Finalytica Experiential Learning – Agentic AI for Knowledge Interface

GenAI Agents for Knowledge Interface

Introduction:

There are specialized AI models – each designed to excel at a particular task. These models can write, analyze or even classify documents. These models are like skilled specialists, each performing their particular role with expertise.… Continue reading

Finalytica Mar 2025, Experiential Learning – Cloud-Based Data Warehousing

Setup of a Cloud-Based Data Warehousing Solution on AWS for a South Asian Bank

Introduction

For Banks and large financial Institutions, consolidating data plays a crucial role in decision-making and strategic planning. One of our banking clients faced significant challenges in managing their scattered data infrastructure and they had a manual reporting process.… Continue reading

Finalytica Feb, 2025 – How Agentic AI is Transforming Data Analytics and Decision-Making

A special kind of AI framework called Agentic AI framework promises to apply decision-making in real time, thus preparing organizations for the AI age. Whereas in the conventional paradigm rules yield to pre-formatting, Agentic AI actively perceives its context, gathers information, and acts.… Continue reading

Finalytica Jan, 2025: Milestones Achieved by G-Square in 2024

I. Geographic Expansion

G-Square successfully entered the North American markets, on-boarding two new clients from this region.
The US market, being a critical area for future growth, has become a significant focus.
G-square also acquired an additional client in South Asia.

Finalytica Experiential Learning, NOV 2024: Fund Transfer Pricing (FTP): Methodology & Use cases for Financial Institutions

Introduction

Funds Transfer Pricing (FTP) is a sophisticated methodology employed by financial institutions to accurately attribute profitability to their diverse funding sources and applications. By leveraging FTP, banks and other financial organizations can gain invaluable insights into their operational strengths and weaknesses, informing strategic decisions to optimize performance and maximize returns.… Continue reading

Finalytica Experiential Learning, October 2024: Text-to-SQL Prompt Engineering

Introduction

Text-to-SQL aims to narrow the gap between database systems and business users by automating the conversion of natural language queries into SQL commands. By utilizing the capabilities of Large Language Models (LLMs), it enhances the Text-to-SQL process, thereby enhancing data processing efficiency and enabling a range of applications including automated data analysis, intelligent database services, and streamlined query responses.… Continue reading

The Art and Science of Prompt Engineering

I. Introduction

Large language models have revolutionized the use of Artificial Intelligence to the next level. These models are so powerful that we can solve many complex use cases using them. At the heart of harnessing this power lies the discipline of prompt engineering; a craft that involves designing and refining prompts to use the most effective and accurate responses from large models.… Continue reading

Knowledge Series: Delving into the technical depths of LLMs

Introduction

Large Language Models (LLMs) have emerged as transformative tools capable of understanding and generating human language with unprecedented accuracy. These models, underpinned by the sophisticated transformer architecture, represent a significant leap forward in natural language processing. This article delves into the technical details that make LLMs so powerful, exploring the foundational components such as self-attention mechanisms, token embeddings, and the interplay of linear and softmax layers.

Knowledge Series: Building Efficient ML Pipelines

Introduction

In today’s data-driven world, building efficient machine learning (ML) pipelines is crucial for leveraging data to drive insights and business value. In the realm of machine learning, the creation of robust, scalable, and automated pipelines is not just a technical necessity but a strategic imperative.

Knowledge Series: Use cases of Gen AI in Financial Services

Introduction

In the dynamic landscape of financial services Industry, the integration of Generative Artificial Intelligence (Gen AI) has emerged as a game-changer. In this article, we delve into the transformative applications of Gen AI, focusing on the role of Large Language Models (LLMs) such as GPT-3, BERT, and LLaMA, among others.

Experiential Learning: BI Part II: From Data views to building BI Dashboards and Insights

Background:

Having extracted data from various Data sources and establishing robust data pipelines and creating comprehensive data views in previous stages, which we covered in our previous edition of Finalytica last month. In this article and in continuation of the process, we delve into building reports & dashboards and extracting actionable insights from the accumulated data.

Experiential Learning: Creating Data Views in various environments for complex BI Dashboard Creation

Creating Data Views in various environments for complex BI Dashboard Creation

Introduction:

In various BI implementations, we have addressed the need for efficient data pipelines to build complex BI reports from diverse sources. Here’s how we practically implemented robust data pipelines supporting advanced BI dashboards, utilizing cloud platforms like AWS and GCP, as well as on-premise solutions.