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DLA Piper advised #telecommunications company Liberty Latin America Ltd. on a transformative ten-year strategic engagement with Amdocs that will transform Liberty Latin America’s technology operations through an AI-driven operating model. Read more: spr.ly/6010B1Moog https://t.co/RiOaps3g1t

When Skrill calls, I always pick up, when my old bank calls, I let it go to voicemail 🥱 https://t.co/wb4PgXIJuH

As high-voltage #batteries move through increasingly complex lifecycle stages, determining whether and how they can be #transported safely and lawfully becomes a central operational question. Read our alert for key considerations: spr.ly/6011B1Moe9 #Environmental #Energy https://t.co/oseYxxbwwY

DLA Piper ranked Top 10 in Octus 2026 H1 Private Credit League Tables. * Total Engagements: #7 (33) * Borrower/Sponsor: #7 (9) * Lender: #8 (24) * Debt Quantum | Overall Middle Market: #6 Read more: spr.ly/6017B1MoeT https://t.co/o3p46AkkRv

Proud to volunteer with Sun Youth alongside the Paysafe team!🎒📚 Supporting students and families as they prepare for the new school year. Thank you to everyone involved!💙 #Paysafe #IncomeAccess #VolunteerWork #SunYouth #GivingBack #BackToSchool https://t.co/ReFMHOA53z

RT FICCI FRAMES: The landscape is changing and so is the way we create value. Introducing #FICCIFRAMES2026 theme: India's Media Moment :…

Responsible AI should be embedded within the existing enterprise risk-management framework, with governance spanning the entire AI lifecycle—from data selection and model development to deployment and continuous monitoring. For banks serving thin-file customers, particularly in rural and semi-urban markets, explainability, fairness testing and meaningful human oversight are essential to ensure that AI does not inadvertently automate exclusion: Mr George K. John, Executive Director, ESAF Small Finance Bank in a session on risk, compliance and responsible AI at #FIBAC2026

The future of credit decisioning lies in combining regulated bureau data with alternate and surrogate data to create more comprehensive and explainable risk assessments. While AI can automate processes and generate intelligent risk signals, responsible lending will continue to require human judgment to validate complex cases and ensure transparent, unbiased decisions: Mr Sachin Seth, Regional Managing Director, India and South Asia, CRIF India in a session on risk, compliance and responsible AI at #FIBAC2026

The future of compliance will require a fundamental shift in capabilities as institutions move from rule-based frameworks to principle-based oversight. While AI will increasingly augment compliance functions, human judgment, business understanding, and decision science will remain indispensable. Building these hybrid capabilities will be a gradual journey, giving organisations the opportunity to evolve alongside technology: Mr P R Seshadri, MD & CEO, South Indian Bank in a session on risk, compliance & responsible AI at #FIBAC2026

Risk management is moving from qualitative overlays to more quantitative, data-driven assessment, with emerging risks such as climate and AI increasingly finding a place in credit and underwriting frameworks. Strong governance will be critical as this transition progresses: Mr Brajesh Kumar Singh, MD & CEO, Canara Bank in a session on Risk, Compliance & Responsible AI at #FIBAC2026

Data governance is important for AI to function properly and efficiently. It is also important to have a digital consent framework which can be pulled up in a short time. Most of our work, is built on large language models which are not originating from India and that is the greatest risk. Model localisation is essential, with no kill switch outside India: Mr Sudipta Roy, MD & CEO, L&T Finance in a session on Risk, Compliance & Responsible AI at #FIBAC2026

AI’s most meaningful impact on MSME finance may come from creating data symmetry by making relevant financial information available in a form that small businesses can easily understand and use. Better information can improve credit access, enable faster lending decisions and support stronger business growth across the MSME ecosystem: Mr Kumar Abhishek, Founder & CEO, ToneTag

AI is increasingly being integrated across both the business cycle and the customer life cycle to create a more seamless banking experience. From sales enablement and eligibility assessment to lead conversion and customer engagement, AI is becoming a core operating capability: Mr Rakesh Singh, Executive Director & CEO – NBFC, Aditya Birla Capital in session on AI-powered credit engine at #FIBAC2026

MSME lending is emerging as a major use case for AI, as banks increasingly combine business data, credit analytics and market intelligence to make better credit decisions and manage relationships at scale. For collateral-based lenders, AI can further strengthen valuation, title verification and portfolio monitoring, enabling earlier detection of risk signals and more proactive risk management: Mr Salee S Nair, MD & CEO, Tamilnad Mercantile Bank Ltd. in session on AI powered credit engine at #FIBAC2026

Agentic AI is compressing the transformation cycle in banking—from four to six quarters for building agent workflows to potentially four to six weeks. As the transition from pilot to production accelerates, the need for equally agile governance and risk controls becomes critical: Ms Pankaj Sharma, Head – Business Transformation, IndusInd Bank in session on Agentic AI at #FIBAC2026