AI/ML
3 data and analytics 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…
7 essential skills for building a successful career in Data Science
According to the US Bureau of Labor Statistics, data scientist jobs are predicted to increase by 36% between 2021 and 2031. This…
Sigmoid’s 7 step approach for big data project success
A scoping exercise is the holy grail of your data project success be it Data Science, Product, or Data Engineering. In our…
Defining the right data analytics KPIs to drive business success
Business leaders often find it challenging to determine the right success metrics to assess the impact of Data and Analytics(D&A) programs. A…
Creating a single source of truth for banks to accelerate productivity and customer satisfaction
The digital revolution has created a huge influx of data across the banking industry in terms of payments, online transactions, loans, and…