QuanTemplate is a company that focuses on data automation in the insurance industry. The company offers services such as data integration, machine learning, and analytics, which help to automate and validate insurance data, turning fragmented information into reliable insights. QuanTemplate primarily serves the insurance and reinsurance sectors. QuanTemplate was formerly known as Bullingdon Research Limited. It was founded in 2012 and is based in New York, New York.
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CB Insights Intelligence Analysts have mentioned QuanTemplate in 1 CB Insights research brief, most recently on Jan 23, 2023.
Expert Collections containing QuanTemplate
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
QuanTemplate is included in 3 Expert Collections, including Regtech.
Technology that addresses regulatory challenges and facilitates the delivery of compliance requirements. Regulatory technology helps companies and regulators address challenges ranging from compliance (e.g. AML/KYC) automation and improved risk management.
Companies and startups that use of technology to improve core and ancillary insurance operations. Companies in this collection are creating new product architectures, improving underwriting models, accelerating claims and creating a better customer experience
Companies and startups in this collection provide technology to streamline, improve, and transform financial services, products, and operations for individuals and businesses.
Latest QuanTemplate News
Aug 3, 2023
Key Players SAP SE, IBM Corporation, Salesforce, Inc., Oracle Corporation, SAS Institute Inc., Microsoft Corporation, Applied Systems, Shift Technology, SimpleFinance, OpenText Corporation, Quantemplate, Slice Insurance Technologies, Pegasystems Inc., Vertafore, Inc., Zego, and Others Report Highlights By offering, the software segment is expected to hold the largest share of the market during the forecast period. By automating fraud detection processes, software can save costs and protect insurers from financial losses due to fraudulent activities. By deployment, the cloud segment is expected to hold the largest share during the forecast period. These services include natural language processing (NLP), image and video analysis, speech recognition, and more. Insurers can integrate these AI services into their applications without the need for extensive AI expertise. By end user, the life and health insurance segment is expected to capture the largest market share over the forecast period. AI technologies, including machine learning algorithms, are used to analyze a wide range of data sources in the life and health insurance sectors. This data may include medical records, lifestyle data, genetic information, and more. AI-driven underwriting models help insurers assess risks more accurately, enabling them to tailor insurance products and set appropriate premiums based on individual health profiles. AI is employed to analyze health data and predict potential health risks. In the health insurance segment, this can help insurers encourage policyholders to take proactive measures to prevent or manage certain health conditions, ultimately reducing claims and healthcare costs. Thereby, driving the segment growth during the analysis period. By application, the fraud detection and credit analysis segment is expected to hold a substantial market share during the forecast period. Fraud detection is a critical aspect of the insurance industry, as fraudulent claims can result in significant financial losses. AI-powered fraud detection systems analyze vast amounts of data, including historical claims data, customer behavior patterns, and external data sources, to identify suspicious activities and potential fraud indicators. Additionally, AI-driven credit risk assessment models analyze an individual's credit history, payment behavior, and financial stability to determine their credit risk. This information helps insurers make informed decisions on financing options and credit terms. Thus, influencing segment growth. By organization size, the large enterprise segment is expected to hold the dominant share of the market during the forecast period. AI systems can provide personalized recommendations, answer customer queries, and assist with policy-related inquiries, leading to improved customer engagement and satisfaction for large-scale organization. Market Dynamics Cost efficiency and automation Insurance companies face significant operational challenges, including manual and time-consuming processes. AI technologies, such as robotic process automation and natural language processing, offer automation of repetitive tasks, leading to increased operational efficiency and cost savings. Automation reduces human errors, accelerates processes like claims handling, underwriting, and policy administration, and allows employees to focus on more complex and strategic tasks. Therefore, the cost efficiency and automation benefits provided by AI are expected to propel the market expansion during the projected period. Restraint Lack of skilled workforce The successful implementation of AI technologies requires a skilled and knowledgeable workforce capable of developing, managing, and interpreting AI models. The demand for AI talent often outpaces the available supply, making it challenging for some insurance companies to find the right expertise to drive their AI initiatives effectively. Thus, the lack of a skilled workforce is expected to hamper the industry growth over the projected period. Opportunity Enhanced customer experience AI-driven chatbots and virtual assistants have transformed customer service in the insurance industry. These intelligent systems can provide real-time support and personalized responses, improving customer engagement and satisfaction. Additionally, AI enables insurers to offer tailor-made insurance products and pricing based on individual customer profiles, leading to a more customer-centric approach. Thus, the enhanced customer experience is expected to offer an attractive opportunity for market growth during the analysis period. Challenge Explainability and transparency issues AI algorithms, particularly those based on deep learning and neural networks, can be complex and challenging to interpret. The lack of transparency and explainability in AI decision-making processes can raise concerns among regulators, customers, and even within the insurance companies themselves. In highly regulated industries like insurance, explainable AI is essential to build trust and comply with regulatory requirements. Thus, this is expected to act as a major challenge for the market growth over the forecast period. Related Reports AI in Healthcare Market - The global AI in healthcare market was valued at USD 15.1 billion in 2022 and it is expanding around USD 187.95 billion by 2030 with a CAGR of 37% from 2022 to 2030. AI in Renewable Energy Market - The global AI in renewable energy market was valued at US$ 8.24 billion in 2021 and it is expanding around US$ 75.82 billion by 2030 with a CAGR of 27.9% from 2021 to 2030. A utomotive AI Market - The global automotive AI market was valued at USD 2.71 billion in 2022 and is expanding around USD 15.23 billion by 2030 with a CAGR of 24.1% from 2022 to 2030. AI in ultrasound imaging market - The global AI in ultrasound imaging market size was valued at USD 881.2 million in 2022 and is expanding around USD 2,001.51 million by 2032 with a CAGR of 8.6% from 2023 to 2032. Recent Development In April 2022, CLARA Analytics introduced CLARA Optics, a software application that combines AI and machine learning to scan, organize, and analyze invoices and medical papers to produce a claim-based medical record and contributes to the commercial insurance industry's usage of artificial intelligence technology. Market Segmentation Customer Profiling and Segmentation Immediate Delivery Available | Buy This Premium Research Report@ https://www.precedenceresearch.com/checkout/3160 You can place an order or ask any questions, please feel free to contact at email@example.com | +1 9197 992 333 About Us Precedence Research is a worldwide market research and consulting organization. We give an unmatched nature of offering to our customers present all around the globe across industry verticals. Precedence Research has expertise in giving deep-dive market insight along with market intelligence to our customers spread crosswise over various undertakings. We are obliged to serve our different client base present over the enterprises of medicinal services, healthcare, innovation, next-gen technologies, semi-conductors, chemicals, automotive, and aerospace & defense, among different ventures present globally. For Latest Update Follow Us:
QuanTemplate Frequently Asked Questions (FAQ)
When was QuanTemplate founded?
QuanTemplate was founded in 2012.
Where is QuanTemplate's headquarters?
QuanTemplate's headquarters is located at 434 W 33rd St, New York.
What is QuanTemplate's latest funding round?
QuanTemplate's latest funding round is Series C.
How much did QuanTemplate raise?
QuanTemplate raised a total of $23.32M.
Who are the investors of QuanTemplate?
Investors of QuanTemplate include Anthemis, Route 66 Ventures, Allianz X, Transamerica Ventures, Insight Catastrophe Group and 3 more.
Who are QuanTemplate's competitors?
Competitors of QuanTemplate include Groundspeed and 2 more.
What products does QuanTemplate offer?
QuanTemplate's products include Bordereaux Management and 4 more.
Who are QuanTemplate's customers?
Customers of QuanTemplate include James Rivers, Axa, Sompo International and Adeptive.
Compare QuanTemplate to Competitors
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Carpe Data is a company that focuses on data science and artificial intelligence in the insurance industry. The company offers services that automate and optimize insurance claims and underwriting workflows, using advanced data science techniques and artificial intelligence to detect fraud, validate claimant information, and evaluate business profiles. The company primarily sells to the insurance industry. It was founded in 2016 and is based in Santa Barbara, California.
goZeal is a team of skilled female experts that combines artificial intelligence (AI) and matching algorithms to find, hire, and manage hiring for clients' unique business needs. The company specializes in business operations, data engineering, data science, and more. It creates accessible and equal-opportunity jobs for professional women. It was founded in 2020 and is based in New York, New York.