Artificial Intelligence
RPA and Artificial Intelligence – Five Questions
BOSTON, March 17, 2020 (GLOBE NEWSWIRE) — Indico CEO Tom Wilde sees a shifting landscape ahead for AI and RPA users as enterprises look to move their process automation efforts forward. Some of the major themes he’s watching include: RPA’s adoption problem; the poor viability of AI-only projects; explainability as a new standard for AI; the opportunity in scalable decisioning; and the emergence of Automation Centers of Excellence.
1. Is RPA at an Inflection Point?
RPA continues to be one of the hottest areas of enterprise tech. And it will continue to grow rapidly as it gains new users in small and mid-size enterprises. According to Gartner, most of the inquiry calls it received from users are from new users just getting started. That suggests there is still huge potential for continued growth. However, those users trying to expand their use of RPA are discovering real limits – both in the technology and within their organizations. According to Gartner, only a small percentage of RPA users have expanded their implementations across the enterprise. For one, it requires organizations to re-engineer business processes. That takes time. Additionally, RPA has some built-in technological limitations. While it’s great with repetitive, deterministic businesses processes involving structured data — where there is no judgment involved. However, it does not work when it is required to make judgements about information or learn and improve with experience. These type of workflows require some level of cognitive ability. They also make up the majority for many enterprises today; e.g., contract analytics, audit planning and reporting, RFP analysis and composition, sales opportunity workflow automation, customer support analysis and automation, appraisal and claims analysis, etc. 2. Can AI-Only Projects Succeed?
According to Gartner, only 15-20% of enterprise AI projects are ever designated for production use, and only about half of those projects actually make it into production. The reasons vary. Projects drift and get pushed aside due to changing priorities and solutions fail to deliver, but the most common issue is that enterprise users underestimate the ecosystem in which AI has to run. There are a lot of things to consider: infrastructure, process, people, organizational structure, business sponsorship – that impact how AI will run (or not), but the reality is that too many AI-projects start as data science projects—entirely disconnected from the business, with no clear business outcome or KPIs in mind.
Experimentation is important, but without a defined business outcome, projects are doomed. Users must ask themselves, why they are using and what business outcome will it achieve.3. Is Explainability Becoming a New Standard for AI-Powered Initiatives?
Everyone agrees that RPA, AI, Natural Language Processing (NLP) and Intelligent Process Automation (IPA) technologies can all add tremendous value by automating mundane tasks and allowing people to focus on more important things. Unfortunately, there have been problems realizing those benefits in practice: Many have experienced AI that is so complex, and NLP capabilities that are so cutting edge, that non-technical people will never be able to understand them.Most solutions have been integrated behind the scenes so that you don’t have to worry about how it works. But if you want to change anything, you’re out of luck.When your AI algorithm makes a decision to do something or to take some action, business users (and in some cases, regulatory bodies) need to know how it reached that conclusion. It’s less about how the algorithm works and more about why it makes decisions the way it does. They want an audit trail. In our experience, about 80% of AI errors can be tied back to bad training data. The problem is finding it. It is really important to tie every prediction that your algorithm makes back to training data so you can figure out why it made the decision it did. The other reason is to prevent unintended bias. Most AI models are trained on some historical behavior or reference. The ability to understand how an algorithm is making decisions can surface potential problems.4. Will Automation Centers of Excellence Become Best Practice in Large Enterprises?
As more and more enterprises look beyond the hype of digital transformation and focus on putting it into practice via business process automation, we’re seeing the emergence of Automation Centers of Excellence—teams tasked with identifying the best opportunities for automation in an organization and finding the right solution to accomplish that goal. Sometimes that may be RPA, but in others it may be AI or IPA. These groups are responsible for defining clear KPIs and business outcomes for each use case and connecting data science and technology with lines of business so best practices can be applied more quickly across an organization. Today, we see this most commonly in financial services, but we expect to see more Automation CoEs in manufacturing and healthcare in 2020.5. Is Scalable Decisioning A New Power Use Case for AI?
One of the big goals of process automation is the ability to speed accurate decision-making to accelerate cycle time. To date though, business process management (BPM) and RPA efforts have stalled in this area – due to the limitations of hard-coded rules-engines and taxonomies. If the decision is not binary one, defined by pre-existing conditions, these technologies cannot make one.New applications of AI and deep learning are changing this though. By adding the cognitive ability of deep learning to process automation, users have the ability to automate a much larger percentage of business process decisions and minimize the manual intervention required in those processes. We are already seeing these capabilities being applied to a number of enterprise use cases such as contract analytics, regulatory compliance, customer support analysis, insurance claims analysis, and more. In legal departments, for example, contracts that are out of compliance, can easily be automatically flagged for manual review, vs. having a highly trained legal resource comb through volumes of pages to determine which contracts are in and out of compliance. About Indico
Indico is the leading provider of Intelligent Process Automation (IPA) solutions. We help organizations turn process into profit by enabling them to automate manual, labor-intensive, document-based workflows. Our breakthrough in solving these challenges is an approach known as transfer learning, which allows users to train machine learning models with orders of magnitude less data than required by traditional rule-based techniques. With Indico, enterprises are now able to deploy AI to unstructured content challenges more effectively while eliminating many of the common barriers to adoption. For more information, visit https://indico.io/.Media Contact:
Jeremy Stinson
Indico
508.277.7837
Artificial Intelligence
GEEKOM releases a perfect mini PCs with dual 2.5Gbps Ethernet ports – GEEKOM GT1 MEGA
TAIPEI, Sept. 20, 2024 /PRNewswire/ — GEEKOM, a Taiwanese tech company also known as the Green Mini PC Global Leader, recently released a strong lineup of flagship mini PCs with Intel Core Ultra processors and dual Ethernet ports, making it possible for users to enjoy impeccable performance and superb networking functionalities at the same time.
One of these mini PCs is the GEEKOM GT1 Mega, which employs a beautiful aluminum chassis with plenty of I/O, including two full-function 40Gbps USB4 Type-C, six USB Type-A, 2 HDMI2.0, a 3.5mm audio jack, an SD card reader and dual Ethernet ports. The two Ethernet jacks are both of 2.5Gbps standard, which not only delivers high-speed and reliable internet connection for people’s daily computing chores, but also enables the mini PC to serve more sophisticated networking functionalities as a soft router, a virtual machines, a hardware firewall, or even a home server. Besides, dual Ethernet ports can separate internal and external network connections, providing logical and physical separation of trusted and untrusted network traffic and keeping data safe from potential cyber-attacks.
The GT1 Mega is powered by Intel’s latest and smartest Core™ Ultra processor (up to CoreTM U9-185H) and dual-channel DDR5-5600MHz RAM. Thanks to the new CPU, GPU, and NPU three tier multi-processing architecture, the mini PC is ready to harness the superpowers of Artificial Intelligence. It is compatible with more than 500 AI models across 20+ categories and supports high-performance low-power processing in a wide range of computing scenarios, which include enhancing facial features and blurring the background during video calls, removing the vocals from songs to create karaoke tracks, and generating large-scale images based on texts or voice commands. Basically, the GT1 Mega allows users to finish tasks that used to take hours or even days through only a few keystrokes!
The GEEKOM GT1 Mega,is now available on GEEKOM’s official website.
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SAN FRANCISCO, Sept. 19, 2024 /PRNewswire/ — Lucinity and Sift have announced a partnership, unifying fraud and Anti-Money Laundering (AML) into Lucinity’s integrated FinCrime compliance platform for case management, agent-enabled workflow automation, and Generative AI.
Sift is an AI-powered fraud platform securing digital trust for leading global businesses. Its Global Data Network analyzes more than 1 trillion events and identity signals per year to prevent fraud across the entire consumer journey. Lucinity and Sift formed this new partnership to address the challenges of fragmented fraud and AML systems, aiming to centralize and enhance financial crime investigations.
Sift’s AI-powered solution will now be integrated into Lucinity’s platform. This collaboration enhances Lucinity’s ability to provide a seamless and efficient compliance solution. It allows teams to review and manage fraud alerts more effectively through Lucinity’s unified Case Management system, thanks to the native integration between the systems. Key benefits to Lucinity’s users include:
Real-Time Fraud Screening: Payments are screened for potential fraud in real time, utilizing Sift’s fraud detection capabilities.Automatic Payment Holds: Payments suspected of fraud are temporarily held, ensuring verification before processing.Streamlined Reviews: Compliance teams can conduct thorough reviews of flagged payments within Lucinity’s Case Management solution.Risk Level Adjustments: Fraud detection parameters can be customized to adjust sensitivity levels, adapting to emerging fraud trends and risk appetites.This partnership also enables users to leverage Lucinity’s Generative AI capabilities through the Luci copilot to investigate fraud cases more efficiently.
Udi Nessimyan, President and Chief Revenue Officer of Lucinity, comments, “One of the greatest challenges in fighting financial crime is fragmented systems and data. Our partnership with Sift helps address this challenge by providing a centralized platform for various case types, including AML, fraud, sanctions, and ad hoc cases. Our collaboration significantly enhances the productivity of investigation teams, reducing the time spent on cases from hours to minutes.”
Sift’s Chief Marketing Officer, Armen Najarian, emphasizes the collaborative effort to enhance financial crime prevention, stating, “Cybercriminals are increasingly leveraging AI to bypass traditional anti-money laundering and fraud controls, creating sophisticated and dynamic threats. To combat these evolving risks, companies must adopt a ‘fight fire with fire’ approach by leveraging AI-powered solutions. Through Sift’s partnership with Lucinity, businesses can stay ahead of fraudsters, ensuring robust protection against abuse and enabling fearless growth.”
About Sift: https://sift.com About Lucinity: https://lucinity.com
Media contact:Celina [email protected] +354 792 4321
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Artificial Intelligence
Employee Background Check Software Market Size to Grow USD 828.8 Million by 2030 at a CAGR of 4.9% | Valuates Reports
BANGALORE, India, Sept. 19, 2024 /PRNewswire/ — Employee Background Check Software Market is Segmented by Type (Cloud-Based, On Premises), by Application (SMEs, Large Enterprises): Global Opportunity Analysis and Industry Forecast, 2024-2030.
The Global Employee Background Check Software Market was valued at USD 587 Million in 2023 and is anticipated to reach USD 828.8 Million by 2030, witnessing a CAGR of 4.9% during the forecast period 2024-2030.
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Major Factors Driving the Growth of Employee Background Check Software Market:
The employee background check software market is growing due to increasing demands for secure hiring processes and regulatory compliance, especially in industries such as finance, healthcare, and IT. As companies look to reduce risks associated with fraud, legal liabilities, and workplace safety, background checks are becoming a critical part of recruitment processes. The rise of remote work has further accelerated the need for digital solutions. However, challenges include concerns over data privacy and varying legal frameworks across regions, which may slow adoption in some areas.
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TRENDS INFLUENCING THE GROWTH OF THE GLOBAL EMPLOYEE BACKGROUND CHECK SOFTWARE MARKET:
Cloud-based background check software is gaining traction due to its scalability, remote access, and cost-effectiveness. With cloud-based systems, businesses can streamline their hiring processes, particularly when operating across multiple locations. The ability to access data and conduct checks in real-time is highly valuable for organizations managing large workforces or remote employees. The flexibility and lower upfront investment of cloud-based solutions make them popular among businesses seeking efficient and adaptable systems for their recruitment processes.
On-premises solutions remain important for organizations with strict security and data control requirements, such as those in government, defense, or finance. These companies often need complete ownership of their data, which on-premises software offers, reducing the risk of external breaches. Although it requires significant upfront investment and maintenance, on-premises software provides a high level of customization and security. It’s especially useful for businesses dealing with sensitive information and industries where compliance with local data protection laws is critical.
Large enterprises, particularly those operating in regulated industries like banking and healthcare, are the major adopters of employee background check software. These organizations deal with large volumes of hires, making streamlined background checks essential for compliance and operational efficiency. The ability to integrate background check systems with existing HR tools, such as applicant tracking systems, allows large companies to manage their recruitment processes more effectively. The need for comprehensive and accurate background checks is crucial for mitigating risk and ensuring legal compliance.
The rise in remote working has increased the demand for background check software that allows companies to vet employees regardless of their location. Digital background checks, particularly cloud-based ones, make it easier for organizations to screen remote workers efficiently. This trend is expected to continue as more companies adopt hybrid or fully remote work models, where geographical barriers no longer restrict talent acquisition but require thorough and remote-friendly verification processes.
As regulatory frameworks for employment practices become more stringent globally, businesses are increasingly relying on background check software to ensure compliance. Laws like the General Data Protection Regulation (GDPR) in Europe and the Fair Credit Reporting Act (FCRA) in the U.S. have made it mandatory for companies to conduct background checks within specific legal parameters. This has led to increased demand for software solutions that can automate these processes while maintaining compliance with regional and international laws.
A major trend in the employee background check software market is the integration of these solutions with human resources management systems (HRMS). Integrating background checks with HR software streamlines the hiring process by consolidating background checks, employee records, and onboarding into one system. This improves operational efficiency for businesses, particularly large enterprises that handle significant recruitment volumes. Integration with HRMS allows for real-time updates, making background screening an even more integral part of the hiring process.
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EMPLOYEE BACKGROUND CHECK SOFTWARE MARKET SHARE
North America dominates the market due to stringent employment regulations and widespread adoption across industries. Europe is another key region, driven by GDPR compliance and demand in finance and healthcare. The Asia-Pacific region is experiencing rapid growth due to increasing awareness of the importance of background checks, especially in countries like China and India, where digital hiring platforms are becoming more popular. The market is also expanding in the Middle East and Africa as businesses prioritize secure hiring practices.
Key Companies:
HireRightGoodHireCheckrSterlingHireologyINTELIFIGood EggPeopleG2VitayCertnGlobal HR ResearchVeritable ScreeningXrefZincPaycomADPVICTIGIntelliCorp (Cisive)SpringVerifyAsurintUniversalAssureHireVerified FirstHireSafePurchase Chapters: https://reports.valuates.com/request/chaptercost/QYRE-Auto-2A10579/Global_Employee_Background_Check_Software
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