CBNITS

  Artificial Intelligence (AI), particularly Generative AI (GenAI), has rapidly emerged as a disruptive force in the financial services industry. Financial institutions globally are integrating AI-driven solutions into their operations to enhance efficiency, decision-making, and customer experience. According to a recent PwC India report , nearly 90% of financial institutions are focusing on AI and GenAI for innovation, underlining the growing importance of these technologies in reshaping the sector. The applications of AI in finance span across various areas like risk assessment, fraud detection, credit scoring , and algorithmic trading . In this blog, we’ll explore the top use cases of AI in finance, how GenAI is driving innovation, and why businesses must adopt these technologies to stay competitive in an increasingly digitized world. 1. Synthetic Data Generation One of the most crucial applications of Generative AI in finance is synthetic data generation . Financial institution...

  In the rapidly evolving landscape of artificial intelligence (AI), businesses across the globe are facing unprecedented challenges and opportunities. Generative AI (GenAI) has emerged as a powerful tool that not only enhances productivity but also redefines the way organizations operate. CBNITS , a leading provider of AI-driven solutions, is at the forefront of this revolution, delivering innovative GenAI solutions that address the unique needs of businesses. The Impact of GenAI on the Workforce According to a recent study by  Pearson,  GenAI is poised to revolutionize the Indian workforce by saving approximately 51 million hours per week by 2026. This dramatic shift in productivity is driven by the ability of GenAI to automate routine tasks, enhance decision-making processes, and create new efficiencies across various sectors. For businesses, this means not only reduced operational costs but also the ability to focus on higher-value tasks that drive innovation and grow...

  A form of conversational AI known as generative AI chatbots utilizes deep learning and natural language processing (NLP) techniques to produce human-like text responses instantly during interactions. These chatbots engage in text-based conversations, comprehend user input, and generate relevant responses within context. Key aspects of Generative AI include enhanced natural language understanding (NLU), improved text generation, contextual comprehension, minimized biases, extensive training on large datasets, increased capabilities, and growing concerns regarding ethical usage, among others. The adoption of generative AI by numerous organizations is notable, with approximately one-third of surveyed entities incorporating it into at least one operational function. This translates to about 60 percent of AI-adopting organizations integrating generative AI into their systems. Future developments in generative chatbots are anticipated to encompass enhanced multitasking, heightened em...

  Since OpenAI released ChatGPT, there have been great leaps of progress in the field of generative AI. Generative AI is a type of artificial intelligence focused on the ability of computers to use models to create content like images, text, code, and synthetic data. Generative AI applications are built on top of large language models (LLMs) and foundation models. Chatbots using LLMs can handle a wide range of tasks, including customer support, information retrieval, language translation, content generation, and more. They offer a sophisticated conversational experience that approaches human-like interaction, although they still have limitations and may occasionally produce incorrect or nonsensical responses.   CBNITS creating & co-piloting Generative AI chatbots using large language models for finance, healthcare and security industries Because many large language models are trained on general data, they can only answer general questions. They are better at interpreting ...