#Robotic Process Automation in Insurance market analysis

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Robotic Process Automation in Insurance Market to See Huge Growth by 2027 | EdgeVerve, Salesforce, Datamatics, Cognizant

Advance Market Analytics published a new research publication on Global Robotic Process Automation in Insurance Market Insights, to 2027 with 232 pages and enriched with self-explained Tables and charts in presentable format. In the study, you will find new evolving Trends, Drivers, Restraints, Opportunities generated by targeting market-associated stakeholders. The growth of the Robotic Process Automation in Insurance market was mainly driven by the increasing R&D spending across the world.

Major players profiled in the study are:

Aspire Systems (United States), IBM (United States), Salesforce (United States), Microsoft (United States), Automation Anywhere, Inc., AutomationEdge (United States), Blue Prism (United Kingdom), Datamatics (United States), EdgeVerve (Infosys) (India), Kofax (United States), Nintex (United States), Paanini Inc. (United States), Pegasystems Inc. (United States), UiPath (United States), WorkFusion, Inc. (United States), Mindtree (India), Appian (United States) and Cognizant (United States)

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Scope of the Report of Robotic Process Automation in Insurance

Robotic process automation is rule-based low code software robotics that allows businesses to automate their operation without a human interface. The growing demand for RPA in the insurance sector to accelerate the digital transformation and automate claim and underwriting processes have boosted the market. Further, the outbreak of covid-19 has created significant opportunities for digital transformation across various business verticals. Rising IT spending of insurance companies and a focus to reduce human errors during claim processing will further drive the global market.This growth is primarily driven by Increasing Use of RPA in the Insurance Industry for Claim Processing and Sales & Distribution of Policies .

In February 2022, Nintex acquired Kryon, an RPA company to expand the intelligent process automation (IPA) capabilities of its Process Platform. With this acquisition, the aim of Nintex is to deliver more advanced automation capabilities to customers and community members.

In March 2022, SS&C Technologies Holdings Inc., a leading provider of software services acquired Blue Prism Group. Blue Prism provides RPA and intelligent automation across various industry verticals including financial services. The acquisition strengthens SS&C’s position and allows combining its RPA technology to offer a full suite of intelligent automation technologies.The key manufacturers are targeting the innovations of the products with better quality, better technical characteristics, and also assist in providing and humanizing the after-sale service to the consumers. The key players are anticipated to keep a stronghold position in the market over the anticipated period. The key players are accepting strategic decisions as well as thinking upon mergers and acquisitions in order to maintain their presence in the market.

The Global Robotic Process Automation in Insurance Market segments and Market Data Break Down are illuminated below:

by Application (Claim Registration & Processing, Underwriting & Pricing, Process & Business Analytics, Sales & Distribution, Others), Organization Size (Small & Medium Enterprises, Large Enterprises), End Users (Insurers, Agents & Brokers), Deployment (Cloud, On Premises)

Market Opportunities:

Significant Growth of Life Insurance Industry In Asia Pacific Region is Likely to create Noteworthy Opportunities for the RPA in Insurance

Market Drivers:

Increasing Use of RPA in the Insurance Industry for Claim Processing and Sales & Distribution of Policies

High Growth of RPA Bots to Quickly Address Service Requests and Provide Customer Support

Emerging trend of Hyperautomation to Accelerate Digital Transformation Across the Insurance Sector During and Post Pandemic

Market Trend:

Shifting Towards the Cloud Deployment of RPA Software

The Integration of OCR and Natural Language Processing Technologies to Offer Enhanced Customer Service

What can be explored with the Robotic Process Automation in Insurance Market Study?

Gain Market Understanding

Identify Growth Opportunities

Analyze and Measure the Global Robotic Process Automation in Insurance Market by Identifying Investment across various Industry Verticals

Understand the Trends that will drive Future Changes in Robotic Process Automation in Insurance

Understand the Competitive Scenarios

Track Right Markets

Identify the Right Verticals

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

Have Any Questions Regarding Global Robotic Process Automation in Insurance Market Report, Ask Our Experts@ https://www.advancemarketanalytics.com/enquiry-before-buy/199028-global-robotic-process-automation-in-insurance-market#utm_source=DigitalJournalVinay

Strategic Points Covered in Table of Content of Global Robotic Process Automation in Insurance Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Robotic Process Automation in Insurance market

Chapter 2: Exclusive Summary the basic information of the Robotic Process Automation in Insurance Market.

Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Robotic Process Automation in Insurance

Chapter 4: Presenting the Robotic Process Automation in Insurance Market Factor Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region/Country 2016-2021

Chapter 6: Evaluating the leading manufacturers of the Robotic Process Automation in Insurance market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2022-2027)

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source

Finally, Robotic Process Automation in Insurance Market is a valuable source of guidance for individuals and companies.

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[industrynewsupdates]

A Strategic Approach to Material Handling Equipments Procurement Intelligence

The global material handling equipments category is anticipated to grow at a CAGR of 5.85% from 2023 to 2030. Key factors driving the growth of the category include innovations in technology and the incorporation of Industry 4.0 into logistics infrastructure and warehouse management systems, growing need for expedited delivery, improved warehouse operations, and effective order fulfilment. In addition, the category is also being fuelled by rising e-commerce combined with shifting customer preferences is advancing last-mile delivery robot capabilities, and growing industrialization and the need for automation in material handling machinery. However, costly initial outlay for the purchase and upkeep of the product offered in the category places limitations on companies, especially small and medium-sized ones (SMEs). This may hinder the growth of the category during the forecasted timeframe.

Robotics & automation, internet of things (IoT) & data analytics, smart & connected systems, artificial intelligence (AI), digitization, and sensors & communication. Robotics & automation can improve speed, precision, flexibility, and quality while lowering labor expenses, human error, injuries, and downtime. For instance, automated guided vehicles (AGVs) integrated with navigations systems, cameras and sensorscan move goods and materials across the plant on their own. In addition, utilization of IoT & data analytics enables businesses in real-time optimizing, controlling and monitoring of technology and equipments. For instance, a business can use barcode scanners, GPS, and RFID tags to monitor the condition, status and location of its products and materials. Furthermore, a business can optimize and align the material handling process with its overall plant operations and company goals by utilizing smart & connected solutions.

The category for material handling equipments exhibits a moderately consolidated landscape, with majority of the share in the market being held by few of the global players who seek to maintain competition by implementing both organic and inorganic strategies as part of their core growth plan. The players are utilizing strategic activities like mergers, acquisitions, and new product launches to increase their competitive share and improve material handling operations through the quick adoption of cutting-edge technologies. For the purpose of making a significant market penetration, they regularly supply a range of specialist devices to their end users across nations. In addition, they are investing heaving in research & development to enhance their product lines. Despite intense competition, buyers in the category possess low negotiation capability as the market is ruled by few of the large players who leave less scope for switching to other options or let small regional players survive for long.

Order your copy of the Material Handling Equipments Procurement Intelligence Report, 2023 – 2030, published by Grand View Research, to get more details regarding day one, quick wins, portfolio analysis, key negotiation strategies of key suppliers, and low-cost/best-cost sourcing analysis

Cost of equipment, financing, insurance, fuel expenses, and repairs & maintenance constitute the total cost of ownership for the products offered in the category. The factors that drive the prices of the equipments include demand & supply, manufacturer, model & safety features, and resale value.Prices of equipment are impacted by the laws of supply and demand. Prices decrease as a result of increased competition among firms for machinery. Purchasers benefit if a certain equipment is oversupplied in the market. In addition,there are many equipment manufacturers, but only a handful control the market. The annual sales of new and second-hand equipment around the world reflect the fact that many businesses only purchase one or two specific brands of machinery. In the U.S., the price of high-rise crawler excavator ranges between USD 99,500 to USD 124,500. The price of diesel forklift ranges between USD 5,900 to USD 9,500.

Asia-Pacific region dominates the global material handling equipments category, holding substantial share of revenue. Growth of the region is attributed to the continuous rise of food retail sector which aims to boost the speed and effectiveness of picking & sorting processes, hence, requiring the need for the products offered in the category. In addition, strong economic growth in China, India, and several ASEAN nations is responsible for the expansion of the Asian market, which in turn has contributed to the overall growth of the region. Selecting an equipment that doesn’t incurs high cost of maintenance, thoroughly observing the space where the equipment will be deployed in order to get the relevant machinery (i.e. not too big, nor too small), selecting a supplier that is reliable and offers the equipments which are safe and doesn’t compromise on the quality, and comparing multiple suppliers to get the best deal are some of the best sourcing practices considered in this category.

Material Handling Equipments Procurement Intelligence Report Scope

• Material Handling Equipments Category Growth Rate: CAGR of 5.85% from 2023 to 2030

• Pricing Growth Outlook: 4% - 8% increase (Annually)

• Pricing Models: Cost-plus pricing, Competition-based pricing

• Supplier Selection Scope: Cost and pricing, Past engagements, Productivity, Geographical presence

• Supplier Selection Criteria: Industries served, years in service, geographical service provision, types of equipments, power output, propulsion type, on-site assistance, regulatory compliance, and others.

• Report Coverage: Revenue forecast, supplier ranking, supplier matrix, emerging technology, pricing models, cost structure, competitive landscape, growth factors, trends, engagement, and operating model

Browse through Grand View Research’s collection of procurement intelligence studies:

• Drilling Equipment & Consumables Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

• Heavy Mining Equipment Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

Key Companies Profiled

• BEUMER Group GmbH & Co. KG

• Crown Equipment Corporation

• Daifuku Co., Ltd.

• Fritz SCHÄFER GmbH & Co KG

• Hyster-Yale Materials Handling, Inc.

• Jungheinrich AG

• Kardex Holding AG

• KION Group AG

• KUKA AG

• Liebherr-International Deutschland GmbH

• Mitsubishi Heavy Industries, Ltd.

• Toyota Industries Corporation

Brief about Pipeline by Grand View Research:

A smart and effective supply chain is essential for growth in any organization. Pipeline division at Grand View Research provides detailed insights on every aspect of supply chain, which helps in efficient procurement decisions.

Our services include (not limited to):

• Market Intelligence involving – market size and forecast, growth factors, and driving trends

• Price and Cost Intelligence – pricing models adopted for the category, total cost of ownerships

• Supplier Intelligence – rich insight on supplier landscape, and identifies suppliers who are dominating, emerging, lounging, and specializing

• Sourcing / Procurement Intelligence – best practices followed in the industry, identifying standard KPIs and SLAs, peer analysis, negotiation strategies to be utilized with the suppliers, and best suited countries for sourcing to minimize supply chain disruptions

[datahorizzon-research1]

Medical Billing Outsourcing Market size was valued at USD 14.1 Billion in 2023 and to grow at a CAGR of 12.3%

The medical billing outsourcing market size was valued at USD 14.1 Billion in 2023 and is expected to reach a market size of USD 40.1 Billion by 2032 at a CAGR of 12.3%.

The medical billing outsourcing market has experienced significant growth over the past few years due to the increasing complexities in healthcare billing processes, rising demand for efficient revenue cycle management, and the need for cost reduction by healthcare providers. Outsourcing medical billing services enables healthcare providers to focus on core activities such as patient care while ensuring timely and accurate processing of claims, reducing errors, and improving revenue capture.

Recent developments in the medical billing outsourcing market include:

Technological Advancements: The adoption of advanced technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) has transformed the medical billing outsourcing landscape.

Focus on Compliance and Security: With the increasing emphasis on data security and privacy regulations such as HIPAA (Health Insurance Portability and Accountability Act), medical billing outsourcing companies are investing heavily in compliance measures and cybersecurity protocols to ensure the protection of sensitive patient information.

Shift Towards Value-Based Care: The transition from fee-for-service to value-based care models has prompted medical billing outsourcing companies to adapt their services accordingly.

Expansion of Service Offerings: Medical billing outsourcing vendors are expanding their service portfolios to offer end-to-end revenue cycle management solutions, including patient eligibility verification, coding, claims processing, denial management, and accounts receivable management.

Global Market Growth: The medical billing outsourcing market is witnessing significant growth globally, with emerging markets such as Asia-Pacific and Latin America becoming increasingly attractive destinations for outsourcing due to lower operational costs and a large pool of skilled workforce.

Top Companies are:

· Allscripts Healthcare Solutions

· Cerner Corporation

· eClinicalWorks

· Experian Information Solutions Inc.

· GE Healthcare

· Genpact

· Kareo Inc.

· McKesson Corporation

· Quest Diagnostics Incorporated

· The SSI Group LLC

Market Segmentations:

By Component (2024–2032)-

In-house

Outsourced

By Service (2024–2032)-

Front-end Services

Middle-end Services

Back-end Services

By End-use (2024–2032)-

Hospital

Physician Office

Others

Regional Analysis:

North America holds a dominating share of the medical billing outsourcing market, with the United States holding a substantial share of this region. The country dominates this market due to the high adoption of medical billing outsourcing services by healthcare providers in the region to streamline their revenue cycle management processes. Also, it enables them to reduce the high labor cost and the efforts to search and hire trained professionals in this sector and instead focus on their core operations.

Key highlights of the report include:

1. The report delivers thorough Market analysis, furnishing valuable insights to guide strategic decision-making.

2. The comprehensive research outlined in the study enhances the depth of your presentations and marketing strategies.

3. By offering crucial insights into key market competitors, the study empowers businesses with a strategic edge.

4. It delivers a precise assessment of evolving market dynamics, ensuring readers stay abreast of the latest industry trends.

5. With meticulous breakdowns of various market niches, the report facilitates informed decision-making processes.

[johnmaxblogs]

What are the top RPA service providers in the USA?

In the USA, there are several renowned companies providing Robotic Process Automation (RPA) services. Below are some of the noteworthy ones:

UiPath: UiPath is an awesome RPA software company that provides a complete RPA platform. They offer a variety of services, including RPA consulting, implementation, training, and support.

Automation Anywhere: Automation Anywhere is a top-tier RPA vendor that offers a reliable RPA platform. Their services include RPA implementation, process analysis, business planning and training. Automation Anywhere has a vast customer base in the United States and provides solutions for businesses.

Blue Prism: Blue Prism is a widely used RPA software that offers enterprise-level automation services such as RPA implementation, process optimization, and support. The software has a strong presence in the United States and caters to organizations of all sizes, including large enterprises.

Pega Systems: Pega Systems offers an integrated platform that combines RPA and intelligent automation capabilities. They offer services such as RPA consulting, implementation and support. Pega Systems has a strong presence in the United States, particularly in banking, healthcare and insurance.

Microsoft Power Automate : By partnering with Microsoft for the Microsoft Power Automate Consulting Service, businesses can unlock the full potential of automation and drive operational efficiencies. With a streamlined workflow and reduced manual effort, organizations can focus on implementing processes and deliver exceptional results. Your expertise and commitment to customer success makes them an ideal partner for businesses looking to harness the power of Microsoft Power Automate.

NICE Systems (NICE): NICE offers comprehensive RPA solutions that combine attended and unattended automation. They provide services such as RPA consulting, implementation and management. NICE has a strong presence in the US. and meets the needs of organizations across sectors.

It's important to note that the RPA landscape is dynamic and constantly evolving. While the companies mentioned above are well-established and highly regarded, there are also emerging players and niche providers in the RPA market. It's advisable to conduct thorough research, evaluate your specific requirements, and engage in discussions with multiple service providers to determine the best fit for your organization's RPA needs.

[imarcmarketreport]

Fintech Market Size, Trends, Growth, Analysis Report 2024-2032

IMARC Group, a leading market research company, has recently releases report titled “Fintech Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2024-2032” The global fintech market size reached US$ 187.1 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 764.4 Billion by 2032, exhibiting a growth rate (CAGR) of 17% during 2024-2032.

Request For Sample Copy of Report: https://www.imarcgroup.com/fintech-market/requestsample

Factors Affecting the Growth of the Fintech Industry:

Increasing Consumer Demand:

People are increasingly looking for digital and hassle-free financial services. Fintech firms offer user-friendly apps and platforms for activities, such as online payments, budgeting, investing, and peer-to-peer lending, aligning with preferences of people for convenience and accessibility. Fintech companies use advanced data analytics to offer tailored financial services in the country. This personalization resonates with individuals who appreciate solutions that cater to their individual financial goals and circumstances. Fintech solutions often provide cost-effective alternatives to traditional banking services. People are attracted to lower fees, competitive interest rates, and transparent pricing models offered by many fintech providers.

Enhanced Tech Infrastructure:

The enhanced tech infrastructure allows people to have access to high-speed internet. This widespread connectivity ensures that fintech services can reach a broad audience, enabling seamless online interactions between consumers and financial platforms. The proliferation of smartphones and the availability of 4G and 5G networks are creating a mobile-friendly environment. Fintech companies leverage this trend by developing mobile apps and platforms, catering to people who prefer conducting financial transactions on their mobile devices.

Cybersecurity Awareness:

Rising awareness about cybersecurity instills trust and confidence among consumers and businesses when using fintech services. People are more conscious about the importance of data protection, and fintech companies are responding by implementing robust security measures. This includes encryption, secure authentication methods, and data encryption technologies to safeguard sensitive information. Cybersecurity awareness is leading to the introduction of stringent regulations in the fintech sector. Fintech companies are required to comply with cybersecurity standards and regulations, further enhancing the security of financial transactions and data.

Leading Companies Operating in the Global Fintech Industry:

Adyen N.V.

Afterpay Limited (Block Inc.)

Avant LLC

Cisco Systems Inc.

Google Payment Corp.

International Business Machines Corporation

Klarna Bank AB

Microsoft Corporation

Nvidia Corporation

Oracle Corporation

Paypal Holdings, Inc.

Robinhood Markets Inc.

SoFi Technologies Inc

Tata Consultancy Services

Fintech Market Report Segmentation:

By Deployment Mode:

On-premises

Cloud-based

On-premises represented the largest segment as some financial institutions and businesses prefer to maintain control over their data and infrastructure, especially for sensitive financial transactions.

By Technology:

Application Programming Interface

Artificial Intelligence

Blockchain

Robotic Process Automation

Data Analytics

Others

On the basis of technology, the market has been segmented into application programming interface, artificial intelligence, blockchain, robotic process automation, data analytics, and others.

By Application:

Payment and Fund Transfer

Loans

Insurance and Personal Finance

Wealth Management

Others

Payments and fund transfer exhibit a clear dominance in the market on account of the growing consumer demand for convenient and efficient payment solutions.

By End User:

Banking

Insurance

Securities

Others

Banking holds the largest market share as traditional banks increasingly collaborate with fintech companies to offer digital services.

Regional Insights:

North America (United States, Canada)

Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)

Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)

Latin America (Brazil, Mexico, Others)

Middle East and Africa

North America enjoys the leading position in the fintech market due to the growing number of fintech startups and financial institutions.

Global Fintech Market Trends:

Governing agencies of several countries are implementing open banking regulations, which allow people to share their financial data securely with third-party fintech providers. The adoption of digital payment solutions and mobile wallets is rising due to increasing consumer demand for convenient and contactless payment methods. Robo-advisors and wealthtech platforms are gaining traction, offering automated investment advice and portfolio management services. This trend aligns with consumers seeking simplified and cost-effective investment options.

Moreover, interest in cryptocurrencies and blockchain technology is growing, with fintech companies exploring applications beyond traditional finance, such as supply chain management and digital identity verification.

Other Key Points Covered in the Report:

COVID-19 Impact

Porters Five Forces Analysis

Value Chain Analysis

Strategic Recommendations

About Us

IMARC Group is a leading market research company that offers management strategy and market research worldwide. We partner with clients in all sectors and regions to identify their highest-value opportunities, address their most critical challenges, and transform their businesses.

IMARC Group’s information products include major market, scientific, economic and technological developments for business leaders in pharmaceutical, industrial, and high technology organizations. Market forecasts and industry analysis for biotechnology, advanced materials, pharmaceuticals, food and beverage, travel and tourism, nanotechnology and novel processing methods are at the top of the company’s expertise.

Contact US

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[prasannareddy]

Digital Disruption: The Role of Fintech Technologies in Shaping the Future of Finance

Increase in use of smartphones for mobile banking, investing, borrowing services, and cryptocurrency are examples of technologies aiming to make financial services more advance & accessible to the general public. Moreover, Fintech technology companies consist of both startups and established financial institutions trying to replace & enhance usage of financial services provided by existing financial companies. In addition, Fintech technologies include advance technologies such as artificial application programming interface (API), artificial intelligence (AI), blockchain, robotic process automation, and data analytics to enhance financial processes. Payments, fund transfer, personal finance, insurance, and wealth management are some of the major business areas engaged in fintech technologies.

According to the report published by Allied Market Research, the global fintech technologies market size was valued at $110.57 billion in 2020, and is projected to reach $698.48 billion by 2030, growing at a CAGR of 20.3% from 2021 to 2030. The report offers a detailed analysis of changing market trends, top investment pockets, regional landscape, major segments, value chain, and competitive scenario.

Convenience services & maintenance of transparency in terms of financial inclusions and integration of advanced technologies drive the growth of the global fintech technologies market. However, privacy & security concerns with massive shift of consumer data and conflicting regulations across different jurisdictions hinder the market growth. On the other hand, expansion of offerings in developing economies with growth in the middle-class segment, rise in literacy level, rapid urbanization, and increase in tech-savvy youth generation presents new opportunities in the coming years.

Request Sample Report: https://www.alliedmarketresearch.com/request-sample/5024

COVID-19 Scenario:

The demand for fintech technologies increased with surge in usage and adoption of online & digitalized financial products among consumers across the world. In addition, fintech providers have been consolidating their capital and funding for technologies from investors and lenders. Fintech innovations are coming into picture to reduce the cost of services, making financial institutions possible to reach more people and eliminate the need for face-to-face interactions during the pandemic. The report offers detailed segmentation of the global fintech technologies market based on deployment mode, application, technology, end user, and region. Based on deployment mode, the on-premise segment accounted for the highest market share in 2020, contributing to nearly three-fifths of the total share, and is projected to maintain its leadership status during the forecast period. However, the cloud segment is expected to register the highest CAGR of 21.3% from 2021 to 2030.

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Based on end user, the banking sector contributed to the highest market share in 2020, accounting for more than half of the global fintech technologies market, and is projected to continue its lead in terms of revenue during the forecast period. However, the securities segment is estimated to witness the highest CAGR of 23.2% from 2021 to 2030.

Based on region, North America held the largest share in 2020, accounting for more than one-third of the total share, and is estimated to maintain its dominant share in terms of revenue by 2030. However, Asia-Pacific is projected to portray the largest CAGR of 22.1% during the forecast period.

Get Detailed COVID-19 Impact Analysis on the Fintech Technologies Market: https://www.alliedmarketresearch.com/request-for-customization/5024

List of companies profiled of the global fintech technologies market analyzed in the research include Blockstream Corporation Inc., Bankable, Cisco Systems Inc., Circle Internet Financial Limited, IBM Corporation, Microsoft, Goldman Sachs, Oracle, NVIDIA Corporation, and Tata Consultancy Services Limited. These market players have adhered to several strategies including partnership, expansion, collaboration, joint ventures, and others to prove their flair in the industry.

Fintech Technologies Market Key Segments

By Deployment Mode

On-premise Cloud

By Application

Payment & Fund Transfer Loans Insurance & Personal Finance Wealth Management Others

By Technology

Application Programming Interface (API) Artificial Intelligence (AI) Blockchain Robotic Process Automation Data Analytics Others

By End User

Banking Insurance Securities Others

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Housing Finance Market https://www.alliedmarketresearch.com/housing-finance-market-A17178

Business Travel Insurance Market https://www.alliedmarketresearch.com/business-travel-insurance-market

Retail Cash Management Market https://www.alliedmarketresearch.com/retail-cash-management-market-A16646

Crowdfunding Market https://www.alliedmarketresearch.com/crowdfunding-market-A47387

Car Finance Market https://www.alliedmarketresearch.com/car-finance-market

Insurance Analytics Market https://www.alliedmarketresearch.com/insurance-analytics-market-A07602

Mutual Fund Assets Market https://www.alliedmarketresearch.com/mutual-fund-assets-market-A06932

Asia-Pacific Travel Insurance Market https://www.alliedmarketresearch.com/asia-pacific-travel-insurance-market

About Us:

Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Wilmington, Delaware. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports Insights” and “Business Intelligence Solutions.” AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.

We are in professional corporate relations with various companies and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Allied Market Research CEO Pawan Kumar is instrumental in inspiring and encouraging everyone associated with the company to maintain high quality of data and help clients in every way possible to achieve success. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.

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[omkarpatel]

Pharmacy Automation Market is Estimated to Witness High Growth Owing to Opportunity of Improving Patient Safety and Workflow Efficiency

Pharmacy automation systems aid in streamlining dispensing and packaging of medications with minimal human errors and involvement. These systems incorporate various automated medication dispensing cabinets, packaging machines, and robotics to automate medication preparation, packaging, labeling, and dispensing processes. Pharmacy automation improves patient safety by reducing error rates and potential adverse drug events (ADEs). It also enhances pharmacy workflow efficiency by freeing up pharmacists and technicians from repetitive manual tasks. The global Pharmacy Automation Market is estimated to be valued at US$ 3,601.4 Mn in 2023 and is expected to exhibit a CAGR of 8.1% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights. Market Opportunity: Growing need to improve patient safety and workflow efficiency in pharmacies is expected to boost the pharmacy automation market growth over the forecast period. Medication errors continue to be a concerning issue in healthcare systems worldwide. Automating key pharmacy processes can effectively minimize errors and free up staff from repetitive tasks to focus more on direct patient care. This presents lucrative opportunities for pharmacy automation system vendors to provide innovative, integrated solutions matching the evolving needs of pharmacies. Continuous technological advancements are enabling enhanced capabilities of current pharmacy automation solutions. Porter's Analysis Threat of new entrants: The threat of new entrants is moderate due to high initial capital requirements for R&D and automation technologies. However, large corporations can enter this market easily. Bargaining power of buyers: The bargaining power of buyers is high as pharmacy automation systems have several players and buyers can negotiate on price and demand customized solutions. Competitive rivalry: The competitive rivalry is high due to presence of several global players offering differentiated solutions. SWOT Analysis Strength: Automation enhances efficiency, reduces errors and labor costs. It ensures accuracy in dispensing and inventory management. Weakness: High initial investments and maintenance costs of automated solutions. Resistance to change from traditional methods. Key Takeaways The global Pharmacy Automation Market is expected to witness high growth. The global Pharmacy Automation Market is estimated to be valued at US$ 3,601.4 Mn in 2023 and is expected to exhibit a CAGR of 8.1% over the forecast period 2023 to 2030. The market in North America dominated with a share of around 45% in 2023 owing to stringent regulations and presence of key players. However, Asia Pacific is expected to grow at the fastest CAGR of around 9.5% during the forecast period due to growing healthcare expenditure and increasing patients in countries like China and India. Growing penetration of health insurance and expansion of retail pharmacies are driving demand. Furthermore, presence of contract manufacturing hubs and favorable government policies promoting FDI will augment the pharmacy automation market in Asia Pacific. Key players operating in the Pharmacy Automation market are Becton, Dickinson and Company, McKesson Corporation, Yuyama Co., Ltd., Omnicell, Inc., ScriptPro LLC, Cerner Corporation, Capsa Healthcare, Baxter International, Inc., KUKA AG, TCGRx Pharmacy Workflow Solutions, RxSafe, LLC, ARxIUM Inc. Swisslog Holdings AG and Talyst systems LLC. These players are focusing on new product launches and mergers & acquisitions to strengthen their market presence.

[foresight-opinion-trading]

10 Mind-Blowing Ways AI can Make You a Fortune in Money Making

The Role of Artificial Intelligence in Personal Finance

Artificial Intelligence (AI) has emerged as a transformative force in various industries, revolutionizing processes and improving efficiency. One such industry that stands to benefit greatly from AI is personal finance and wealth accumulation. With its advanced algorithms and data analysis capabilities, AI holds significant potential to enhance financial decision-making and streamline wealth management. https://aieventx.com/10-effortless-ways-to-boost-content-creation-with-chat-gpt/ Overview of the Impact of AI in Various Industries Before delving into the potential of AI in personal finance, it is essential to understand its impact in other industries. AI has already made its mark in sectors such as healthcare, manufacturing, and transportation. In healthcare, AI-powered systems are improving diagnostics, predicting disease outbreaks, and personalizing treatment plans. In manufacturing, AI-enabled machines and robots are optimizing processes, reducing errors, and boosting productivity. The transportation sector has witnessed advancements such as self-driving cars and optimized logistics through AI algorithms. The Potential of AI in Personal Finance and Wealth Accumulation The potential impact of AI in personal finance cannot be overstated. Here are some ways in which AI can revolutionize this sector: - Automated Financial Planning: AI-powered systems can analyze personal financial data, including income, expenses, investments, and goals, to create personalized financial plans. These plans can optimize savings, budgeting, and investment strategies, taking into account individual risk tolerance and long-term objectives. - Intelligent Investment Management: AI algorithms can analyze vast amounts of financial data, market trends, and economic indicators in real-time to make informed investment decisions. They can identify potential investment opportunities and manage portfolios efficiently, continually adjusting investment strategies based on changing market conditions. - Detecting Fraud and Security Threats: AI can help detect fraudulent activities and security threats in personal finances. By analyzing transaction patterns, AI systems can identify unusual behavior, alerting individuals to potential risks and preventing financial losses. - Personalized Financial Advice: AI-powered chatbots and virtual assistants can provide personalized financial advice based on individual circumstances. These AI systems can answer questions, provide guidance on saving, budgeting, and investment options, and educate individuals on financial literacy. - Improved Risk Assessment: AI can enhance risk assessment models by leveraging advanced data analysis techniques. This can help individuals make more informed decisions about insurance coverage, retirement planning, and wealth protection. - Efficient Tax Planning: AI algorithms can simplify tax planning by analyzing tax regulations, personal financial data, and deductions to optimize tax strategies and minimize liabilities. In conclusion, AI has the potential to revolutionize personal finance and wealth accumulation. By automating financial planning, providing intelligent investment management, detecting fraud, offering personalized financial advice, improving risk assessment, and streamlining tax planning, AI can empower individuals to make better financial decisions and achieve their long-term goals. As AI continues to advance, its impact on personal finance is likely to be even more profound, creating a more efficient and inclusive financial landscape.

AI-based Investing Strategies for Higher Returns

In the rapidly evolving world of finance, Artificial Intelligence (AI) has emerged as a powerful tool, offering innovative investment strategies for higher returns. By harnessing the capabilities of AI, investors can make data-driven decisions and capitalize on market opportunities. Here are three AI-based investing strategies to consider: - Robo-advisors: Robo-advisors are automated investment platforms that utilize AI algorithms to manage portfolios. These platforms analyze various factors, such as risk tolerance, investment goals, and market trends, to create personalized investment plans. By automating portfolio management, robo-advisors offer cost-effective and efficient solutions for investors, minimizing human bias and emotions. With their ability to rebalance portfolios and provide real-time monitoring, robo-advisors offer a convenient way to achieve higher returns. - Algorithmic trading: Algorithmic trading involves using AI algorithms to execute trades based on predefined rules and market conditions. These algorithms analyze vast amounts of data, such as historical prices, market trends, and indicators, to identify profitable trading opportunities. By leveraging AI's speed and accuracy, algorithmic trading can rapidly respond to market changes and execute trades with precision. This strategy allows investors to capitalize on price inefficiencies, resulting in potentially higher returns. - AI-powered hedge funds: AI-powered hedge funds employ advanced machine learning techniques to make investment decisions. These funds analyze extensive datasets to identify patterns and anomalies in financial markets. By continuously learning and adapting, AI algorithms can uncover profitable investment opportunities that humans might overlook. AI-powered hedge funds can optimize portfolio allocations, actively manage risks, and generate higher returns through data-driven investment strategies. Incorporating AI-based investing strategies can provide investors with a competitive advantage in the market. These strategies leverage AI's ability to process vast amounts of data, identify trends, and make accurate predictions. However, it's essential to conduct thorough research and understand the risks associated with these strategies before implementing them. By combining human expertise with AI technology, investors can strive for higher returns and stay ahead in the ever-changing financial landscape.

Predictive Analytics for Smarter Financial Decisions

Predictive analytics is revolutionizing the financial industry by enabling smarter and more informed decision-making. By analyzing vast amounts of data and applying advanced algorithms, predictive analytics provides valuable insights that can greatly enhance various aspects of financial operations. 1. Credit Scoring and Risk Assessment: Improving Lending Decisions Predictive analytics is transforming the lending landscape by revolutionizing credit scoring and risk assessment processes. Through the analysis of historical data, including borrower information and credit history, predictive models can accurately assess an individual's creditworthiness. This enables financial institutions to make more informed lending decisions, minimizing the risk of default and ensuring appropriate interest rates. 2. Fraud Detection and Prevention: Enhanced Security Measures In an increasingly digital world, financial institutions face the constant threat of fraud. Predictive analytics plays a crucial role in detecting and preventing fraudulent activities. By analyzing patterns and identifying anomalies in financial transactions, predictive models can flag suspicious activities in real-time. This proactive approach enables financial institutions to respond quickly and implement enhanced security measures, protecting both their customers and their assets. 3. Personalized Financial Recommendations: Tailored Advice Based on Individual Goals With the abundance of financial products and services available, individuals often struggle to make optimal financial decisions. Predictive analytics alleviates this challenge by providing personalized recommendations based on individual goals and preferences. By incorporating various factors such as income, expenses, and savings, predictive models can offer tailored advice regarding investment opportunities, retirement planning, and budgeting. This empowers individuals to make smarter financial choices that align with their long-term objectives. In conclusion, predictive analytics is a game-changer in the financial industry. From improving lending decisions through credit scoring and risk assessment to enhancing security measures with advanced fraud detection, and providing personalized financial recommendations, predictive analytics enables financial institutions and individuals alike to make smarter and more informed financial decisions.

AI-Driven Automation for Financial Management

The advancement of Artificial Intelligence (AI) has brought about significant changes in various industries, including financial management. With AI-driven automation, individuals and businesses can streamline their financial processes and make informed decisions. Here are three key areas where AI is revolutionizing financial management: - Expense Tracking and Budgeting: AI-powered tools and apps are simplifying the process of tracking expenses and creating budgets. These tools categorize expenses, analyze spending patterns, and provide personalized insights to help users manage their finances effectively. With real-time tracking and automated data entry, individuals can gain a comprehensive view of their financial health, identify areas for improvement, and make informed budgeting decisions. - Tax Optimization: AI technology is transforming tax planning and filing processes. AI-driven platforms can analyze a vast amount of financial data, identify potential deductions and credits, and optimize tax strategies accordingly. These tools can also automate the tax filing process, reducing errors and saving time for individuals and businesses. With AI-powered tax optimization, individuals can maximize their tax savings and ensure compliance with changing tax laws. - Cash Flow Management: Managing cash flow is essential for both individuals and businesses. AI-driven cash flow management tools leverage historical financial data, market trends, and predictive analytics to forecast future cash flows. These tools can also optimize cash allocation, suggesting the best allocation strategies and highlighting potential risks. By providing accurate cash flow forecasts and intelligent recommendations, AI-driven tools enable individuals and businesses to make proactive financial decisions, identify cash flow gaps, and optimize cash utilization. In conclusion, AI-driven automation is revolutionizing financial management by offering innovative solutions in expense tracking and budgeting, tax optimization, and cash flow management. These AI-powered tools empower individuals and businesses to make better-informed financial decisions, save time, reduce errors, and optimize their financial well-being.

AI-Powered Customer Service in Banking and Fintech

The advent of Artificial Intelligence (AI) has revolutionized customer service in the banking and fintech industries. AI-powered solutions are now being widely employed to provide enhanced customer support, streamline fraud detection and prevention, and accelerate loan application processes. - Chatbots and Virtual Assistants: Chatbots and virtual assistants have become integral components of customer service in the banking and fintech sectors. These AI-powered tools offer round-the-clock personalized support to customers, answering queries, providing account information, and assisting with transactions. By leveraging Natural Language Processing (NLP) capabilities, chatbots and virtual assistants can understand and respond to customer inquiries in real-time, greatly improving customer satisfaction and reducing response times. - Fraud Detection and Prevention: AI algorithms are employed to continuously monitor and analyze vast amounts of data in real-time, identifying suspicious patterns and potential fraudulent activities. Advanced AI models can detect anomalies and raise alerts, enabling rapid intervention and prevention of financial fraud. By automating fraud detection processes, banks and fintech companies can significantly enhance security and protect customer assets. - Credit Scoring and Underwriting: Traditionally, the loan application process involved manual assessment of creditworthiness and extensive paperwork. AI-powered credit scoring and underwriting systems have revolutionized this process by utilizing machine learning algorithms to analyze multiple data points and generate accurate credit scores. This enables faster loan application processing and decision-making. AI models can assess factors such as credit history, income, and financial behavior to make more objective underwriting decisions, reducing human bias and improving efficiency. In summary, AI-powered customer service solutions in banking and fintech industries have facilitated 24/7 personalized support, real-time fraud detection and prevention, and accelerated loan application processes. By leveraging AI technology, organizations can enhance customer experience, improve security, and increase operational efficiency.

AI in Real Estate Investment and Property Management

Artificial Intelligence (AI) is revolutionizing the real estate industry by enhancing investment decision-making and streamlining property management processes. 1. Property Price Prediction: Identifying Investment Opportunities AI-powered algorithms analyze various factors such as historical data, market trends, and economic indicators to predict property prices accurately. By leveraging these predictions, investors can identify lucrative investment opportunities and make informed decisions. 2. Asset and Tenant Management: Streamlining Day-to-Day Operations AI-based property management systems automate and optimize day-to-day operations, simplifying tasks such as tenant screening, lease management, and maintenance requests. These systems can efficiently handle multiple properties, reducing administrative burdens and ensuring smooth operations. 3. Automated Valuation Models: Efficient Property Appraisals and Assessments AI-driven automated valuation models (AVMs) provide quick and accurate property appraisals and assessments. By analyzing vast amounts of data, including property characteristics, market conditions, and sales history, AVMs can generate reliable property valuations. This streamlines the appraisal process, saves time, and improves efficiency. In summary, AI's integration in real estate investment and property management brings numerous benefits. It enables investors to make data-driven decisions, optimizes day-to-day property management operations, and enhances the efficiency of property appraisals and assessments. As AI continues to advance, the real estate industry stands to benefit from increased accuracy, cost savings, and improved decision-making capabilities.

AI for Enhanced Trading and Market Analysis

In today's fast-paced financial markets, utilizing artificial intelligence (AI) can provide traders and investors with a competitive edge. AI's ability to analyze vast amounts of data and make rapid decisions has revolutionized trading and market analysis. Here are three key ways AI is enhancing trading and market analysis: - Sentiment Analysis: AI algorithms can assess market sentiment by analyzing social media trends, news articles, and other sources of information. By understanding the emotions and opinions of market participants, traders can predict trends and make informed investment decisions. Sentiment analysis helps traders identify market sentiment shifts and take advantage of investment opportunities. - High-Frequency Trading: AI-powered high-frequency trading (HFT) algorithms enable automated transactions at incredibly high speeds. These algorithms analyze market data and execute trades in fractions of a second. HFT allows traders to take advantage of small price discrepancies and capitalize on short-term market fluctuations. With AI's ability to process large volumes of data and make split-second decisions, HFT has become a dominant force in the financial markets. - Market Research and Data Analysis: AI's data analysis capabilities are invaluable for traders and investors looking to identify profitable opportunities. AI algorithms can swiftly analyze historical market data, identify patterns, and uncover hidden correlations that human traders might overlook. By combining market research with AI-powered data analysis, traders can make informed decisions and increase their chances of success. In summary, AI is transforming the world of trading and market analysis. Through sentiment analysis, high-frequency trading, and data analysis, AI-powered systems are providing traders with valuable insights, helping them navigate complex financial markets with greater efficiency and accuracy.

AI-Assisted Personalized Wealth Management

In the ever-evolving world of finance and wealth management, Artificial Intelligence (AI) has emerged as a powerful tool. It offers personalized strategies and optimized solutions for individuals seeking to enhance their financial well-being. The implementation of AI in wealth management enables the following: 1. Goal-based Financial Planning AI-powered recommendation engines play a crucial role in goal-based financial planning. These engines analyze individual financial data and generate personalized strategies to achieve specific financial goals. By considering factors such as income, expenses, risk tolerance, and time horizons, AI algorithms can provide tailored recommendations for investments, savings plans, and debt reduction strategies. This approach empowers individuals to make informed decisions and pursue their financial aspirations with confidence. 2. Portfolio Optimization Optimizing investment portfolios is a fundamental aspect of wealth management. AI models help individuals maximize returns while considering their risk tolerance and preferences. By analyzing historical data, market trends, and other relevant factors, AI algorithms can generate optimized portfolios that align with an individual's asset allocation goals. These portfolios are designed to balance risk and reward, ensuring that investments are in line with the individual's risk appetite and long-term wealth-building objectives. 3. Retirement Planning Planning for retirement is a critical financial milestone, and AI models contribute significantly to long-term financial planning and savings. AI algorithms analyze various variables, such as income, expenses, life expectancy, and desired retirement lifestyle, to assist individuals in creating robust retirement plans. These AI models generate personalized insights on savings targets, investment strategies, and asset allocation to ensure a financially secure retirement. By leveraging AI technology, individuals can optimize their retirement plans and make confident decisions regarding their future financial well-being. In conclusion, AI-assisted personalized wealth management empowers individuals with goal-based financial planning, optimal portfolio allocation, and comprehensive retirement strategies. Read the full article

[datadiscoveriesdaily]

Robotic Process Automation in BFSI Market Key Players, Industry Overview, Application and Analysis to 2024 to 2031

Robotic Process Automation in BFSI Market: Navigating the Future of Financial Operations

The Robotic Process Automation in BFSI Market was valued at 710.63 Billion in 2022 and expected to grow at CAGR of 40.1% over forecast period. In the dynamic landscape of the Banking, Financial Services, and Insurance (BFSI) sector, the integration of Robotic Process Automation (RPA) has emerged as a transformative force, reshaping traditional workflows and operational paradigms. RPA, a technology that utilizes robots or 'bots' to automate repetitive tasks, is gaining widespread adoption in the BFSI sector due to its potential to enhance efficiency, reduce operational costs, and mitigate risks.

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Overview:

The BFSI sector, being data-intensive and compliance-driven, has recognized the significance of RPA in optimizing processes. RPA in BFSI involves the deployment of software robots to perform rule-based tasks, such as data extraction, validation, and reconciliation, across various functions like customer onboarding, account management, fraud detection, and regulatory compliance. This automation not only accelerates routine tasks but also ensures accuracy, enabling financial institutions to redirect human resources to more strategic and value-added activities.

Drivers:

Several factors fuel the rapid adoption of RPA in the BFSI sector. One of the primary drivers is the quest for operational efficiency. RPA streamlines mundane tasks, allowing financial institutions to handle vast volumes of data swiftly and accurately. Cost reduction is another compelling driver as RPA diminishes the need for manual intervention, leading to significant savings in labor costs. Additionally, regulatory compliance is a critical aspect of the BFSI sector, and RPA ensures adherence to stringent norms by minimizing errors and ensuring consistency in processes.

Restraints:

Despite the promising prospects, the integration of RPA in BFSI is not without challenges. One notable constraint is the initial investment required for implementation. While the long-term benefits are substantial, some financial institutions may hesitate due to the upfront costs associated with acquiring and implementing RPA solutions. Moreover, concerns regarding data security and privacy may act as a deterrent, especially in an industry where safeguarding sensitive customer information is paramount.

Growth Factors:

The growth of RPA in BFSI is propelled by its adaptability to diverse processes within the sector. As financial institutions increasingly recognize the potential of RPA to enhance customer experience, the technology is witnessing widespread adoption. Moreover, the scalability of RPA solutions ensures that they can be tailored to fit the unique requirements of different organizations, irrespective of their size or complexity. The continuous advancements in RPA technology, including the incorporation of artificial intelligence and machine learning capabilities, further contribute to its sustained growth in BFSI.

Future Outlook:

The future of RPA in BFSI appears promising, with ongoing technological advancements and a growing emphasis on digital transformation. The integration of cognitive capabilities, such as natural language processing and sentiment analysis, will elevate RPA from rule-based automation to a more intelligent and adaptive solution. This evolution is expected to drive innovation in areas like customer service, risk management, and decision-making processes, positioning RPA as a cornerstone of BFSI's digital evolution.

In conclusion, the integration of Robotic Process Automation in the BFSI sector represents a transformative shift in operational dynamics. As financial institutions navigate the challenges of a rapidly evolving landscape, RPA stands out as a key enabler of efficiency, cost-effectiveness, and compliance. While hurdles exist, the numerous drivers and growth factors underscore the inevitability of RPA becoming an integral part of the future of BFSI operations.

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Key Companies Profiled:  NICE; Nintex UK Ltd. (Kryon Systems); Pegasystems Inc.; Protiviti Inc.; UiPath; WorkFusion, Inc., Antworks, Atos SE; Automation Anywhere, Inc.; Blue Prism Limited; EdgeVerve Systems Ltd.; FPT Software; IBM; Kofax Inc.; Microsoft (Softomotive)

Global Robotic Process Automation in BFSI Market, Report Segmentation

Robotic Process Automation in BFSI Market, By Type

Software

Services

Services

Robotic Process Automation in BFSI Market, By Organization

SMEs

Large Enterprises

Robotic Process Automation in BFSI Market, By Application

Banking

Financial Services & Insurance

Global Anti-aging Devices Market, Regional Outlook

North America (U.S., Canada, and Mexico)

Europe (Germany, France, Italy, Spain, U.K., Russia, and Rest of Europe)

Asia Pacific (China, India, Japan, Australia, and Rest of Asia Pacific)

South America (Brazil, Argentina, and Rest of South America)

Middle East & Africa (South Africa, UAE, and Rest of ME&A)

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Artificial Intelligence Market: https://sanglobalresearch.com/report/artificial-intelligence-market/3027

Artificial Intelligence in Construction Market: https://sanglobalresearch.com/report/artificial-intelligence-in-construction-market/3026

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[jayanthitbrc]

Embedded AI Market Growth Trajectory, Key Drivers And Trends

The Business Research Company’s Embedded AI Global Market Report 2023 is the most detailed report available on the market, including broad forecast periods and multiple geographies. The report covers the historic period – 2010-2021, and the forecast period – 2023-2032. The Embedded AI Global Market Report 2023 evaluates embedded AI market size, growth rate, drivers, trends, and major companies.

The report provides a global perspective by covering 60 geographies and focusing on major economies in each region – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

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The global embedded AI market is expected to grow from 11.64 billion in 2022 to 13.04 billion in 2023 at a compound annual growth rate (CAGR) of 12%. The Russia-Ukraine war disrupted the chances of global economic recovery from the COVID-19 pandemic. The war between these two countries has led to economic sanctions on multiple countries, surge in commodity prices, and supply chain disruptions, causing inflation across goods and services and resulted in increased interest rates affecting many markets across the globe. The embedded AI market is expected to reach 20.36 billion in 2027 at a CAGR of 11.8%.

An increase in industrial automation is expected to propel the growth of the embedded AI market going forward. Industrial automation uses advanced technologies, control systems, and machinery to automate industrial processes and operations. Embedded AI is widely used in industrial automation to enhance productivity, efficiency, and decision-making in manufacturing and production processes. It is used for machine vision, quality control, predictive maintenance, and robotics automation. For instance, in February 2022, according to the International Federation of Robotics, a Germany-based non-profit organization, 23,000 industrial robots were operating in UK factories in 2021, an increase of 6% from the previous year. Further, sales of new robots were up by 8% to 2,205 units in 2020. Therefore, the increase in industrial automation is driving the growth of the embedded AI market.

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The embedded AI market segments in the report are:

1) By Offering: Hardware, Software, Services

2) By Data Type: Sensor Data, Image And Video Data, Numeric Data, Categorial Data, Other Data Types

3) By Application: Smart Phone, Wearable Device, Vehicle Electronics, Smart Home, Security Monitoring, Drone, Robot, Other Applications

4) By Vertical: Banking, Financial Services And Insurance (BFSI), Information Technology (IT) And Information Technology Enabled Services (ITES), Retail And Ecommerce, Manufacturing, Healthcare And Life Sciences, Media And Entertainment, Telecom, Automotive, Other Verticals

The table of contents in TBRC’s embedded AI market report includes:

1. Executive Summary

2. Market Characteristics

3. Market Trends And Strategies

4. Impact Of COVID-19

5. Market Size And Growth

6. Segmentation

7. Regional And Country Analysis

.

.

.

27. Competitive Landscape And Company Profiles

28. Key Mergers And Acquisitions

29. Future Outlook and Potential Analysis

Learn About Us:  The Business Research Company is a market intelligence firm that pioneers in market, company, and consumer research. TBRC’s specialist consultants are located globally and are experts in a wide range of industries that include healthcare, manufacturing, financial services, chemicals, and technology. The firm has offices located in the UK, the US, and India, along with a network of proficient researchers in 28 countries.

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[techrobot1235]

7 low code platforms embracing AI

Microsoft’s AI Builder adds AI and machine learning capabilities to Power Apps and Power Automate, while other firms are implementing AI within their low-code and no-code software development and robotic process automation services. AI features are also being added to Amazon SageMaker, DataRobot, Google Cloud AutoML, and Dataiku. 

Here are seven low code products adopting AI:

1. Creatio Atlas

Creatio is incorporating a ChatGPT interface into its Creatio Atlas low-code platform and CRM solutions to improve predictive machine learning models. The connector, which uses the GPS-3.5-turbo model API, charges for use cases such as knowledgebase Q&A, content development, language translation, personal assistants, and email production.

2. Mendix AI-Assisted Development

Mendix Assist (AIAD) is a low-code application development platform featuring two virtual co-developer bots: MxAssist Logic Bot and MxAssist Performance Bot. Smart app capabilities are provided by the platform, which includes an AWS service connection and the Mendix ML Kit. The MxAssist Logic Bot walks users through the process of modelling and setting application logic while offering real-time, context-driven actions. While working in Mendix Studio Pro, the MxAssist Performance Bot inspects the app project model against Mendix development best practices to assist in enhancing app performance.

3. OutSystems AI Mentor System

OutSystems AI Mentor System is a collection of AI-powered solutions meant to aid teams across the software development lifecycle. It contains mentors in code, architecture, security, performance, and reliability who help with coding and handle architectural, security, performance, and maintainability concerns. OutSystems also has an Azure ChatGPT connection in their Forge repository, which enables code completions, conversation completions, and machine learning model embeddings. Azure ChatGPT is recommended for personalized suggestions, virtual assistant power, and summarizing and comparing documents such as insurance policies, legal papers, and financial documents.

4. Pega AI and GenAI

Pega AI and Pega GenAI are part of the Pega low-code platform. Pega AI enables “decisioning” through event monitoring, mining of processes, speech-to-text conversion, and natural language processing. It uses decision techniques, machine learning, and adaptive analytics to help you assess facts and actions, forecast consequences, and make decisions in real-time. Pega GenAI develops procedures, phases, and measures. maps integrations to back-end systems, produces test data on the fly and provides conversational guidance to developers.

5. UiPath AI Center

Machine learning has been integrated into the advanced processes of UiPath, a major RPA software. It now has an AI Centre where you can train, evaluate, deploy, and retrain machine learning models for use with RPA. Importing models and employing pre-trained models for image analysis, language analysis, understanding, translation, and tabular data is supported by the AI Centre.

6. Appian Platform

The Appian Platform provides a low-code design experience for process automation, with Appian 23.2 featuring three AI skills: document classification, document extraction, and email classification. The Document Classification AI Skill provides for document classification and routing, whilst the Email Classification AI Skill allows for bespoke machine learning models that classify emails based on business labels. The Document Extraction AI Skill pulls relevant content from structured documents for convenient application use. Appian 23.3 will integrate Appian AI Copilot, a generative AI conversation interface for form design and process modelling.

7. Airtable AI (beta)

Airtable has enhanced its offering, which was previously released alongside OpenAI’s generative foundation models. The AI can be integrated with roadmap apps, marketing apps, and hiring funnel apps to generate product specifications, creative briefs, and job descriptions for available positions.

Conclusion

As we’ve witnessed, most low-code and no-code development and RPA systems now offer AI capabilities, which are frequently based on a version of GPT. More will undoubtedly follow. Microsoft Power Platform is a market leader in this space, thanks in part to its tight partnership with OpenAI and the current AI and machine learning capabilities on Microsoft Azure.

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[medinyx-tech]

7 Essential Features of Automation in Life Insurance Policy Management

In an era defined by digital transformation, insurance policy management stands at the precipice of a significant revolution. The traditional processes of underwriting, quoting, policy issuance, renewals, claims processing, and more have long relied on manual labor, often leading to inefficiencies, delays, and errors. To enhance efficiency, reduce costs, and ultimately provide superior service, the automation of policy administration processes has become a necessity.

This article explores the seven essential features of life insurance policy management software that not only simplify the tasks at hand but also set the stage for a more agile and customer-centric insurance industry.

Why Should the Typical Insurance Policy Administration Process be Automated?

Policy management is the end-to-end process of handling insurance services. There’s a multitude of tasks that insurers need to handle as part of it, including:

Underwriting

Quoting

Proposal Generation

Policy Issuance, Renewal, & Cancellation

Claims Processing

Loss Run Report Preparation

Compliance Checking

As you can see, policy administration encompasses all the main business processes of an insurance firm. By automating these tasks, your company can differentiate itself, become more cost-efficient, and deliver better service. Isn't that something every company wants?

Features of Life Insurance Policy Management Software

Intelligent life insurance policy management software should simplify your life. It needs to make your work easier and reduce the amount of time you spend on repetitive tasks that drive little value. So, let’s take a look at the components of the most useful policy administration software.

1. Policy Issuance, Updating, and Cancellation

The first must-have of any insurance policy management software is the ability to systemize everything related to policy management. This includes generating necessary documents, maintaining comprehensive records, and managing the entire lifecycle. Modern technology like Robotic Process Automation (RPA) has made this process more efficient, reducing manual work and enhancing data synchronization.

2. Underwriting

Underwriting can be one of the most time-consuming processes for any insurance company. Intelligent automation can speed up the data gathering and analysis process, providing underwriters with the information they need efficiently. Virtualizing underwriting enables data mining from various sources, streamlining risk assessment.

3. Quoting

Efficient quoting capabilities are essential for forward-thinking insurance companies. Modern solutions enable potential clients to receive quote estimates quickly, without the need for in-person or phone interactions. This innovation is a game-changer for insurers.

4. Renewals Handling

Keeping track of renewals and preventing customer churn is vital. Policy management solutions help by notifying policyholders of impending coverage end dates and facilitating smooth renewals.

5. Claims Processing

Claims management is a core process in the insurance sector, and automating its workflow is crucial. Custom software solutions can automate the entire claims settlement process, reducing manual tasks and improving efficiency.

6. Regulatory Intelligence

Insurance companies must adhere to a complex web of regulations. Some insurers may seek solutions that incorporate regulatory intelligence to ensure compliance and prevent financial losses. Modern technologies offer tools to manage regulation-related tasks effectively.

7. Customer Service

Customer service is paramount in the insurance industry. Automation across various areas, combined with customer relationship management (CRM) and marketing automation features, enhances communication with clients and overall service quality. Custom software solutions can be tailored to meet specific customer service needs.

By embracing these essential features of insurance policy management software, insurers can not only streamline their operations but also deliver improved service in an increasingly digital world.

[rdglobalincsblog]

10 Mind-Blowing Ways RPA Services Are Transforming Insurance

The insurance industry is on the brink of a digital revolution powered by Robotic Process Automation (RPA). RPA is reshaping insurance operations by enhancing efficiency and accuracy. McKinsey reports that 25% of insurance processes can be automated in the next two years. In this blog: https://www.rdglobalinc.com/10-mind-blowing-ways-rpa-services-are-transforming-insurance/, we explore how RPA is setting new industry standards and its benefits. 

Streamlining Claims Processing: 

RPA automates data entry, form filling, and verification in claims processing, reducing delays and errors. Bots mimic human actions but work faster and more accurately, allowing staff to focus on higher-value tasks. 

Enhancing Customer Service: 

RPA automates routine tasks like policy quotes and issuance, improving customer service. Bots handle common queries, offer instant responses, and enable personalized experiences, enhancing satisfaction and loyalty. 

Fraud Detection and Prevention: 

RPA analyses data swiftly to detect fraudulent patterns and anomalies. It cross-verifies information, predicts fraudulent behaviour, and leads to faster detection, reduced payouts, and improved trust. 

Policy Administration and Renewal Automation: 

RPA streamlines policy administration and renewals, automating notifications, and ensuring smooth operations. 

Mitigating Compliance Risks: 

RPA automates compliance tasks, ensuring accuracy and reducing time. It provides audit trails for regulatory transparency. 

Efficient Data Management and Analysis: 

RPA excels in data management, collecting, validating, and analysing data for real-time insights and forecasts. 

Boosting Sales and Marketing: 

RPA automates sales and marketing tasks, improving interactions, conversion rates, and customer retention. 

Effective Underwriting: 

RPA automates underwriting tasks, reducing manual work, and ensuring consistent risk assessments. 

Improved Operational Efficiency: 

RPA processes tasks faster and with fewer errors, leading to better services, quicker responses to market changes, and a competitive edge. 

Cost Reduction and ROI Improvement: 

RPA reduces labour costs, errors, and enhances ROI by boosting productivity and efficiency. 

Want to learn how to implement robotic process automation solutions in your business? 

At RD Global, we specialize in providing comprehensive RPA development services and robotic process automation consulting solutions for the insurance industry. Our experienced RPA experts will design, implement, monitor, and maintain automated processes to help you unlock your business’s full potential. 

[datahorizzon-research1]

Medical Billing Outsourcing Market size was valued at USD 14.1 Billion in 2023 and to grow at a CAGR of 12.3%

The medical billing outsourcing market size was valued at USD 14.1 Billion in 2023 and is expected to reach a market size of USD 40.1 Billion by 2032 at a CAGR of 12.3%.

The medical billing outsourcing market has experienced significant growth over the past few years due to the increasing complexities in healthcare billing processes, rising demand for efficient revenue cycle management, and the need for cost reduction by healthcare providers. Outsourcing medical billing services enables healthcare providers to focus on core activities such as patient care while ensuring timely and accurate processing of claims, reducing errors, and improving revenue capture.

Recent developments in the medical billing outsourcing market include:

Technological Advancements: The adoption of advanced technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) has transformed the medical billing outsourcing landscape.

Focus on Compliance and Security: With the increasing emphasis on data security and privacy regulations such as HIPAA (Health Insurance Portability and Accountability Act), medical billing outsourcing companies are investing heavily in compliance measures and cybersecurity protocols to ensure the protection of sensitive patient information.

Shift Towards Value-Based Care: The transition from fee-for-service to value-based care models has prompted medical billing outsourcing companies to adapt their services accordingly.

Expansion of Service Offerings: Medical billing outsourcing vendors are expanding their service portfolios to offer end-to-end revenue cycle management solutions, including patient eligibility verification, coding, claims processing, denial management, and accounts receivable management.

Global Market Growth: The medical billing outsourcing market is witnessing significant growth globally, with emerging markets such as Asia-Pacific and Latin America becoming increasingly attractive destinations for outsourcing due to lower operational costs and a large pool of skilled workforce.

Top Companies are:

· Allscripts Healthcare Solutions

· Cerner Corporation

· eClinicalWorks

· Experian Information Solutions Inc.

· GE Healthcare

· Genpact

· Kareo Inc.

· McKesson Corporation

· Quest Diagnostics Incorporated

· The SSI Group LLC

Market Segmentations:

By Component (2024–2032)-

In-house

Outsourced

By Service (2024–2032)-

Front-end Services

Middle-end Services

Back-end Services

By End-use (2024–2032)-

Hospital

Physician Office

Others

Regional Analysis:

North America holds a dominating share of the medical billing outsourcing market, with the United States holding a substantial share of this region. The country dominates this market due to the high adoption of medical billing outsourcing services by healthcare providers in the region to streamline their revenue cycle management processes. Also, it enables them to reduce the high labor cost and the efforts to search and hire trained professionals in this sector and instead focus on their core operations.

Key highlights of the report include:

1. The report delivers thorough Market analysis, furnishing valuable insights to guide strategic decision-making.

2. The comprehensive research outlined in the study enhances the depth of your presentations and marketing strategies.

3. By offering crucial insights into key market competitors, the study empowers businesses with a strategic edge.

4. It delivers a precise assessment of evolving market dynamics, ensuring readers stay abreast of the latest industry trends.

5. With meticulous breakdowns of various market niches, the report facilitates informed decision-making processes.

[rithvik-scryai]

How AI is Transforming the Fintech Industry

Overview

Financial technology ("FinTech") refers to businesses that aim at providing financial services by making use of software and modern technology. With revolutionary shifts in Internet and mobile technology in recent years, the FinTech industry has witnessed explosive growth by being a pioneer in embracing advanced technologies. Artificial intelligence (AI) has become a promising technology for enterprises from various sectors of the economy. The market for AI in FinTech is estimated at USD 42.83 billion in 2023. According to the Mordor Intelligence report, it is expected to reach USD 49.43 billion by 2028, growing at a CAGR of 2.91% during the forecast period 2023-2028 [1]. Forrester estimates that about half of the world's banks and insurance agencies use intelligent algorithms in their transactions, and the demand for FinTech development services continues growing [2].

Data Digitization Accelerating Fintech

FinTech companies benefit from AI. FinTech players use technology to streamline standard business processes as digitization becomes inevitable. They are doing away with manual work, and technology is rapidly taking over, making business processes more efficient. Technology helps to work with data, which is a rich competitive resource. Businesses use only 0.5 percent of 44 zettabytes of data generated annually [3]. The financial industry has a lot of information: browser specifications, transaction history, images, confidential information, etc. According to research by Mordor Intelligence, process automation was one of the most significant drivers of AI in financial organizations. It rapidly evolves to cognitive process automation, whereby AI systems can perform complex automation processes [4].

Automated Financial Analysis For Increased Throughput

Employing robotic process automation (RPA) for high-frequency repetitive tasks eliminates the room for human error. It allows a financial institution to refocus workforce efforts on processes that require human involvement. It reduces the burden on finance professionals, particularly around the cornerstones of traditional activities, such as transaction processing, audit, and compliance. Amidst the COVID-19 pandemic, FinTech built contactless methods and AI-assisted businesses to automate financial analysis. Artificial intelligence-enabled software verifies data, generates reports according to the parameters, reviews documents, and extracts information from forms. It emphasizes financial analytics and forecasting, strategic risk and resilience, compliance and control, and better data-driven financial management. Ernst & Young has reported a 50 percent to 70 percent cost reduction for these tasks [5]. Forward-thinking industry leaders look to RPA to cut operational costs, enhance user experience and boost productivity.

Human-Like Chatbots For Advanced Customers Engagement

Personalization is becoming increasingly crucial in FinTech to deliver a banking experience that provides an accurate answer in natural language to the customer. AI-powered chatbots help minimize the workload placed on call centers as they tackle the most typical and frequent user problems. The chatbot market is predicted to amount to 454.8 million dollars in revenue by 2027, according to a Statista report [6]. Each chatbot uses a complex sentiment analysis that focuses on understanding the customer’s experience with their service/application, identifying ways it falls short, and training the chatbot to address those shortfalls. Communication between customers and FinTechs is becoming easier and more accessible with AI-based systems. Providing 24×7 banking services is the best way to show availability for bank service providers. With machine learning, AI enhances customer engagement with the ability to respond instantly, resulting in more customer acquisition.

Enhanced Decision Making With Data-Driven Insights

A decision is always informed if it is data-driven. Customers can utilize FinTech apps that have data visualization tools. These tools can break down complex data into a simple form that everyone can understand and digest insights. It improves their financial decision-making. At the corporate level, data-driven decisions have substantially transformed how different issues are handled. Instead of recommendations from human experts, managers are basing their decisions on machine-generated information. For instance, the COVID-19 pandemic has strongly affected FinTech and its consumers, who have shifted now to employing mobile apps more actively. So it has become a golden chance for enterprises to get significant insights into customers and their user experience. That data can be used to fortify their market reputation consequently. AI and data visualization tools can analyze data and provide the most viable and practical recommendations.

Predictive Analytics Reducing Errors

The success of many FinTech companies depends on how well they can analyze current business trends and predict the trends of tomorrow. According to a recent study by the Entrepreneur, AI offers predictive analytics, which is a significant game-changer since it enhances business operations and improves internal processes, giving financial organizations a competitive advantage. It also helps stock traders make decisions by predicting fluctuations in the market. Good analytics in FinTech affects sales growth, business development, and competitiveness. It may depend on predictions of whether a loan will be issued to a reliable person or an insolvent one, what financial products will be helpful to customers in the future, and so on. Studying a vast amount of data is necessary to find a pattern in processes and draw reasonable conclusions, as is learning how to store and protect it. Artificial intelligence examines stored customer data, "tells" managers how to use the information profitably and can reveal complex and unexpected variables.

Secure Your Organisation With Fraud Detection & Enhanced Security

Fraud is one of the most pressing problems the finance industry faces nowadays. According to Javelin, users and businesses experienced a 56 billion dollar loss in 2020 due to fraud [7]. It hampers the companies' reputation, customer experience, and financial loss. Hence, banks, enterprises, and financial institutions employ AI to react to suspicious activity before the fraud happens by blocking a user's request or accessing their account if the system detects potentially fraudulent activity. Over the years, artificial intelligence has significantly boosted data security in the FinTech sector. AI offers a variety of solutions via chatbots designed to enhance security precautions, such as resetting forgotten passwords and granting additional access. Another way AI improves security in finance is through speech, facial, and fingerprint recognition. This added layer of security makes it more difficult for trespassers to bypass than traditional passwords. While these types of processes are still being perfected, AI-backed security solutions may completely replace usernames and passwords in the near future. 

Automate Reconciliation, Underwriting & Claim Management

AI is beneficial in corporate finance as it can better predict and assess loan risks. For companies looking to increase their value, AI technologies such as machine learning can help improve loan underwriting and reduce financial risk. AI technology can increase efficiency and automate workflows by accelerating underwriting processes, delegating tasks for human attention, offering better data-informed banking policies faster, and improving customer experiences. With AI, underwriters can accurately pinpoint optimal rates based on the individual customer for optimal risk management. AI-based pricing models also help reduce the time it takes to introduce new pricing frameworks across the underwriting lifecycle.

Summary

Fintech is one of the rising businesses, and its success depends solely on the technologies being deployed by industry experts. As technology advances rapidly, AI use in the FinTech industry will soon be more adapted for enhanced efficiency, improvised precision levels, and high-speed query resolution. AI in FinTech drives innovation, leading to personalized, fast, and secure services with higher customer satisfaction and global reach. Thus, artificial intelligence is digitizing finance like never before. With integrations, digital finance is reaching new heights as they create a better economic environment for banks and their clients.

Author Bio:

Rithvik is an analyst at ScryAI developing AI products. He received his bachelor's in Data Science from the IIT-Madras.

Follow ScryAI on LinkedIn and read more such blogs at our website: https://scryai.com/.

[dan6085]

Here are 20 jobs that are at risk of being taken over by artificial intelligence (AI) in the near future, along with some details about each:

1. Telemarketing: AI-powered chatbots and voice assistants can now handle many customer service tasks, reducing the need for human telemarketers.

2. Data Entry: AI can automate the process of entering data into software systems, reducing the need for human data entry clerks.

3. Bookkeeping: AI-powered accounting software can now handle many bookkeeping tasks, reducing the need for human bookkeepers.

4. Translation: AI-powered translation software can now handle many language translation tasks, reducing the need for human translators.

5. Writing: AI-powered writing assistants can now generate basic news articles and other content, reducing the need for human writers.

6. Retail Sales: AI-powered chatbots and customer service assistants can now handle many retail sales tasks, reducing the need for human sales associates.

7. Customer Service: AI-powered chatbots and voice assistants can now handle many customer service tasks, reducing the need for human customer service representatives.

8. Data Analysis: AI-powered software can now analyze large amounts of data and generate insights, reducing the need for human data analysts.

9. Stock Trading: AI-powered algorithms can now make stock trades based on market trends and other data, reducing the need for human stock traders.

10. Insurance Underwriting: AI-powered software can now analyze data and make risk assessments for insurance underwriting, reducing the need for human underwriters.

11. Legal Research: AI-powered software can now analyze legal documents and provide insights for legal research, reducing the need for human legal researchers.

12. Medical Diagnosis: AI-powered software can now assist medical professionals with diagnosing diseases and conditions, reducing the need for human diagnosticians.

13. Surgery: AI-powered surgical robots can now perform many surgical procedures with greater precision and accuracy than human surgeons.

14. Transportation: Self-driving cars and trucks could eventually reduce or eliminate the need for human drivers in many industries.

15. Manufacturing: AI-powered robots and automated systems can now handle many manufacturing tasks, reducing the need for human factory workers.

16. Construction: AI-powered robots and automated systems can now handle many construction tasks, reducing the need for human construction workers.

17. Accounting: AI-powered accounting software can now handle many accounting tasks, reducing the need for human accountants.

18. HR Recruitment: AI-powered software can now analyze resumes and candidate data to help identify the best candidates for open positions, reducing the need for human recruiters.

19. Marketing: AI-powered marketing software can now analyze customer data and generate targeted marketing campaigns, reducing the need for human marketing professionals.

20. Financial Planning: AI-powered financial planning software can now analyze data and provide investment advice, reducing the need for human financial planners.