ABSTRACT This paper investigates the presence of window dressing in the Brazilian investment fund market, focusing on equity funds. Window dressing is a practice that presents a particular portfolio composition to the market, which is different from that held by the fund in the reporting period. Just before the end of the period, fund managers change their positions with the aim of presenting safer, more profitable securities portfolios. We believe that there is a lack of empirical evidence on this topic in Brazil. Previous research focuses on diversification, style analysis, fund portfolio turnover, manager profile, and performance. Therefore, we believe that our paper is pioneering in presenting results on window dressing in Brazil. With the presence of window dressing, the market may signal distorted results to investors and guide their allocations towards funds in which they would not invest in the absence of such practices. Moreover, the adoption of window dressing may increase transaction costs and thus destroy value. Our results present a connection with previous studies by Bremer and Kato (1996), O’Neal (2001), Ng and Wang (2004), Ortiz, Sarto, and Vicente (2012), and Agarwal, Gay, and Ling (2014). This paper provides evidence of window dressing in Brazilian equity funds and proposes an empirical study to verify the presence of the practice between 2010 and 2016, using market model residuals, rank gap, and backward holding return gap analysis techniques. In short, our results are consistent with window dressing practices in funds managed by small companies that were losers against the Bovespa Index and presented a high tracking error in the period.

Portfolio Stewardship Analytics Market Outlook

According to our latest research, the global portfolio stewardship analytics market size reached USD 2.04 billion in 2024, reflecting the sector's rapid evolution and adoption across financial services. The market is expected to expand at a CAGR of 13.7% from 2025 to 2033, reaching a projected value of USD 6.18 billion by 2033. This robust growth is primarily driven by increasing regulatory scrutiny, the growing need for data-driven investment decisions, and the integration of advanced analytics and artificial intelligence into portfolio management processes.

A significant growth factor fueling the portfolio stewardship analytics market is the escalating complexity of global investment portfolios. With institutional investors, asset managers, and pension funds managing increasingly diversified and international portfolios, there is a heightened need for sophisticated analytics to ensure transparency, compliance, and optimal performance. The proliferation of environmental, social, and governance (ESG) criteria in investment strategies further amplifies the demand for advanced stewardship analytics solutions. These tools empower investors to track ESG compliance, assess risk exposures, and benchmark performance against evolving regulatory standards, thereby facilitating more responsible and informed investment practices. As financial institutions strive to meet stakeholder expectations for accountability and value creation, the adoption of portfolio stewardship analytics becomes indispensable.

Another key driver is the rapid advancement and adoption of artificial intelligence, machine learning, and big data analytics in the financial sector. These technologies enable real-time data processing, predictive modeling, and scenario analysis, which are critical for effective risk management and performance analysis. The integration of these advanced analytics tools into portfolio stewardship platforms allows for more granular insights into asset allocation, risk-adjusted returns, and compliance monitoring. As a result, asset managers and institutional investors can make more agile and informed decisions, optimizing portfolio outcomes while mitigating potential risks. The continuous evolution of these technologies is expected to further enhance the capabilities of stewardship analytics platforms, fostering sustained market growth.

Furthermore, the growing regulatory environment across global financial markets is compelling organizations to invest in robust stewardship analytics solutions. Regulatory bodies are increasingly mandating transparent reporting, risk assessment, and compliance monitoring, especially in light of high-profile financial scandals and the growing importance of ESG disclosures. Portfolio stewardship analytics platforms provide comprehensive solutions for automating compliance processes, generating audit-ready reports, and tracking regulatory changes in real time. This not only reduces operational risk but also helps organizations maintain a competitive edge by proactively adapting to regulatory shifts. The convergence of regulatory requirements and technological advancements is thus creating a fertile ground for the expansion of the portfolio stewardship analytics market.

From a regional perspective, North America continues to dominate the global portfolio stewardship analytics market, accounting for more than 36% of the total market share in 2024. This leadership is attributed to the region's mature financial services sector, early adoption of advanced analytics technologies, and stringent regulatory frameworks. Europe follows closely, driven by its strong focus on ESG integration and regulatory compliance. The Asia Pacific region is emerging as a high-growth market, propelled by increasing institutional investments, digital transformation of financial services, and rising awareness of stewardship responsibilities. Latin America and the Middle East & Africa, while smaller in market size, are witnessing steady growth as financial institutions in these regions embrace analytics-driven portfolio management to enhance transparency and performance.

Component Analysis

The portfolio stewardship analytics market is segmented by component into software and services. The software segment holds the largest share, driven by the increasing demand for integrated analytics platforms that offer comprehensive capabilities for data aggregation, visual

National Investment and Infrastructure Fund Limited Business Operations, Opportunities, Challenges and Risk (SWOT, PESTLE and Porters Five Forces Analysis); Corporate and ESG Strategies; Competitive Intelligence; Financial KPI’s; Operational KPI’s; Recent Trends: “ Read More

ILS Fund Management Market Outlook

According to our latest research, the ILS Fund Management market size reached USD 109.8 billion globally in 2024, reflecting a robust sector that continues to attract capital due to its unique risk-return profile. The market is projected to grow at a CAGR of 8.7% from 2025 to 2033, reaching a forecasted value of USD 233.9 billion by 2033. This impressive growth is primarily driven by the increasing adoption of alternative risk transfer solutions, heightened demand for catastrophe risk coverage, and the entrance of new investor classes seeking diversification beyond traditional asset classes.

The expansion of the ILS Fund Management market is fundamentally underpinned by the intensifying frequency and severity of natural catastrophes globally. As climate change accelerates, insurers and reinsurers are increasingly compelled to seek innovative risk transfer mechanisms, and insurance-linked securities (ILS) have emerged as a preferred solution. The ability of ILS to provide rapid liquidity and capital relief after catastrophic events makes them an attractive tool for both primary insurers and reinsurers. Furthermore, regulatory developments such as Solvency II in Europe and similar frameworks elsewhere have encouraged greater transparency and risk management, further boosting the adoption of ILS structures in fund management portfolios.

Another significant driver for the ILS Fund Management market is the evolving investor appetite for uncorrelated returns. Institutional investors, including pension funds, hedge funds, and sovereign wealth funds, are increasingly allocating capital to ILS funds to achieve portfolio diversification and hedge against traditional market volatility. The relatively low correlation of ILS returns with equity and bond markets has made them particularly appealing during periods of economic uncertainty. This trend has been further accelerated by technological advancements and data analytics, which have enhanced risk modeling and pricing accuracy, thereby increasing investor confidence in ILS structures.

In addition, the proliferation of digital distribution channels and online platforms has revolutionized the accessibility of ILS fund products. Investors now have unprecedented access to a broad range of ILS funds through digital brokers and direct platforms, reducing transaction costs and increasing market transparency. The rise of fintech solutions tailored for ILS fund management is also streamlining the investment process, improving operational efficiency, and fostering greater participation from both institutional and retail investors. Collectively, these factors are driving sustained growth and innovation within the ILS Fund Management market.

Regionally, North America continues to dominate the ILS Fund Management market, accounting for the largest share due to the region's mature insurance and reinsurance sectors, as well as its exposure to high-value catastrophe risks such as hurricanes and wildfires. Europe follows closely, supported by a strong regulatory environment and growing investor sophistication. Meanwhile, Asia Pacific is emerging as a significant growth area, fueled by increasing insurance penetration, economic development, and rising awareness of catastrophe risk transfer solutions. The market dynamics in Latin America and the Middle East & Africa are also evolving, albeit at a slower pace, as these regions gradually embrace alternative risk transfer mechanisms.

Fund Type Analysis

The fund type segment of the ILS Fund Management market is highly diversified, with catastrophe bonds, sidecars, collateralized reinsurance, industry loss warranties, and other structures each playing a crucial role in the ecosystem. Catastrophe bonds remain the most prominent fund type, accounting for a substantial portion of the market due to their standardized structure, transparency, and liquidity. These bonds allow insurers and reinsurers to transfer specific catastrophe risks directly to capital m

Gain insights into the features, exposure levels, performance metrics, attribution, and risk factors of an international fixed income portfolio using Eulerpool's adaptable and top-tier portfolio analysis solution. Discover the traits, exposure, performance, attribution, and risk assessment of a worldwide fixed income portfolio with Eulerpool's versatile, market-leading portfolio analysis tool. Explore the attributes, exposure, performance, attribution, and risk profile of a global fixed income portfolio through Eulerpool's flexible and premier solution for portfolio analysis.

Abstract

Household data was collected from 8 localities across the five Darfur states (Tawilla, Assalaya, Yassin, Sheiria, Nertiti, Undukum, Gereida, Jebel Moon). The profiling exercises in Darfur are aimed at: i. informing PBF programming and Action Plan development in each Darfur state/locality; ii. provide the baseline of the agreed upon PBF outcome/output indicators (for later measurement of impact); and iii. inform broader HDPN programming beyond the Fund. The sample size consisted of 10,914 households with a total of 60,154 individuals.

Geographic coverage

8 localities across the five Darfur states (Tawilla, Assalaya, Yassin, Sheiria, Nertiti, Undukum, Gereida, Jebel Moon)

Analysis unit

Individual and household

Universe

All IDP returnes, IDPs, nomads in damrahs and non-displaced populations across five Darfur states' eight localities.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Approach The sampling followed a stratified multi-stage sampling approach in which villages were the primary sampling unit (PSU) and households were the secondary sampling unit (SSU), while stratification was done by target group. Accordingly, the first sampling stage consisted of selecting a sample of villages with probabilities that were proportional to size; villages with higher numbers of households had a higher probability of being selected for the survey. A random sample of households was then selected based on two approaches: systematic skips or systematic snowballing. This depended on the spatial distribution of the target groups in each village. For example, in all camps and return villages where only IDPs reside, systematic skips were done. In villages with more target groups, systematic snowballing was performed for each target group.

Sampling limitations & specifications - The sampling is designed to produce results representative for each target group in the locality. Analysis at the village level is not possible and therefore no reference to villages or breakdown by villages is done in the report. - The locations targeted for the survey were not selected randomly across the localities and thus do not necessarily provide representative results of all settlement situations in the localities. The targeting of location has been based on a conflict sensitive approach and the programmatic scope of the PBF. However, the area level analysis has looked at locality as a whole and thus ounterbalance the survey scope which focused on the displaced target groups.

Mode of data collection

Face-to-face interview: Mobile

Startups Funding Rounds

A look at startup funding patterns over time

About this dataset

This dataset contains information on startup funding patterns. This data can be used to understand how startups are funded and what types of startups are most likely to receive funding. This data can also be used to understand the trends in startup funding over time.

Columns:SNo,**SNo,Date,**Date,StartupName,**StartupName,IndustryVertical,**IndustryVertical,SubVertical,**SubVertical

How to use the dataset

This dataset can be used to understand how startups are funded and what types of startups are most likely to receive funding. This data can also be used to understand the trends in startup funding over time.

This dataset contains information on startup funding patterns. The data includes the following columns:

SNo: Serial number. (Numeric) Date: Date of funding. (Date) StartupName: Name of the startup. (String) IndustryVertical: Industry vertical of the startup. (String) SubVertical: Sub-vertical of the startup. (String) CityLocation: City of the startup. (String) … … … … … .. Product .. Technology .. Hardware.. Online Accessories.. Data Processing & Management.. eLearning .. Technology.. Cloud Computing, Enterprise Software & SaaS.. Web Hosting and Development .. Open Source Software Development Tools, Services & Platforms.. Electric Vehicle Infrastructure../ big data analytics, IOT etc… . Thus it’s difficult to really profile an ideal investor for a given type of product/ technology/ industry sectorStartups that have raised Series A or later rounds from established venture firms such as Accel Partners, Sequoia Capital, Tiger Global Management etc., tend to have a better chance of success than those that have raisedseed or angel rounds from inexperienced investors.(Statistically speaking, these firms have a better track record in picking winners)

Research Ideas

• Predicting the amount of funding a startup will receive based on factors such as industry vertical, location, and type of investment.
• Understanding which types of startups are most likely to receive funding from venture capitalists.
• Identifying trends in startup funding over time

Columns

File: abc.csv

File: sf.csv | Column name | Description | |:---------------------|:--------------------------------------------| | SNo | Serial number. (Numeric) | | Date | Date of funding. (Date) | | StartupName | Name of the startup. (String) | | IndustryVertical | Industry of the startup. (String) | | SubVertical | Sub-industry of the startup. (String) | | CityLocation | City where the startup is located. (String) | | InvestorsName | Name of the investors. (String) | | InvestmentType | Type of investment. (String) | | AmountInUSD | Amount of investment in USD. (Numeric) | | Remarks | Any additional remarks. (String) |

Discover how investor location impacts startup funding rounds. Data shows 16-22% smaller Series A checks from NY VCs vs CA/MA peers. Key insights for founders.

Success.ai’s Company Funding Data for Pharmaceuticals, Biotech & Life Sciences Leaders Globally provides a comprehensive dataset tailored for businesses and investors looking to connect with decision-makers and innovators in these industries. Covering executives, research directors, and investment leads, this dataset includes verified contact details, funding insights, and firmographic data from 70 million businesses worldwide.

With access to over 700 million verified global profiles, Success.ai ensures your outreach, market research, and investment strategies are powered by accurate, continuously updated, and AI-validated data. Supported by our Best Price Guarantee, this solution is indispensable for navigating the fast-evolving biotech, life sciences, and pharmaceutical sectors.

Why Choose Success.ai’s Company Funding Data?

1. Verified Funding and Contact Data for Precision Engagement

   • Access verified work emails, phone numbers, and LinkedIn profiles of executives, investors, and key decision-makers.
   • AI-driven validation ensures 99% accuracy, improving outreach effectiveness and minimizing wasted effort.

2. Comprehensive Global Coverage of Key Players

   • Includes profiles from global pharmaceutical companies, biotech startups, and life sciences research organizations.
   • Gain insights into funding rounds, investment trends, and research initiatives in North America, Europe, and Asia-Pacific.

3. Continuously Updated Datasets

   • Real-time updates capture changes in leadership, funding milestones, and business expansions.
   • Stay aligned with evolving market conditions and capitalize on emerging opportunities.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Engage with professionals and leaders in pharmaceuticals, biotech, and life sciences worldwide.
• 70M Business Profiles: Access detailed firmographic data, including funding histories, revenue ranges, and geographic footprints.
• Funding Insights: Gain visibility into venture capital rounds, private equity investments, and R&D funding allocations.
• Leadership Contacts: Connect with CEOs, CFOs, and research directors driving innovation and business growth.

Key Features of the Dataset:

1. Comprehensive Funding and Leadership Profiles

   • Identify and connect with executives managing investments, R&D initiatives, and financial strategies.
   • Target professionals responsible for securing funding, managing partnerships, and overseeing product development.

2. Advanced Filters for Precision Targeting

   • Filter companies by funding stage (seed, Series A, IPO), industry focus (pharmaceuticals, biotech, life sciences), or geographic location.
   • Tailor campaigns to align with specific business goals, such as securing partnerships or exploring investment opportunities.

3. Global Trends and Investment Insights

   • Leverage data on funding trends, market opportunities, and breakthrough innovations across key regions.
   • Use these insights to refine investment strategies, identify potential partners, or shape product development.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Investment and Venture Development

   • Identify biotech startups and life sciences companies seeking funding, and build relationships with key stakeholders.
   • Present funding opportunities, venture capital solutions, or strategic investment proposals to decision-makers.

2. Market Research and Competitive Analysis

   • Analyze global funding trends, emerging technologies, and market needs to refine business strategies.
   • Benchmark against competitors to identify growth opportunities and innovative solutions.

3. Sales and Partnership Development

   • Engage with pharmaceutical and biotech companies to offer financial tools, R&D solutions, or investment partnerships.
   • Build long-term relationships with companies exploring product commercialization or market expansion.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers seeking experienced candidates for roles in R&D, finance, or investment management.
   • Provide workforce optimization platforms or recruitment solutions tailored to the biotech and life sciences sectors.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality company funding data at competitive prices, ensuring strong ROI for your marketing, research, and investment initiatives.

2. Seamless Integration

   • Integrate verified funding and contact data into CRM systems, analytics tools, or investment platforms via APIs or downloadable formats, streamlining ...

Mortgage-Backed Securities Market Outlook

According to our latest research, the global mortgage-backed securities (MBS) market size reached USD 11.2 trillion in 2024, driven by robust demand for securitized debt instruments and a thriving real estate sector. The market is projected to expand at a CAGR of 6.1% from 2025 to 2033, with the total market value forecasted to reach USD 19.1 trillion by 2033. This growth trajectory is underpinned by increasing investor appetite for fixed-income assets, ongoing financial innovation, and supportive regulatory frameworks that continue to shape the evolution of the global MBS landscape.

The primary growth factor for the mortgage-backed securities market is the persistent demand for yield in a low-interest-rate environment. Institutional investors, such as pension funds, insurance companies, and mutual funds, are continuously seeking stable, long-term returns to meet their portfolio objectives. MBS offer attractive risk-adjusted yields compared to other fixed-income alternatives, making them a preferred choice for these investors. In addition, the diversification benefits provided by pooling mortgage loans into securities help mitigate individual credit risk, further enhancing their appeal. The market has also witnessed a resurgence in investor confidence, thanks to improved underwriting standards and enhanced transparency following the 2008 financial crisis, which has contributed to sustained growth in the issuance and trading of mortgage-backed securities.

Another significant driver for the MBS market is the increasing sophistication of financial markets and the proliferation of securitization techniques. Financial institutions and government agencies have developed advanced structuring mechanisms, such as tranching and credit enhancement, which allow for the tailoring of MBS products to meet specific investor requirements. This has led to the creation of a wide array of MBS types, including residential MBS (RMBS), commercial MBS (CMBS), and collateralized mortgage obligations (CMOs), catering to diverse risk-return profiles. The integration of technology and data analytics in the origination and servicing of mortgage loans has also streamlined the securitization process, reducing operational costs and improving the accuracy of risk assessment. As a result, issuers can efficiently package and distribute mortgage assets, further fueling market expansion.

Regulatory support and favorable government policies have played a pivotal role in bolstering the MBS market. In major economies such as the United States, government-sponsored enterprises (GSEs) like Fannie Mae, Freddie Mac, and Ginnie Mae have been instrumental in providing liquidity and stability to the housing finance system. These agencies guarantee or directly issue a significant portion of MBS, thereby enhancing investor confidence and lowering funding costs for mortgage originators. Recent regulatory reforms aimed at increasing transparency, standardizing disclosure practices, and strengthening risk retention requirements have further contributed to the resilience and attractiveness of the MBS market. As policymakers continue to prioritize housing affordability and financial market stability, the regulatory landscape is expected to remain supportive of MBS growth in the coming years.

Collateralized Mortgage Obligations (CMOs) have become a significant component of the mortgage-backed securities market, offering unique benefits to both issuers and investors. These structured financial products allow for the creation of multiple tranches with varying risk and return profiles, providing investors with tailored options to meet their specific investment objectives. The flexibility of CMOs in managing interest rate and prepayment risks makes them particularly attractive to institutional investors seeking to optimize their portfolios. As the market continues to evolve, the role of CMOs in providing customized investment solutions is expected to grow, driven by advancements in technology and data analytics that enhance the structuring and risk management processes.

From a regional perspective, North America remains the dominant market for mortgage-backed securities, accounting for the majority of global issuance and trading activity. The well-established securitization infrastructure, deep investor base, and active part

Net Stable Funding Ratio (NSFR) Optimization Market Outlook

According to our latest research, the global Net Stable Funding Ratio (NSFR) Optimization market size reached USD 1.42 billion in 2024 and is projected to grow at a CAGR of 10.3% from 2025 to 2033, reaching USD 3.46 billion by 2033. This robust growth is primarily driven by the increasing demand for advanced liquidity management solutions and stringent regulatory mandates that require financial institutions to maintain stable funding profiles. The market’s expansion is further fueled by the rapid adoption of digital technologies and a growing emphasis on risk management and compliance within the banking and financial services sector.

One of the key growth factors propelling the Net Stable Funding Ratio (NSFR) Optimization market is the evolving regulatory landscape. Global banking regulations, especially those stemming from the Basel III framework, have made NSFR compliance a top priority for banks and financial institutions. The need to maintain a healthy ratio of stable funding over a one-year horizon has compelled organizations to invest in sophisticated software and services that can automate and optimize funding strategies. This demand is particularly evident among Tier 1 banks and large financial conglomerates, which face significant scrutiny from regulators and are under constant pressure to demonstrate robust liquidity profiles. As a result, the adoption of NSFR optimization solutions is becoming increasingly widespread, not only to meet regulatory requirements but also to gain a competitive edge in liquidity management.

Another significant driver of market growth is the rapid digitization of financial services and the integration of advanced analytics and artificial intelligence in risk management. Financial institutions are leveraging cutting-edge NSFR optimization platforms that offer real-time data analytics, scenario modeling, and predictive insights. These capabilities enable banks and investment firms to proactively manage their funding needs, optimize asset-liability mismatches, and reduce the cost of compliance. The shift toward cloud-based deployment models further accelerates this trend, as institutions seek scalable, secure, and cost-effective solutions that can be quickly updated in response to regulatory changes. As the financial sector continues to embrace digital transformation, the demand for comprehensive NSFR optimization tools is set to rise.

Additionally, the growing complexity of financial products and the increasing interconnectedness of global markets are compelling organizations to adopt integrated approaches to liquidity management. NSFR optimization solutions are now being designed to address not only compliance but also broader objectives such as capital efficiency, profitability, and resilience against market shocks. Financial institutions are seeking platforms that can seamlessly integrate with existing risk management, treasury, and reporting systems, thereby providing a holistic view of funding and liquidity risks. This trend is particularly pronounced in regions with active cross-border banking activities, where compliance with multiple regulatory regimes requires a unified, agile, and transparent approach to funding optimization.

From a regional perspective, the market is witnessing strong growth in Asia Pacific and North America, where regulatory reforms and digital innovation are transforming the financial landscape. Europe remains a key market due to the early adoption of Basel III standards and the presence of leading financial institutions. Meanwhile, emerging markets in Latin America and the Middle East & Africa are gradually increasing their investments in NSFR optimization solutions as they modernize their banking sectors and align with global regulatory best practices. The regional outlook for the NSFR optimization market is characterized by both mature markets seeking to enhance efficiency and emerging economies focused on regulatory alignment and risk mitigation.

Solution Type Analysis

The solution type segment of the Net Stable Funding Ratio (NSFR) Optimization market is primarily divided into software and services. Software solutions dominate the market, accounting for a significant portion of the global revenue in 2024. These platforms provide banks and financial institutions with automated tools for calculating, monitoring, and optimizing thei

🌍 Worldwide B2B Company Dataset | 65M+ Verified Records | Firmographics & API Access Power your sales, marketing, and investment strategies with the most comprehensive global B2B company data—verified, AI-driven, and updated bi-weekly.

The Forager.ai Global Company Dataset delivers 65M+ high-quality firmographic records, covering public and private companies worldwide. Leveraging AI-powered validation and bi-weekly updates, our dataset ensures accuracy, freshness, and depth—making it ideal for sales intelligence, market analysis, and CRM enrichment.

📊 Key Features & Coverage ✅ 65M+ Company Records – The largest, most reliable B2B firmographic dataset available. ✅ Bi-Weekly Updates – Stay ahead with refreshed data every two weeks. ✅ AI-Driven Accuracy – Sophisticated algorithms verify and enrich every record. ✅ Global Coverage – Companies across North America, Europe, APAC, and emerging markets.

📋 Core Data Fields: ✔ Company Name, LinkedIn URL, & Domain ✔ Industries ✔ Job postings, Revenue, Employee Size, Funding Status ✔ Location (HQ + Regional Offices) ✔ Tech Stack & Firmographic Signals ✔ LinkedIn Profile details

🎯 Top Use Cases 🔹 Sales & Lead Generation

Build targeted prospect lists using firmographics (size, industry, revenue).

Enhance lead scoring with technographic insights.

🔹 Market & Competitive Intelligence

Track company growth, expansions, and trends.

Benchmark competitors using real-time private company data.

🔹 Venture Capital & Private Equity

Discover investment opportunities with granular sector-level insights.

Monitor portfolio companies and industry shifts.

🔹 ABM & Marketing Automation

Enrich CRM data for hyper-targeted campaigns.

Power intent data and predictive analytics.

⚡ Delivery & Integration Choose the best method for your workflow:

REST API – Real-time access for developers.

Flat Files (CSV, JSON) – Delivered via S3, Wasabi, Snowflake.

Custom Solutions – Scalable enterprise integrations.

🔒 Data Quality & Compliance 95%+ Field Completeness – Minimize gaps in your analysis.

Ethically Sourced – Compliant with GDPR, CCPA, and global privacy laws.

Transparent Licensing – Clear usage terms for peace of mind.

🚀 Why Forager.ai? ✔ AI-Powered Accuracy – Better data, fewer false leads. ✔ Enterprise-Grade Freshness – Bi-weekly updates keep insights relevant. ✔ Flexible Access – API, bulk files, or custom database solutions. ✔ Dedicated Support – Onboarding and SLA-backed assistance.

Tags: B2B Company Data |LinkedIn Job Postings | Firmographics | Global Business Intelligence | Sales Leads | VC & PE Data | Technographics | CRM Enrichment | API Access | AI-Validated Data

LinkedIn Company Data for Company Analysis, Valuation & Portfolio Strategy LinkedIn company data is one of the most powerful forms of alternative data for understanding company behavior, firmographics, business dynamics, and real-time hiring signals. Canaria’s enriched LinkedIn company data provides detailed company profiles, including hiring activity, job postings, employee trends, headquarters and branch locations, and verified metadata from Google Maps. This LinkedIn corporate data is updated weekly and optimized for use in company analysis, startup scouting, private company valuation, and investment monitoring. It supports BI dashboards, risk models, CRM enrichment, and portfolio strategy.

Use Cases: What Problems This LinkedIn Data Solves Our LinkedIn company insights transform opaque business landscapes into structured, analyzable data. Whether you’re conducting M&A due diligence, tracking high-growth companies, or benchmarking performance, this dataset empowers fast, confident decisions.

Company Analysis • Identify a company’s size, industry classification, and headcount signals using LinkedIn firmographic data • Analyze social presence through LinkedIn follower metrics and employee engagement • Understand geographic expansion through branch locations and hiring distribution • Benchmark companies using LinkedIn profile activity and job posting history • Monitor business changes with real-time LinkedIn updates

Company Valuation & Financial Benchmarking • Feed LinkedIn-based firmographics into comps and financial models • Use hiring velocity from LinkedIn job data as a proxy for business growth • Strengthen private market intelligence with verified non-financial signals • Validate scale, structure, and presence via LinkedIn and Google Maps footprint

Company Risk Analysis • Detect red flags using hiring freezes or drop in profile activity • Spot market shifts through location downsizing or organizational changes • Identify distressed companies with decreased LinkedIn job posting frequency • Compare stated presence vs. active behavior to identify risk anomalies

Business Intelligence (BI) & Strategic Planning • Segment companies by industry, headcount, growth behavior, and hiring activity • Build BI dashboards integrating LinkedIn job trends and firmographic segmentation • Identify geographic hiring hotspots using Maps and LinkedIn signal overlays • Track job creation, title distribution, and skill demand in near real-time • Export filtered LinkedIn corporate data into CRMs, analytics tools, and lead scoring systems

Portfolio Management & Investment Monitoring • Enhance portfolio tracking with LinkedIn hiring data and firmographic enrichment • Spot hiring surges, geographic expansions, or restructuring in real-time • Correlate LinkedIn growth indicators with strategic outcomes • Analyze competitors and targets using historical and real-time LinkedIn data • Generate alerts for high-impact company changes in your portfolio universe

What Makes This LinkedIn Company Data Unique

Includes Real-Time Hiring Signals • Gain visibility into which companies are hiring, at what scale, and for which roles using enriched LinkedIn job data

Verified Location Intelligence • Confirm branch and HQ locations with Google Maps coordinates and public company metadata

Weekly Updates • Stay ahead of the market with fresh, continuously updated LinkedIn company insights

Clean & Analysis-Ready Format • Structured, deduplicated, and taxonomy-mapped data that integrates with CRMs, BI platforms, and investment models

Who Benefits from LinkedIn Company Data • Hedge funds, VCs, and PE firms analyzing startup and private company activity • Portfolio managers and financial analysts tracking operational shifts • Market research firms modeling sector momentum and firmographics • Strategy teams calculating market size using LinkedIn company footprints • BI and analytics teams building company-level dashboards • Compliance and KYC teams enriching company identity records • Corp dev teams scouting LinkedIn acquisition targets and expansion signals

Summary Canaria’s LinkedIn company data delivers high-frequency, high-quality insights into U.S. companies, combining job posting trends, location data, and firmographic intelligence. With real-time updates and structured delivery formats, this alternative dataset enables powerful workflows across company analysis, financial modeling, investment research, market segmentation, and business strategy.

About Canaria Inc. Canaria Inc. is a leader in alternative data, specializing in job market intelligence, LinkedIn company data, and Glassdoor salary analytics. We deliver clean, structured, and enriched datasets at scale using proprietary data scraping pipelines and advanced AI/LLM-based modeling, all backed by human validation. Our AI-powered pipeline is developed by a seasoned team of machine learning experts from Google, Meta, and Amazon, and by alumni of Stanford, Caltech, and Columbia ...