AI/ML
Maximizing AI Project Success through JIRA Data Upcycling
JIRA has long been a staple in the world of project management, particularly for software development teams. Its robust features provide excellent…
Cloud data modernization for business growth: Insights from industry leaders
Srinath Reddy B Head of Data Platforms & Engineering at Dun & Bradstreet Mayur Rustagi CTO and Co-Founder at Sigmoid According…
Why banks must embrace proactive risk management with AI-driven RegTech
Large firms spend up to $10,000 per employee annually on compliance, averaging around $300 million annually.¹ This significant investment could be redirected…
How to elevate digital banking experiences with data and AI
From data silos and security concerns to poor data quality and ineffective segmentation, retail banks today face a myriad of challenges in…
3 data and AI trends shaping the MedTech industry
In the MedTech industry, one of the key challenges lies in balancing cutting-edge advancements with the practical realities of cost, regulation, and…
Driving regulatory success in capital markets with data governance
The ever-evolving regulatory landscape of capital markets feels like a tightrope walk. One misstep with data management, and brand reputation along with…
How data-driven strategies can strengthen risk management in investment banking
For decades, risk management relied heavily on historical data and reactive measures. Loan approvals were based on heuristic records, fraud detection focused…
6 data engineering fundamentals to accelerate generative AI deployment in banking
Generative AI-based models are quickly becoming essential solutions for enhancing operational efficiency, improving customer experiences, and mitigating risks in the banking and…
Scalable data architecture to create seamless digital banking experiences
The need for seamless banking experiences and personalized services is driving banks to leverage data and analytics for effective decision-making. According to…