Augmented analytics uses machine learning and natural language processing to automate the preparation, analysis, and explanation of data, so business teams get answers without waiting on a data science queue.
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Banking & Finance
What Is Augmented Analytics? Benefits, Use Cases & Best Practices for Enterprises
Data Governance in Banking and Financial Services: Framework, Benefits & Best Practices
When institutions run an intentional, operationalized governance model, they convert chaotic data streams into predictable business assets. That shift reduces regulatory exposure, eliminates costly manual reconciliations, and clears a straight path. Read More
How Enterprises Turn Analytics into Measurable Business Outcomes
Enterprises turn insights into analytics business outcomes by aligning analytics initiatives with specific business goals, embedding data professionals within business units… Read More
Digital Scams Are Evolving – Is Your Response Strategy Evolving Too?
Discover how AI in digital scam prevention helps organizations combat deepfakes, scams, and cyber threats. Contact Us for Solutions.
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First-party fraud is costing US banks billions: How to solve them?
Data & AI are helping detect and prevent first-party fraud in US Banks, reducing losses, improving accuracy, and protecting customer trust. Read More
Smart Data Extraction in Oil & Gas: Making Sense of What’s Buried in Unstructured Data
The oil and gas industry depends on timely, accurate data—from the field to the boardroom. But the majority of that information doesn’t come neatly packaged in dashboards or databases. Read More
How Intelligent Automation is Reshaping the Banking Industry in 2025
The demand for transformation in banking has reached a tipping point. Rising operational complexity, tighter regulations, and digital-first customers are forcing banks to rethink how they operate—fast. Read More
What are the Business Concerns Surrounding GenAI Decision-making in Banking?
GenAI transforms banking with new opportunities and exposes risks like bias, data security threats, and transparency gaps. Banks must navigate these challenges to ensure responsible use and maintain trust. Read More
How GenAI Is Redefining Product Design and Development in Financial Services
A proactive approach unlocks innovation faster. For instance, BNY’s AI tool, Eliza, leverages Nvidia hardware and cloud services from Microsoft Azure and Google Cloud, combined with AI models like GPT-4, Gemini, and Llama. Read More
How Can Banks Balance GenAI Investments with Tangible ROI?
Before deploying AI, banks must establish strong data infrastructure. GenAI thrives on high-quality, clean data, and banks must invest in building data platforms that ensure their information’s availability, consistency, and integrity. Read More