Core Insights - Diginex Limited reported a transformative fiscal year ending March 31, 2025, highlighted by a 57% increase in revenues and the successful completion of its IPO in January 2025 [4][5][17] - The company signed strategic agreements with professional firms to enhance future revenues and client acquisition, while also introducing AI-powered compliance solutions [4][5] - Diginex is pursuing a dual listing on the Abu Dhabi Securities Exchange to increase exposure to investors and support sustainable finance initiatives in the GCC region [4][5] Financial Performance - Total revenue for the fiscal year increased by 57% to $2.0 million, driven primarily by software subscriptions and license fees [5][8] - The net loss for the fiscal year was $5.2 million, an increase of $0.3 million compared to the previous year's loss of $4.9 million [5][24] - General and administrative expenses rose to $10.3 million, primarily due to IPO-related professional fees and share-based payments [13][24] Revenue Breakdown - Revenue from subscription and license fees increased significantly to $1.3 million from $0.4 million, while advisory fees rose modestly to $0.3 million [7][9] - Customization fees decreased to $0.4 million from $0.7 million, reflecting a strategic shift towards core product development [10][11] Balance Sheet Highlights - As of March 31, 2025, Diginex reported net assets of $4.6 million, a significant improvement from net liabilities of $23.0 million the previous year [15][23] - The company's cash position improved to $3.1 million from $0.1 million at the end of the prior fiscal year [15][23] Strategic Initiatives - Diginex signed memoranda of understanding to acquire Resulticks Group Companies and Matter DK ApS, aimed at enhancing its technology and data capabilities [5][6] - The planned acquisitions are expected to expand Diginex's AI-driven data management and sustainability analytics capabilities [6][17]

Core Insights - The article discusses the author's academic and professional background in Machine Learning, Economics, and Finance, highlighting expertise in Data Science and Machine Learning applications within the banking and finance sectors [1]. Group 1: Academic Background - The author holds a PhD in Machine Learning with a focus on Economics and Finance [1]. - The author has academic affiliations with IESE Business School, ESADE Business School, and the Barcelona Supercomputing Center [1]. Group 2: Professional Experience - The author has worked at Deloitte Financial Advisory, specializing in Data Science and Machine Learning applications for clients in banking, insurance, and finance [1]. - The author currently teaches Asset Pricing and Introduction to Corporate Finance at ESADE Business School at the MSc/BSc level [1]. Group 3: Research Focus and Interests - Current research focuses on Generative AI in sustainable finance [1]. - The author's interests include machine learning and generative AI applications in finance and economics, with proficiency in Python, R, and SQL [1].

Core Insights - The article discusses the author's academic and professional background in Machine Learning, Economics, and Finance, highlighting expertise in Data Science and Machine Learning applications within the banking and finance sectors [1]. Group 1: Academic Background - The author holds a PhD in Machine Learning with a focus on Economics and Finance [1]. - The author has academic affiliations with IESE Business School, ESADE Business School, and the Barcelona Supercomputing Center [1]. Group 2: Professional Experience - The author has worked at Deloitte Financial Advisory, specializing in Data Science and Machine Learning applications for clients in banking, insurance, and finance [1]. - The author currently teaches Asset Pricing and Introduction to Corporate Finance at ESADE Business School at the MSc/BSc level [1]. Group 3: Research Focus and Interests - Current research focuses on Generative AI in sustainable finance [1]. - The author's interests include machine learning and generative AI applications in finance and economics, with proficiency in Python, R, and SQL [1].

Core Insights - The article discusses the author's academic and professional background in Machine Learning, Economics, and Finance, highlighting expertise in Data Science and Machine Learning applications within the banking and finance sectors [1] - The current research focus is on Generative AI in sustainable finance, indicating a trend towards integrating advanced technologies in financial practices [1] Group 1: Academic and Professional Background - The author holds a PhD in Machine Learning with a focus on Economics and Finance, and has affiliations with prestigious business schools and research centers [1] - Professional experience includes working at Deloitte Financial Advisory, specializing in Data Science and Machine Learning applications for clients in banking, insurance, and finance [1] - The author teaches Asset Pricing and Introduction to Corporate Finance at ESADE Business School at both MSc and BSc levels [1] Group 2: Research Interests and Skills - Current research interests include Generative AI applications in sustainable finance, reflecting a growing intersection of technology and finance [1] - Proficient in programming languages such as Python, R, and SQL, which are essential for data analysis and machine learning applications in finance [1]

Group 1 - The individual holds a PhD in Machine Learning with a focus on Economics and Finance, indicating a strong academic background relevant to financial analysis [1] - Professional experience includes working at Deloitte Financial Advisory, specializing in Data Science and Machine Learning applications for clients in banking, insurance, and finance, highlighting expertise in applying advanced technologies in financial sectors [1] - Current teaching roles include Asset Pricing and Introduction to Corporate Finance at ESADE Business School, suggesting involvement in educating future finance professionals [1] Group 2 - Research interests focus on Generative AI in sustainable finance, indicating a trend towards integrating advanced AI technologies in financial practices [1] - Proficiency in programming languages such as Python, R, and SQL, which are essential for data analysis and financial modeling in the industry [1] - The individual has publications in Artificial Intelligence and finance journals, reflecting a commitment to contributing to academic and professional discourse in these fields [1]

Group 1 - Vox Royalty (NASDAQ: VOXR) is identified as a small-cap precious-metals royalty company with shares trading at approximately $3.13 and a market capitalization of around $162 million, which is perceived to be undervalued relative to its growth prospects [1] - The company has a diversified portfolio consisting of over 60 royalties, indicating a broad exposure to the precious metals sector [1] - The management team is described as shareholder-aligned, suggesting a focus on maximizing shareholder value [1]

Group 1 - Wheaton Precious Metals operates a unique streaming model, providing upfront financing to miners in exchange for a percentage of future metal production at low costs [1] - This streaming model has resulted in consistent, high-return investments for the company [1] Group 2 - The company does not own mines, which differentiates it from traditional mining companies [1]

LONDON, June 30, 2025 (GLOBE NEWSWIRE) -- Diginex Limited (“Diginex” or the “Company”) (NASDAQ: DGNX), a leading provider of Sustainability RegTech solutions, today announced additional government funding support for its innovative AI-powered compliance solutions. Diginex’s AI-powered compliance solutions will continue to focus on helping companies comply with sustainability disclosure requirements set by the International Sustainability Standards Board (ISSB) and International Financial Reporting Standards ...

Core Viewpoint - Nokia has signed a EUR 1.5 billion five-year multicurrency revolving credit facility with a pricing mechanism linked to its sustainability targets, replacing a previous EUR 1,412 million agreement from 2019 [1][9]. Group 1: Sustainability Targets - The sustainability targets for the revolving credit facility include the reduction of absolute Scope 1 and 2 greenhouse gas emissions and the reduction of absolute Scope 3 GHG emissions, with annual observation periods impacting pricing adjustments for the following year [2][9]. - Nokia is committed to achieving a Net-Zero target by 2040, which has been validated by the Science Based Targets initiative (SBTi) [4]. Group 2: Financing Strategy - Nokia's financing strategy is closely linked to its sustainability strategy, building on previous initiatives such as the sustainability-linked guarantee facility in 2022 and the sustainable finance framework launched in 2023 [3][9]. - The new revolving credit facility reflects strong support from key banking partners, aligning financing with sustainability priorities [6][7]. Group 3: Operational Approach - Detailed operational approaches to reducing GHG emissions are outlined in Nokia's Net-Zero climate transition plan, which includes commitments and actions for decarbonization [5]. - Nokia published its 2024 Annual Sustainability Statement in March 2025, adhering to the EU Corporate Sustainability Reporting Directive and European Sustainability Reporting Standards [5].

LONDON, June 26, 2025 (GLOBE NEWSWIRE) -- Diginex Limited (“Diginex” or the “Company”) (NASDAQ: DGNX), a leading provider of Sustainability RegTech solutions, today announced its inclusion in the S&P Global Broad Market Index (BMI), effective June 22, 2025. The addition to this widely recognized index marks a notable milestone for Diginex. The S&P Global BMI is one of the most comprehensive equity benchmarks in the world, covering more than 14,000 companies across developed and emerging markets. Inclusion i ...