Quant Insight completes series C funding
0
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
The investment will accelerate Quant Insight's global expansion, enhance its unique macro factor risk models, and strengthen its position as the leading provider of macro intelligence for modern investment management.
Solving the Hidden Macro Risk Challenge
Quant Insight addresses a critical gap in portfolio management: the inability to quantify macro exposures that drive over 50% of equity returns during market stress. While traditional risk models focus on equity style factors, macro risks drive returns during market volatility.
"Macro factors increasingly challenge equity investors' ability to generate alpha, yet they remain hard to quantify," said Mahmood Noorani, CEO of Quant Insight. "Our platform provides this critical missing piece—quantifiable macro factor intelligence that complements traditional style factor models."
Strategic Partnership for Fintech Excellence
7RIDGE brings exceptional domain expertise with a proven track record scaling enterprise-facing technologies for trading, capital markets, and investment management. The firm's portfolio includes Digital Asset Holdings, Trading Technologies, and Raft Technologies.
"Quant Insight represents exactly the type of transformative technology that makes the global financial system more robust and efficient," said Carsten Kengeter, CEO of 7RIDGE. "Quant Insight's macro risk analytics fill a genuine market need with rigorous quantitative methodology. We're excited to leverage our capital markets expertise to help scale their platform globally."
Proven Technology
Quant Insight's platform provides three core solutions:
Macro Factor Equity Risk Model (MFERM): Decomposes portfolio returns into explainable macro components and provides clarity on macro exposure
Cross-Asset Valuation Engine: Identifies macro dislocations and fair value gaps across asset classes
Asset Management Solutions: Construction of active ETFs and risk hedging products
The technology covers 13,000+ global assets with API integration and partnerships with leading risk platforms.
The Series A funding will enable global expansion, enhanced platform capabilities with machine learning, scaled operations, and new applications for macro intelligence.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Geeky Gadgets
12 minutes ago
- Geeky Gadgets
ChatGPT Data Analysis : Turn Raw Data into Gold with the DIG Framework
What if you could transform the way you analyze data in just 12 minutes? Picture this: a mountain of raw numbers and spreadsheets that once felt overwhelming now becomes a treasure trove of actionable insights—all thanks to a tool you already know, paired with a simple yet powerful framework. With the rise of AI tools like ChatGPT, the barriers to effective data analysis are crumbling, making it accessible to anyone, regardless of technical expertise. Whether you're a seasoned professional or a curious beginner, the ability to turn messy datasets into meaningful stories is no longer reserved for data scientists. The secret lies in the DIG framework, a structured approach that simplifies analysis while maximizing impact. In the video below, Jeff Su explains how to use ChatGPT as your personal data analyst, guided by the three-step DIG framework: Description, Introspection, and Goal Setting. From identifying trends in streaming platform data to solving real-world business challenges, this methodology enables you to approach data with clarity and confidence. You'll also discover practical tips for addressing common challenges, like resolving data quality issues or validating AI-generated insights. By the end, you won't just learn how to analyze data—you'll master the art of turning information into decisions. After all, isn't it time your data started working for you? What Is the DIG Framework? The DIG framework—Description, Introspection, and Goal Setting—provides a systematic approach to analyzing data. It simplifies the process into three clear steps, making sure you remain organized and focused throughout your analysis. Description: Begin by thoroughly understanding your dataset. Examine its structure, identify key columns, sample the data, and check for inconsistencies, missing values, or errors. This foundational step ensures your dataset is reliable and ready for analysis. Begin by thoroughly understanding your dataset. Examine its structure, identify key columns, sample the data, and check for inconsistencies, missing values, or errors. This foundational step ensures your dataset is reliable and ready for analysis. Introspection: Explore the dataset by asking critical questions. What insights are you seeking? Are there trends, patterns, or anomalies that stand out? This step fosters curiosity and helps you identify areas that require deeper investigation. Explore the dataset by asking critical questions. What insights are you seeking? Are there trends, patterns, or anomalies that stand out? This step fosters curiosity and helps you identify areas that require deeper investigation. Goal Setting: Clearly define the objectives of your analysis. Are you aiming to uncover trends, answer specific stakeholder questions, or support strategic decisions? Setting clear goals ensures your analysis remains focused and actionable. How to Use the DIG Framework with ChatGPT Applying the DIG framework with ChatGPT is straightforward and highly effective. Start by uploading your dataset, whether it consists of sales data, survey responses, or streaming platform statistics. For example, if you're analyzing Apple TV+ data, you can prompt ChatGPT to describe the dataset, identify trends in content genres, or highlight missing information. To enhance your analysis, consider merging datasets using unique identifiers such as IMDb IDs. This allows you to combine data from multiple sources, providing a more comprehensive view. For instance, merging Apple TV+ data with IMDb ratings can help you evaluate the performance of specific genres or titles, offering deeper insights into audience preferences. Master Data Analysis with ChatGPT Watch this video on YouTube. Take a look at other insightful guides from our broad collection that might capture your interest in ChatGPT data analysis. Why Use the DIG Framework? The DIG framework is particularly beneficial for individuals who may not have advanced technical expertise. It simplifies the data analysis process while maintaining depth and accuracy, making it accessible to a wide range of users. Accessibility: The framework is designed to make data analysis approachable for professionals across various industries, regardless of their technical background. The framework is designed to make data analysis approachable for professionals across various industries, regardless of their technical background. Efficiency: By structuring your workflow, the DIG framework helps you save time and focus on extracting meaningful insights without unnecessary complexity. By structuring your workflow, the DIG framework helps you save time and focus on extracting meaningful insights without unnecessary complexity. Insight Discovery: It enables you to uncover trends, patterns, and gaps that might otherwise go unnoticed, making sure a comprehensive analysis. Real-World Applications of the DIG Framework The DIG framework can be applied to a variety of real-world scenarios, delivering valuable insights across industries. For example, analyzing Apple TV+ data might reveal a growing preference for original dramas or an increasing interest in documentaries. It could also highlight gaps, such as missing demographic information, which can guide future data collection efforts and refine your analysis. In a business context, the framework can help organizations identify customer behavior trends, optimize marketing strategies, or improve operational efficiency. For researchers, it can streamline the process of analyzing survey data or experimental results, making sure accurate and actionable conclusions. Tips for Effective Data Analysis To maximize the value of your data analysis efforts, consider the following best practices: Anticipate Stakeholder Needs: Think about the questions your audience or stakeholders might ask and tailor your analysis to address their priorities. Think about the questions your audience or stakeholders might ask and tailor your analysis to address their priorities. Focus on Relevant Data: Use ChatGPT to prioritize the most critical information, making sure your findings align with your objectives and avoid unnecessary distractions. Use ChatGPT to prioritize the most critical information, making sure your findings align with your objectives and avoid unnecessary distractions. Validate AI Outputs: While ChatGPT is a powerful tool, it's essential to cross-check its outputs with your dataset to ensure accuracy and reliability. While ChatGPT is a powerful tool, it's essential to cross-check its outputs with your dataset to ensure accuracy and reliability. Address Data Quality Issues: Resolve inconsistencies, missing values, or errors in your dataset early in the process to avoid skewed or misleading results. Building Advanced Skills Once you've mastered the basics of the DIG framework, you can explore more advanced techniques to enhance your data analysis capabilities. For instance, learning how to mitigate AI hallucinations—where AI generates incorrect or misleading information—can improve the reliability of your results. Additionally, developing skills to debug data errors or handle complex datasets will further strengthen your ability to work with AI-driven tools like ChatGPT. Advanced users can also experiment with integrating external data sources, applying statistical models, or visualizing data trends to communicate findings more effectively. These skills not only improve the quality of your analysis but also ensure your insights are actionable and impactful. Unlocking the Power of Data Analysis The DIG framework offers a structured, accessible approach to data analysis, empowering users of all skill levels to uncover trends, identify gaps, and make data-driven decisions. By using ChatGPT as your personal data analyst, you can streamline your workflow, save time, and focus on generating meaningful insights. Whether you're a business professional, researcher, or student, this methodology equips you with the tools to confidently navigate the world of data analysis in just 12 minutes. Media Credit: Jeff Su Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
The Sun
13 minutes ago
- The Sun
Warning to all 1.8bn Gmail users over ‘hidden danger' that steals password without you noticing – what to watch out for
AN URGENT warning has been issued for over a billion Gmail users amid a "hidden danger" which is stealing passwords - and this is what you need to watch out for. The new type of attack has been flying under the radar, attacking an eye-watering 1.8 billion Gmail users without them even noticing. 2 Users therefore need to make sure they follow the correct instructions in order to combat the malicious activity. Thieving hackers are using Google Gemini - the company's AI built-in tool - to trick users into giving over their credentials. Cybersecurity experts have found that bad actors are sending emails with concealed instructions that cause Gemini to generate fake phishing warnings. These tricks users into sharing personal account information, or visiting malicious websites. The emails are usually constructed in a manner which makes them appear urgent - and occasionally from a business. Shady hackers will craft these emails by setting the font size to zero and the text colour to white - before inserting prompts invisible to users but picked up by Gemini. GenAI bounty manager Marco Figueroa demonstrated how such a dangerous prompt could falsely alert users that their email account has been compromised. These warnings would urge victims to call a fake "Google support" phone number provided, in order to resolve the issue. To fight these prompt injection attacks, experts have made a number of recommendations that users should act on immediately. They firstly suggested that companies configure email clients to detect and neutralise hidden content in message bodies. Google adds AI upgrade to your Gmail that writes emails for you – find it in seconds if you're eligible for freebie This should help counter hackers sending invisible text within emails. Security experts also recommended that users implement post-processing filters to scan inboxes for suspicious elements like "urgent messages", URLs, or phone numbers. This action could bolster defences against threats. The scam was brought to light after research, spearheaded by Mozilla's 0Din security team, showed proof of one of the hostile attacks last week. The report showed how hackers tricked Gemini into showing a fake security alert. It warned users their password had been stolen - but the message was fake and designed to steal their info. The trick works by hiding a secret size zero font prompt in white text that matches the email background. So when someone clicks "summarise this email" using Gemini, the tool reads the hidden message - not just the visible bit. This form of manipulation is named "indirect prompt injection", and it takes advantage of AI's inability to differentiate between a user's question and a hacker's embedded message. AI cannot tell the difference, as both messages look like text, and it will usually follow whichever comes first - even if it is malicious. As Google have failed to patch this method of scamming victims, the door is still open for hackers to exploit this technique. Sneaking in commands that the AI may follow will be an effective method of leaking sensitive data until users are properly protected against the threat. AI is also incorporated into Google Docs, Calendar, and outside apps - widening the scope of the potential risk. Google has reminded users amid this scamming crisis that it does not issue security alerts through Gemini summaries. So if a summary tells you that your password is at risk, or prompts you with a link to click - users should always treat it as suspicious and delete the email.
Finextra
42 minutes ago
- Finextra
Payments startup yetipay raises £3.5m
UK payments startup yetipay today announced that it has raised £3.5 million to continue the expansion of its all-in-one payments platform and introduce new products to its growing base of independent and enterprise hospitality and retail customers, including Brewdog, Pho, Grasso Soho, Kütchenhaus and Zenith. 0 This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author. Yetipay has agreed a debt facility up to £1.75 million with re:cap, the Berlin-based fintech behind the Capital Operating System (Capital OS) – becoming the first UK business to benefit from re:cap's €125M credit facility provided by HSBC Innovation Banking and Avellinia Capital, launched last week. Yetipay has concurrently raised £1.7 million equity from super angel investors. The company's high-profile angel backers include Paul Statham (Condeco, Thoma Bravo), Mark Blandford (Blandford Family Office), Ben Whitaker (Masabi), Lloyd Amsdon (Watchfinder), Christian Riener (PCP Capital) and Simon Squibb (HelpBnk). 'We focused on raising the minimum amount required and selecting investors that bring valuable deep payments industry experience, combined with innovative non-dilutive funding from re:cap,' said Oliver Pugh, Founder of yetipay. 'We are in a David vs Goliath battle with our larger competitors, where their massive OPEX commitments present a significant opportunity for our nimble, innovative and customer-centric approach. We've stayed lean, raised capital in a sustainable non-dilutive way, and delivered products that offer real benefits – there's more to come in 2025.' Yetipay is the first UK company to be backed by Berlin's re:cap, and this raise highlights the growing momentum behind alternative funding models across Europe's SaaS and fintech ecosystems. yetipay has £4.7 million in ARR and is currently processing £450 million per year in transactions. The latest round brings yetipay's total funding to £6.6 million raised. 'We're thrilled to back yetipay as our first customer in the UK,' says Christian Luecke, Chief Commercial Officer at re:cap. 'Their ability to generate significant traction with a lean, focused team – while delivering a very sticky product to a clearly defined market – makes them an exceptional partner and an exciting company to work with.' The yetipay platform simplifies payments for businesses, offering reliable tools that make paying quick and simple for customers while also saving businesses time and money so that they can focus on their core work. The company's suite of innovative tools is continually evolving, adding new features and functionality. The yetipay goal is to compete with the biggest players in transaction volume while keeping operations lean. Headquartered in David Bowie's former Soho studio, the 26-person team has built an innovative payments platform that offers features typically found only in much larger players.
