Daily Archives: November 29, 2020

Since the 2008 financial crash, financial services have developed their compliance systems at pace. From tools that analyse trades and behavioural anomalies, to those that track and map changing financial regulation manual, error-prone systems are fast becoming a thing of the past. CUBEs Elliot Burgess reflects on the journey of automation so far, and sets out his predictions for the future.

The journey to automation

One area that has seen significant innovation since the 2008 crisis is regulatory change management. Historically, tracking, analysing and mapping regulatory change was a manual process managed by teams of people working from innumerable spreadsheets. The task was laborious; constant scanning of regulatory databases for changes, hours spent establishing whether that change would impact business functions and, finally, manually mapping that regulatory change to existing policies, processes and controls. Highly skilled and valuable compliance team members would spend hours on administrative regulatory tracking.

Fast forward a few years and, mercifully, manual systems have fallen out of favour (though a recent survey byEY found that some financial institutions are still using Microsoft Excel to manage regulatory change). Regulatory change management started to evolve, bolstered by the application of technology. Gone were the hours of manual trawling and tracking; the industry started to see a new wave of regulatory technology (RegTech) designed to capture regulatory information and store it in a digitised library. Often the libraries were filled with high-level regulatory data lacking granularity or any form of standardisation but it was an improvement, nonetheless.

Regulatory change today

As we head towards the tail end of 2020, regulatory technology is at a precipice. Regulatory change management programmes are primed for automation, spurred on by sophisticated technologies including Robotic Process Automation (RPA), Machine Learning (ML) and Deep Learning (DL) techniques, semantic web, big data analytics and Natural Language Processing (NLP), to name but a few. A recent report by CUBE, in association with Burnmark entitled RegTech for Regulatory Change, found that a number of noteworthy financial institutions, including Deutsche Bank, HSBC and Lloyds Bank are all using AI within their compliance functions.[1]

RPA now extracts regulatory data and maps it to business taxonomy and organisation structures with the help of semantic technologies. AI technologies such as NLP, ML and DL do the task of analysing and extracting insights from the regulatory legislation and identifying the impact on relevant businesses. The regulatory intelligence process monitors the remediation journey end to end, from requirement identication to compliance changes, with minimal input from the compliance team. Does this mark the end of the compliance team? Absolutely not. These highly skilled employees are no longer spending hours on low-level administrative tasks and are able to instead focus on implementing regulations and remaining compliance.

Where do we go from here?

But what is the future for automated change management and other regulatory technology? As we mentioned above, some financial institutions are still using manual processes, so of course there will be or should be a further shift to AI and other smart tech. These systems are no longer simply cataloguing the seemingly endless stream of regulatory data, they are employing regulatory intelligence to streamline the process, making it faster, smarter and more efficient. It begs the question; how far can it go?

One prediction for the future is that there may, one day, be a regulatory landscape in which regulators publish regulations through automated systems, which then notify compliance teams automatically. Perhaps all it will take is the press of a button and policy changes will implement themselves. I recently considered this point in the afore mentionedRegTech for Regulatory Change report, in which I noted that regulators are working on discreet projects to improve their delivery of rules or improve the ability to comply and may well, in particular areas of regulation, start with push of the button trials. After all, its already happening with readable regulation use cases. However, I cant foresee that such advanced automation will become mainstream practice until an international standardised operating model is agreed.

In the near term, regulatory technology will grow smarter. Automated systems are only ever as good as the data that feeds them. As the data improves, the AI will be fine tuned allowing for precision and error reduction. Change management systems will inevitably be automated, allowing for consistent, fast results and increased, watertight compliance. Regulatory expectation will, in turn, become stricter: those that fail to automate will undoubtedly catch the attention of global financial regulators. Such attention could be costly.

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The journey to automated regulatory change: how far have we come, and how much further to go? - Finextra

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As per the report, theGlobal Automation Testing Marketis anticipated to witness significant growth during the forecast period from 2020to 2025.

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Key players in the Automation Testing covers :IBMSmartBear SoftwareMicrosoftCigniti TechnologiesMicro FocusParasoftTricentisTestPlantCapgeminiRanorexCA Technologies

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The basis of applications, the Automation Testing from 2015 to 2025 covers:Automation testing tool providersAutomation testing service providersTest organizationsQuality Assurance (QA) providersManaged Service Providers (MSPs)Software developersConsultancy firms and advisory firmsTechnology consultantsGovernments

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The report clearly shows that the Automation Testing industry has achieved remarkable progress since 2025 with numerous significant developments boosting the growth of the market. This report is prepared based on a detailed assessment of the industry by experts. To conclude, stakeholders, investors, product managers, marketing executives, and other experts in search of factual data on supply, demand, and future predictions would find the report valuable.

The report constitutes:Chapter 1 provides an overview of Automation Testing market, containing global revenue, global production, sales, and CAGR. The forecast and analysis of Automation Testing market by type, application, and region are also presented in this chapter.Chapter 2 is about the market landscape and major players. It provides competitive situation and market concentration status along with the basic information of these players.Chapter 3 provides a full-scale analysis of major players in Automation Testing industry. The basic information, as well as the profiles, applications and specifications of products market performance along with Business Overview are offered.Chapter 4 gives a worldwide view of Automation Testing market. It includes production, market share revenue, price, and the growth rate by type.Chapter 5 focuses on the application of Automation Testing, by analyzing the consumption and its growth rate of each application.Chapter 6 is about production, consumption, export, and import of Automation Testing in each region.Chapter 7 pays attention to the production, revenue, price and gross margin of Automation Testing in markets of different regions. The analysis on production, revenue, price and gross margin of the global market is covered in this part.Chapter 8 concentrates on manufacturing analysis, including key raw material analysis, cost structure analysis and process analysis, making up a comprehensive analysis of manufacturing cost.Chapter 9 introduces the industrial chain of Automation Testing. Industrial chain analysis, raw material sources and downstream buyers are analyzed in this chapter.Chapter 10 provides clear insights into market dynamics.Chapter 11 prospects the whole Automation Testing market, including the global production and revenue forecast, regional forecast. It also foresees the Automation Testing market by type and application.Chapter 12 concludes the research findings and refines all the highlights of the study.Chapter 13 introduces the research methodology and sources of research data for your understanding.

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Automation Testing Market 2020 | Outlook, Growth by Top Companies, Regions, Types, Applications, Drivers, Trends & Forecasts by 2025 - The Courier

Massive strides in automation have rippled through the pharmaceutical manufacturing industry in recent years, affecting multiple tiers of the drug development process. Quality is easier to control, processes are easier to regulate and product outcomes are more consistent than ever before.

Relative to proportionate industries, however, "the biopharma industry is comparatively behind the times. Although most biopharma companies and some academic labs use liquid-handling robotics to automate parts of their processes, such as high-throughput screenings, robotics have not been utilized to its full potential through the entire process to improve productivity and product quality," according to an earlier Biospace article.

In the cleanroom environment specifically, the benefits of automation are more than meets the microscope.

"Automation as applied to clean manufacturing has two-fold purposes," said Dave Nobile, Technical Services Manager at Contec, Inc. "In general manufacturing, automation is almost entirely to produce products of a quality greater than can be done by hand. Removing the human variation of a manual process in pharmaceutical manufacturing increases value."

In clean spaces, automation has an additional benefit.

"When you take out the human element, you are removing a huge source of contamination from the cleanroom environment. Machinery has been designed for the cleanroom, so it generates far less contamination," Nobile said in an interview with Biospace.

Dave Nobile is no stranger to contamination control. He fell into a part time job in the field back in 1983, then found himself 37 years later in a fully-fledged career. As a mechanical engineer, much of his background involves product development and process design, with an impressive number of patents for cleanroom products.

Today, as Technical Services Manager at Contec, he primarily focuses on customer interface. Nobile and other experts visit facilities in a myriad of industries, taking stock of company goals, then provide solutions that improve contamination control and reduce product quality risks. According to the company website, Contec is the leading manufacturer of contamination control products for critical cleaning and manufacturing environments worldwide. Our innovative wipes, mops, and solutions are used in various industries across the globe.

Naturally, the COVID-19 pandemic has made physically visiting facilities a seemingly distant dream of the past, but Nobile and his team have adapted to restrictions with a few surprising benefits.

"With available technology and growing virtual finesse, both our team and customers have found comfortable ways around a physical visit. With specific planning for any given facility's situation, we can organize virtual tours using both mobile and stationary onsite cameras," he said.

In addition to the convenience of scheduling a virtual tour, users can now have their footage viewed by more than one subject matter expert. "Before, just one expert would visit a facility. Now, our subject matter experts from all over the world can be virtually brought into a tour, integrating knowledge from multiple continents into a customer's provided solutions."

Over the years, Nobile and his fellow experts have certainly witnessed their fair share of common mistakes and challenges in the pharmaceutical manufacturing space.

"The biggest single issue is employees not following their SOPs, or Standard Operating Procedures. In an automated process, tiredness and other factors of human variation don't exist, he said. With people, it's challenging to do the same exact tasks every day, every month, every year. It's a lot to ask of a person. When you compound this with employee turnover, the issue escalates.

Perhaps the most common challenge of pharmaceutical and other manufacturing comes down to employee training.

"Fundamentally, the biggest mistake in any clean room environment is training an operator to complete a task without explaining why it's meant to be done in that way," Nobile said. "If you tell the operator why each step along the way is important, they understand that contamination can be reduced or that quality can be improved with specificity, and it's much more likely that consistent work will be completed. The why is massively important, not just the what."

Regardless of whether a cleanroom is operated mostly by humans or machines, some level of contamination is to be expected.

"When a cleanroom is originally constructed with no activity, numbers will show that it's perfectly pristine. As soon as you start bringing in equipment, however, the potential for contaminants is introduced. Every piece of equipment will generate contaminants. Introduction of anything in the clean room interrupts air flow," Nobile said.

"As soon as people are introduced, there is an entirely new level of contamination. People are, by far, the most contaminating presence in the cleanroom, Nobile said. In pursuing cleaner and cleaner environments, in-depth studies have shown that whether sitting still or walking vigorously, talking or coughing, the contaminants a person sheds in just the natural act of existing is a far greater contaminant than anything else."

With this being said, removing human operators from the cleanroom certainly reduces the risk of contamination, but will not eliminate it entirely.

"When you automate a process from the equipment perspective, you employ disposable, single-use components for maintenance, Nobile said. There are requirements for specific use and handling when taking machines apart and putting them back together in order to keep the rest of the process clean and functioning. Thus, people are not completely removed from the operations, and new considerations with robotics arise.

In addition to this, full automation in pharmaceutical manufacturing is much less realistic than it has proved to be for other industries.

"Back in the 90s, for example, semiconductor manufacturing really strove to remove the human element," Nobile said. "25 years ago, a manufacturer had nearly 600 people in a cleanroom. Today, you may have as few as 50. Investments were made into automated equipment, utilizing robots in completely sealed and separated manufacturing cells. The cleaner environment leads to greater product quality."

"It's been more difficult to automate pharmaceutical processes due to the constant evolution of manufacturing procedures. Any operation requires stability for automation. For example, tablet manufacturing has remained stable for the past couple of decades, making automation realistic. In pharmaceuticals, there's a lot of hand manipulation due to the novelty of the processes, he said.

Above all, Nobile wants end users to be informed of the immense and valuable resources that are available to them.

"If end users could see the available resources, equipment, and products from companies and manufacturers who are not just ready, willing, and able, but have a vested interest in helping them, their product outcomes would improve greatly, Nobile said. Generally, at no cost to the end user, there are very conscientious, dedicated providers in every field who can help improve processes, remove contaminants, and provide assistance. Patient health and safety depends on it."

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Cleanrooms, Contamination and the Realities of Pharmaceutical Automation - BioSpace