As ESG (Environmental, Social, and Governance) considerations gain prominence, asset managers face increasing pressure to meet regulatory requirements and satisfy investors who are demanding greater transparency and accuracy in disclosures. Traditional, manual methods... View
The ESG (Environmental, Social, and Governance) landscape is rapidly evolving, driven by regulatory requirements and increasingly by investor expectations. Asset managers who focus solely on compliance risk missing a critical shift: today, the investors are leading... View
Unpacking the ESG Regulatory Mosaic As ESG regulations proliferate worldwide, asset managers must navigate a complex regulatory mosaic of frameworks, timelines, and unique requirements. Global frameworks like the ISSB standards offer a baseline for ESG integration.... View
As ESG (Environmental, Social, and Governance) expectations from regulators and investors grow, asset managers increasingly recognize that ESG transformation is not merely a compliance exercise but a strategic investment essential to building long-term shareholder... View
As ESG (Environmental, Social, and Governance) metrics evolve into critical components of financial strategy, the responsibility for managing ESG data is shifting toward CFOs and finance teams. This transition is driven by the financialization of ESG data, where... View
Regional banks are not behind on AI in software delivery. They are ahead. The real question is whether test automation moved with them. Most bank technology leaders have this backwards. The assumption, understandably, is that regional banks and credit unions are playing catch-up on AI, that megabanks with larger technology budgets are further along. The […]
Development moved faster this year. Most quality engineering functions did not move with it. Here is how to tell if yours is one of them. Ask most CIOs, CTOs, and Heads of Engineering at regional and challenger banks whether their development teams got faster this year, and the answer comes quickly: yes, obviously. Ask the […]
Banks increasingly consume AI through vendor APIs, SaaS platforms, cloud services, and embedded features. Proprietary architecture can limit visibility, but it does not transfer accountability. SR 26-2 states that model risk principles remain applicable to vendor products and calls for institution-specific understanding, validation, monitoring, and outcome analysis. A vendor model card is an input to […]