India's Credila Financial Services files for $584 million IPO
June 26 (Reuters) - Credila Financial Services on Thursday filed for an initial public offering worth 50 billion rupees ($583.76 million), draft prospectus showed.
($1 = 85.6520 Indian rupees)
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J.P. Morgan hires veteran dealmaker Diamandakis to deepen ties with financial sponsors
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The infrastructure of trust: building AI foundations for inclusive, explainable finance: By Diederick Van Thiel
The time is now to focus on AI infrastructure, which will enable companies to scale AI and build a future where humans and multiple AI agents successfully work together. In this blog I share some insights on how we at AdviceRobo do this so you can learn from it and build your own infrastructure of trust with AI. As the world accelerates toward an AI-first economy, one truth is becoming inescapable: no digital transformation will succeed without the right infrastructure. For financial services, especially those addressing underserved markets, the stakes are even higher. AI must be both inclusive and explainable—capable of reaching those locked out of traditional credit systems, while remaining transparent and accountable. This is the future AdviceRobo has long been building toward: a future where infrastructure meets empathy, and where AI augments human decisioning without undermining human dignity. Rethinking risk in the age of AI Traditional credit systems have failed billions of people globally—those without formal income, credit history, or access to mainstream banking. AdviceRobo has pioneered the use of psychometric data, behavioral analytics, and alternative data to assess risk far beyond FICO scores. These methods have already shown substantial lift: AdviceRobo's research reveals a 20–30% increase in acceptance rates among thin-file customers, while reducing defaults with 20% through better predictive power. But even the most advanced algorithms are only as scalable as the systems supporting them. So I invite you to enter the AI infrastructure revolution! Why Infrastructure is the next growth frontier McKinsey estimates a $5 trillion investment is needed over the next five years to support the growing appetite of AI across industries. But this isn't just about GPUs or cooling systems—it's about how you build AI that earns trust, scales cost-effectively, and adapts to regulatory demands. As Rodrigo Liang of SambaNova puts it, 'You're going to see a tenfold increase in investment for inferencing… and if it's not efficient, it won't scale.' For AdviceRobo and neo-lenders, this means focusing on three foundational pillars: 1. Hybrid AI deployment models AdviceRobo's clients—credit bureaus, retailers, digital banks and credit platforms —often span multiple jurisdictions and compliance regimes. A hybrid AI model, combining cloud-based inference with on-premises secure learning, is no longer optional; it's table stakes. This flexibility allows financial institutions to deploy AdviceRobo's scoring agents locally, while retraining them globally—a balance between data sovereignty and model innovation. 2. Agentic AI for dynamic (credit) decisioning Agentic AI—the use of multiple autonomous, specialized AI agents working in coordinated workflows—is redefining real-time decision-making. Imagine a suite of AdviceRobo agents: One analyzing psychometric data, Another adjusting for behavioral shifts, A third scanning macroeconomic risks. Each agent contributes to a unified, explainable decision. And with response times as fast as 0.03 seconds, these agents feel instantaneous to both lenders and borrowers. This is the dawn of always-on, always-fair credit decisioning. 3. Explainability as core infrastructure AI in finance must be auditable, not a black box. AdviceRobo has led the change in integrating explainable AI (XAI)—highlighting which behavioral traits influenced a risk score, and why. We work with powerful models that can capture the complexities of today's world far more effectively than traditional logistic regression models. At the same time, we use tools like SHAP values and LIME to open up these 'black boxes' and ensure that our AI-driven decisions remain transparent and explainable. This capability isn't just about compliance. It's about empowerment. Borrowers can gain insights into how to improve their profiles, and lenders build trust with regulators and stakeholders. In my opinion: 'We have to cross this S-curve, where we have enough infrastructure that convinces us the models are behaving correctly and the outputs are being securely managed.' Toward inclusive finance at scale The next chapter for AdviceRobo lies not in building bigger models, but smarter infrastructure—systems that: Are multi-lingual and culturally contextual , , Run efficiently even in data-constrained environments, And prioritize inclusion, from UX to underwriting. The ambition? To AI-ify credit and democratize access to credit for the 1.7 billion people currently unbanked—not with brute-force computation, but with infrastructure designed for empathy, precision, and global scale. And we're just getting started. We're also developing AI agents tailored for the embedded finance space, supporting industries like insurance, telecommunications, and retail—each with its own unique challenges and opportunities. In insurance, our agents help underwrite policies using behavioral data, making coverage more accessible for underserved or high-risk segments. In telecom, AI-driven financial profiling can enable dynamic credit limits for prepaid-to-postpaid transitions, or personalized device financing offers. And in retail, our technology powers embedded lending at the point of sale—enabling instant credit decisions and personalized repayment options that drive conversion and loyalty. These use cases all build on AdviceRobo's core strengths: behavioral data science, explainable AI and api-based scalable infrastructure. This ensures our partners can scale inclusive financial services—seamlessly integrated into their customer journeys. Our models go far beyond traditional statistical methods, and our use of explainability tools like SHAP and LIME ensures that every prediction can be trusted, audited, and acted upon—whether you're approving a loan, hiring a candidate, or retaining a customer. Final word: infrastructure is the new differentiator In a world where AI is ubiquitous, the companies that win will be those who build infrastructure with purpose. AdviceRobo is already ahead of the curve—blending cutting-edge AI, ethical risk profiling, and scalable delivery – and there to help others to drive this transformation succesfully too. Because the future isn't just algorithmic. It's agentic, explainable, and radically inclusive.
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Damaged unit of Iran's South Pars refinery back operating, Nour News says
June 26 (Reuters) - A damaged unit of the South Pars refinery's Phase 14, which was hit by Israel in its first strike on Iran's oil and gas sector, has returned to operation, the Iranian state-run agency Nour News reported on Thursday. South Pars, the world's biggest gas field, is located offshore in Iran's southern Bushehr province and is responsible for the lion's share of the country's gas production. Iran is the world's third largest gas producer after the United States and Russia. Gas production was not halted and the damaged unit was repaired in about 10 days, the agency added. On June 14, the Israeli strike caused a fire, which has been extinguished, in one of the four units of Phase 14. Israel launched an air offensive against Iran on June 13 killing commanders and scientists and bombing nuclear sites, saying it wanted to stop Tehran building an atomic weapon. After a 12-day air war between Israel and Iran, U.S. President Donald Trump announced on Monday a ceasefire between them.
