will be required for having intelligent operations in the enterprise. An intelligent enterprise has the ability to inform and implement better business decisions by leveraging data and smarter technology.
In a study conducted in partnership with IPsoft, HfS Research interviewed 100 C-Suite executives to understand their views, expectations, and strategies, along with their investment plans for cognitive technologies. This report discusses opportunities and challenges that business leaders see for moving their organizations toward being truly intelligent—knowing their customers, using technology most effectively, and infusing cognitive technology into the fiber of their business operations.
Table of Contents
- Smart investments in cognitive tech will help solve business problems and collapse internal barriers
- C-Suite executives seek to align operations with business outcomes
- Cognitive Agents are at the Forefront of Investments
- Cognitive Tech is Driving Intelligent, Self-Learning Business Operations
- Intelligent operations of the future: cognitive is a lever for theOneOffice core
- OneOffice by Definition
- Impediments to OneOffice: The Challenges of Aligning the Enterprise
- How to track the impact?
- Using cognitive glue to construct OneOffice
Source: Hfs-Using cognitive tech to connect customers to business operations
Artificial Intelligence-Powered Robots Won’t Kill Banks
The elimination of millions of jobs by battalions of artificial intelligence-powered robots makes for sensational headlines. But like many stories regarding both the threat and opportunity from technological change, the real story is both more nuanced and more interesting.
A recent report from the World Economic Forum predicted that intelligent automation could eliminate five million jobs in developed countries by 2020. So, you would think a recent spate of announced job reductions in Japanese banking over the next decade – over 30,000 in total at the three major banking groups – would be a cause for concern. Instead, on a recent trip to Tokyo, I heard from a senior executive at one of those banks that automation is vital to deal with a shrinking labor force as the country ages, and that busy robots are a better alternative for the country than unfilled job vacancies.
Despite this story of long-run job displacement in Japan, it’s wrong to conclude that intelligent automation will inevitably lead to fewer jobs in the financial services industry. Indeed, recent Accenture research suggests that – for those firms who embrace intelligent automation – revenues could rise by 32% by 2022, but critically employment could also increase 9%.
Just as in every other industrial revolution, job growth will also be associated with job change and evolution. Crucially, the nature of many jobs will reflect new partnerships between man and machine. Humans will be required to teach, monitor, and maintain the automated technology, while intelligent automation will amplify and improve human skills and judgement. Of course, there will be areas in banking where machines will fully displace humans, but those roles will typically be in areas where the work is tedious and repetitive for current employees. There will also remain many roles that require creativity, empathy, and judgement, where machines will continue to play a limited role for the foreseeable future. Ultimately, if we can better understand and define the symbiotic rather than destructive relationship between man and machine, we will be able to create not only more jobs, but also more interesting and higher value-added roles in the financial services industry.
Accenture’s recent 2018 North America Banking Operations Survey finds that this transition has already begun, with many firms using data and artificial intelligence to improve all manner of processes, from customer service to employee training. 22% of North American banks are already using AI, machine learning, and natural language processing, and another 55% intend to do so within the next year. Nearly one in five banks are already using robotic process automation technology and another 63% plan to do so within a year. The research also shows that many North American banks understand the symbiotic nature of these relationships, with 54% of firms saying human-machine collaboration is important in achieving their strategic goals.
Accenture’s global Talent & Organization lead for financial services, Andrew Woolf, says the challenge for banks, insurance companies and others is to “pivot their workforce to enter an entirely new world where human ingenuity meets intelligent technology to unlock new forms of growth.” While it is easy to point to job losses from increased automation, there are also many examples of humans being augmented by technology to improve their productivity and the service they provide to customers. For example, we have seen a proliferation of robo-advisers in wealth management over the last few years. In some situations, they provide automated advice to consumers who often can’t afford to pay the fees associated with traditional financial planning. However, in other situations, rather than replacing financial advisers, AI now makes those advisers more productive. Fintechs like AdvisorEngine can support the asset allocation process, leaving advisers with more time to focus on personalizing advice for clients and doing what humans do best – building relationships. As one senior wealth management executive commented to me “A machine can put a large inheritance into the right investment portfolio, but it can’t ask you what your parents did to accumulate that wealth and express appropriate sympathy at their passing.”
AI is also helping to reduce risk and lower compliance costs. AI and natural language processing can be used to automatically produce anti-money laundering and know your customer (KYC) reports, and to gather data for regulatory stress tests. Using AI for such tasks can cut bank compliance costs by up to 30%, according to the International Banker, saving billions. This automation also spares the thousands of risk and compliance staff who have sat in large warehouses since the financial crisis the tedium of repetitive, mundane tasks and frees up their time for more rewarding work.
Even when robots are deployed in customer-facing roles, there will still be plenty of need for humans to train and maintain them, as even the best struggle with the nuances of human behavior. For example, bots struggle with recognizing such things as sarcasm, and while platforms like Alexa may be able to fake a sense of humor on demand, they are still a long way from being able to handle the full range of human emotions. So, just like a puppet, the robot will need a human to figuratively pull its strings as it learns to navigate the complex, subtle and often culturally-specific landscape of human interactions.
Similarly, humans will need to be able to explain automated decisions to make sure banks don’t fall afoul of regulators: A machine can make credit decisions about whether someone should get a credit card or an auto loan based on the factors it is programmed to look at, but there also need to be processes in place to make sure those decisions don’t discriminate based on race or geographic location. As American Banker notes, “AI has yet to prove that it is more capable than humans in avoiding both safety and soundness and consumer protection pitfalls related to credit decisions. Indeed, humans will still be involved at key steps in the process.”
Ever since the computer HAL went berserk in the 1968 movie 2001: A Space Odyssey, people have worried that humankind might be usurped by machines. The reality in banking will likely be evolution not revolution, with the machines taking on the tasks they are best suited for and the humans focusing on what they do best. However, there will also be a huge array of activities where it will be the ability to combine the humans and the machines that will separate the leading banks from those who will struggle to thrive in this new world.
Source: Forbes-Artificial Intelligence-Powered Robots Won’t Kill Banks
How Robotics Process Automation (RPA) Will Disrupt Real Estate
Digital transformation is changing the rules of business and competition in the financial industries. Established sectors, such as Real Estate, face new challenges and opportunities due to emerging technologies such as Robotics.
A lot of technological advancement is happening right now around front end retail customer experience and related applications in this space, however back office functions in the Real Estate are still deploying heavily manual processes with no automation, and currently driven by spreadsheets with no leverage on the large data sets available.
It is not surprising that many managers are pushing for a transformation to a more efficient, transparent and structured business environment. One of the big assets of the real estate industry is its richness in available data. The opportunity lays in a holistic solution of not only collecting, but also analyzing and reporting data in order to support and deliver proactive and predictive management support and decision making.
Robotics Process Automation (RPA) is one of the digital technologies that is starting to impact various processes across all players of the Real Estate sector and will unlock long existent pain points. It can help capture, validate and process financial and non-financial data in a far more efficient way.
Robotic has already impacted and is being deployed across many industries, which have been early adopters of technological advancements and is bringing in benefits such as operational efficiency, manual effort reduction, reduced error rates, improved customer satisfaction and even increasing employee engagement.
RPA technology enables a virtual workforce that works faster than a human worker, does not make mistakes, requires no monitoring and can work around the clock. The virtual worker’s activities can be logged and operational metrics can be closely tracked in order to improve or readjust the process flow.
RPA undoubtedly changes the business landscape as it eliminates the need for repetitive and highly manual labor. With increasing coverage of automated processes, a different level of skills is required, namely, the need for people who can create, maintain and define the requirements for automation, as opposed to people who actually process transactions. Preparation and re-skilling is key for both employees and employers.
As more routine tasks and activities become automated, workers can leverage RPA to perform more strategic and high value work and services. RPA also creates solutions in regards to other human labor shortages resulting from demographic trends, weak education systems and under motivated staff.
Some of the biggest benefits of RPA are:
- Support in eliminating low value added repetitive tasks and helps process owners to focus on analysis and strategic decision making
- Faster payback period, as by creating a robotic automated process once, it can be easily scalable, tweaked and become more productive, gaining back the investment in six months to a year
- Better transparency and visibility into processes and the ability to capture detailed data more effectively, with greater accuracy, fewer errors, and less risk of fraud
From a back-office standpoint within the Real Estate value chain, software robots can take control over routine and manually intensive processes. This will save significant time, provide more accurate results, leave a clear audit trail and free up human capital for more value-added and judgment-based functions such as strategic analysis and decision-making. From a front office, customer-facing standpoint, system data can be paired with unstructured data from social media, blogs and other profiles to more accurately gauge the needs and preferences of the customer, allowing for more tailored experiences.
In order to evaluate the right processes that could be automated, the following criteria could be assessed:
- Data intensive
- Repetitive in nature
- Rule-driven
- Multiple- systems
- Electronic trigger to the process
- Involve manual calculation
- High error rates
Applying above criteria across the RE value chain, some of the key processes, which could be potentially be a good candidates for the Robotics, includes:
In order to get started on the Robotics journey, the approach starts with the ideation stage, which identifies the activities to be automated. This process is followed by the creation of business cases. Certain processes are selected based on the business case, followed by development of the prototypes and proof of concepts. Afterwards, the roll-out phase is performed using agile methodology, with automation of processes being done in parallel to coaching of selected employees within the clients’ organization, enabling internal resources to further develop, maintain and modify the robots independently.
Real Estate Operations
- Investor AML/KYC
- Vendor and customer setup
- Deal sourcing research
- Entity & property set up
- Common area maintenance
- Portfolio monitoring
- Portfolio management and reporting
- Budgeting and forecasting
- Partner data consolidations
- Contract management etc.
Finance
- Bank & Account reconciliations
- A/P payment processing
- A/R cash application & follow up
- Fund accounting
- Consolidation
- Financial Planning
- Standard journal entries
- Intercompany reconciliation
- Tax filling
- VAT and TAX preparation, etc.
Source: propertyeu.info-How Robotics Process Automation (RPA) Will Disrupt Real Estate
HfS Webinar: Blockchain in BFS – Client Experience and War Stories
Source: Hfs-HfS Webinar: Blockchain in BFS – Client Experience and War Stories
Fly by Wire or Fire and Forget – Augmented Versus Artificial Intelligent Automation?
This is the third and most likely final in a series of articles on the evolution of my Augmentation Intelligent Automation Theory and Practice over the last eight years. The first in the series, “Cybernetic Robotics – The Future of the Claim Processing Professional” was published in October of 2013. It was illustrated by the Giant Robot and Woman that became my Pareto Automation brand logo. It is the quintessential depiction of Intelligent Augmentation on several levels. Intelligent Augmentation is where humans supply intelligence to software robots. I am not talking about RDA. Where humans interact with desktop automation software to provide exceptions handling real time. Rather, very sophisticated RPA Digital Workers, which are detailed in the second and my most read article, “Autonomics or Cybernetic RPA?” published in July of 2016:
https://www.linkedin.com/pulse/autonomics-cybernetic-rpa-john-slagboom/
The two Visios that illustrated that article are now on either side of the Pareto Automation brand logo. They represent the technology of Autonomics (original definition) or Cybernetic Intelligent Augmentation Automation: a very advanced RPA Digital Worker to the left and equally advanced Rules Engine controller on the right. When combined, they provide a de facto remote-control process automation capability or as I will illustrate by analogy a very advanced “Fly by Wire” technology.
I waited a few weeks after publishing the pinnacle of my research and writing efforts: “ROC – How to Artifact” to see if I had anything further to say? This 55-page document (a free 31-page version is available at my website https://paretoautomation.com/) is the result of reviewing all my writings and related documentation over the last few of years to prepare for my speaking engagement at SSON’s 2018 Intelligent Automation World Series last month.
Last week, I woke up for the third time and realized, I had one more thing to say.
I am convinced, that a Billion dollars of annual cost savings still resides in the five percent of Managed Health Care claim automation between 88 to 92 and 93 and 97% adjudication range. There is a four % difference in the start and end points of the five-point range depending on the type of claim system and contract complexity. Now that AI Hype is clearing (I was affected too) and the root causes of significant process automation implementation failures are increasingly traced to business model/culture change management issues. Human Centric Augmentation approaches to Process Automation are gaining the increased credibility they deserve. I am confident that Augmentation Intelligent Automation techniques can automate that 5% for perhaps a third to one half the cost of Artificial Intelligent Automation techniques.
Put simply, Rules Engine Controlled RPA Digital Workers with good OCR and perhaps NLP to access unstructured data, using an Ops Dev business model facilitated by a Culture of Trust that fully engages and empowers front line operations leaders and experts, can automate extremely complex and fluid back office processes far more economically than AI based solutions in many, perhaps most Use Cases.
This is not to challenge the wisdom of investing in AI technologies. They are the Future in many, perhaps eventually most business process automation applications, rather they are not ready yet for most demanding processes and even when they become so, may not be cost effective.
Consider the following analogy between three types of anti-tank missile technologies, which are currently used by every major military in the world: Wire, Laser and Radar Guided missiles. None are fully autonomous. They all require a human to acquire the target and make the launch decision. This corresponds to the fact that even various forms of Machine Learning, requires significant human interaction to create, monitor, validate, and fine tune. Still, decision judgment Machine Learning based AI, once sufficient accuracy levels are attained is self-directed, albeit “Fire and Forget”, which can translate into significant capability advantages over systems that require human decision intelligence.
However, Wire or even Laser guided missiles, where humans guide the missiles all the way to the target using sophisticated computer optical or laser technologies makes the guidance easy to provide and almost fool-proof in terms of reliability and accuracy compared either to the more advanced radar guided missiles or obsolete wire guided technology that required significant human skill to acquire and steer the missile all the way to the target, leaving a lot of opportunity for technical failure and human error.
Wow John, that is a great education on Anti-Tank Missiles! What the heck does that have to do with the comparative advantages and disadvantages of various Automation Technologies?
Early generation “Fly by Wire” automation like .Net Macros and first-generation RPA, while a significant efficiency improvement over various non-guided anti-tank weapons (manual processes) are now obsolete. They correspond to Robotic Process Automation or “Humans Augmented by Robots” in the Automation Continuum that follows. Second generation RPA has many enhancements, which improve efficiency and effectiveness. These can be likened to Computer Optical enhance “Fly by Wire” missiles like the ubiquitous TOW; first operational in Vietnam and alive and well in over 45 militaries on over 15 k platforms today. They correspond to Autonomics or “Robots Augmented by Humans”. A variant of the “Fly by Wire” is the laser guided Hellfire. It cost twice as much as the TOW. However, it has significant advantages like twice the range and laser illumination by a platform remote to the launcher, which greatly increases agility and survivability. This can be compared to extending the ROI range of RPA with OCR and NLP to automate workflows that require unstructured data and Computer Vision that increases automation stability.
There is radar guided version of the Hellfire, which would correspond to Cognitive Computing or “End to End Robots, with Human Oversight”. Again, the advantages of true “Fire and Forget” technologies are manifold; however, they are notoriously hard to perfect in terms of reliability under the full range of operational contingency; something the recent death of a pedestrian by a self-driving Uber car vividly illustrates and are very expensive. The radar guided Hellfire is approximately three times the cost of the laser guided variant.
Sylvan Design Automation Continuum – Notice the resemblance of “Autonomics” or “Robots, augmented by Humans” to the Pareto Automation brand logo that illustrates the article!
Advanced “Fly by Wire” technology has been operational for close to fifty years now and “Fire and Forget” for over twenty. These technologies are all extremely effective tank killers, yet vary greatly in cost per unit. The take home point of the analogy? The older, more simple technologies can continue to have significant usefulness in certain applications long after newer technology arrives on the scene. Because it may not be superior or cost effective in every or even most applications. Consensus is building it will be the same with Process Automation.
PS – I had a lot of hesitation writing this article. I am not sure it really offers useful information and of course uses another hard to relate to military analogy! Sorry about that really. I wrestled with this for a couple of weeks. The tipping point for me is I just had to have a reason post the illustration. Forget about the text; the picture is worth 10 thousand words!
