Beyond ChatGPT: Understanding the Trends of Evolving Generative AI For Finance

Beyond ChatGPT: Understanding the Trends of Evolving Generative AI For Finance

7 Min Reads

Emagia Staff

Editor’s Note: Thank you for joining for part four of four in our “Beyond ChatGPT” blog series. If you’ve missed the previous installments in this series, click one of the following links to review this critically important content.

As businesses aim for better efficiency and productivity in today’s highly competitive and volatile markets, innovative technologies like Generative AI (GenAI) are becoming crucial tools for businesses to achieve success and growth.

GenAI-enabled products help companies harness the potential of AI models to embrace advanced levels of creativity, productivity, and problem-solving capabilities. These technologies transform the digital world, enabling users to create original content and intricate analytics, proactively identify business risks, or develop complicated software. Importantly, it helps professionals – especially in finance functions – do so more rapidly than ever before and help free up time for the most important tasks that require human touch and focus.

It’s increasingly critical for businesses to become not only aware but proficient with these GenAI-powered solutions. What was once about establishing an edge over the competition is now about merely keeping pace, as the explosion of AI use following the widespread adoption of ChatGPT following its release in late 2022.

As Gartner articulated, Generative AI is no longer just a technology or a business case — it is a key part of a society in which people embrace working together with machines as a teammate or copilot. In fact, Gartner predicted that than 100 million professionals will use “robocolleagues” to contribute to their work by 2026.

Let’s examine how businesses can leverage GenAI’s capabilities to stay ahead of business rivals by looking at some of its commercial applications.

What is Generative AI (GenAI)?

Generative AI (GenAI) is a variant of Artificial Intelligence that can learn from existing content and use the learned knowledge to create new, realistic, and diverse types of artifacts, such as images, videos, music, audio, text, software code, product design, and 3D. GenAI has the capability to mimic human creativity to produce exceptionally realistic and unique content. It is a useful tool for businesses in industries ranging from gaming to entertainment, scientific research, and product design to finance processes. Recent innovations such as GPT (Generative Pre-trained Transformer) and Midjourney, leverage the remarkably advanced potentials of GenAI.

Generative AI is already revolutionizing the ways people work, communicate, and innovate. As noted, ChatGPT is a recent and exemplary example of the accelerated adoption and the high impact of GenAI. Technology is rapidly contributing to molding future technology adoption across various segments. A 2022 McKinsey survey showed that AI adoption has more than doubled over the past five years, and investment in AI is only increasing that pace. Let’s take a deep look at some applications of the technology:

Text Generation

This application entails learning patterns from existing text data to generate new text. The models used in this application include Recurrent Neural Networks (RNNs), and more recently, Transformers. Today, text generation is extensively used in natural language processing, chatbots, and content creation. ChatGPT is a recent and perhaps the most on-trend example of a tool that can generate responses that sound like human chat conversations.

Image Generation

This is a process of creating images that look similar to real-world images, with the help of deep learning algorithms such as VAEs, GANs, and, more recently, Stale Diffusion. This is also used to enhance the capabilities of machine learning models, as well as in generating product images, creating artwork, and more. Popular platforms such as MidJourney and DALL-E are popular tools that are capable of generating realistic images using Image-generation techniques.

Video and Speech Generation

Video Generation is about leveraging deep learning models such as GANs and Video Diffusion to create new videos by anticipating frames based on preceding video frames. Today, entertainment, sports, and autonomous driving are the areas that predominantly use the Video Generation. Transformed-powered speech generation models can be used in text-to-speech conversion, virtual assistants, and voice cloning. Video and Speech Generation capabilities help generate realistic video content that appears like a human talking on camera.

Data Augmentation

Training data is critical for the best performance of machine learning and the data augmentation process helps generate new and diversified training data. Some Gen AI tools help build and optimize machine learning models.

What is Generative AI (GenAI)?

Beyond the applications mentioned above, Gen AI can be used for composing music, developing video games, and in healthcare, finance processes, and more. In healthcare, GenAI can help generate artificial medical data for training machine learning models, and designing clinical trials. In finance processes, for example, it can be used to develop tools that can read unstructured data from any document and content type and use the data for matching, reconciliation, analytics, and reports. These are a few examples of the vast array of potentials of generative AI, and we can expect more applications to emerge with advancements in technology.

One more tailored to order-to-cash functions for financial leaders and credit professionals dubbed GiaGPT was launched by Emagia on Sept. 6, making it the first on the market worldwide.

Key Use Cases of GenAI

Customer Assistance

Chatbots powered by GenAI-powered tools like ChatGPT are changing the face of customer service, enabling businesses to offer strong support for their end users by engaging with customers and employees, quickly resolving issues, and building loyalty. Used properly, it helps businesses respond to customer reviews quickly, using automatic replies to reviews on websites like Google, and provides fast and efficient help, to enhance the customer experience. Using natural language processing, models like GPT-4 and GiaGPT can search through documents and voluminous data to help the customer support team respond to user questions and provide the necessary information in a time-saving and hassle-free manner.

Assistance for Marketing & Sales

The GenAI tools help marketing teams develop quality content swiftly and more efficiently. Top companies that provide online design and visual communication platforms such as Canva, Adobe, Shutterstock, and Microsoft Designer, have already been offering AI-powered Generative tools for creating and editing graphics and images and creating videos. GPT-4, a more recent entrant in the GenAI arena, enables users on creative jobs that include composing music, creating songs and speech audio, screenplay writing, or learning a user’s writing style. It can also support sales teams in creating personalized emails, generating meeting notes, and predicting risks for key operational processes, helping sales teams save time and improve efficiency.

Automated Coding and Debugging

GenAI-powered tools help developers automatically develop software and debug errors quickly and efficiently to save time and effort. It can write all or parts of the codes and can also help detect and fix errors in code, eliminating the need for time-consuming manual debugging. One of the best examples in this area is Github Copilot, which enables developers to speed up the coding by automating many of the tedious and time-consuming tasks involved in design, testing, and deployment.

Predictive Analytics

Humans are capable of analyzing structured and unstructured data. However, the emergence of pre-trained transformers is freeing humans from tedious tasks like text analysis. This breakthrough technology can help machines process language and reinforce human work in text analysis. For instance, Generative AI can assist in reading remittance documents, emails, and other information to help the AR team in applying cash or in fraud detection by analyzing large volumes of unstructured data such as customer reviews, social media posts, generating charts and reports based on natural language queries, improving their decision-making abilities, and supporting them in a better understanding of complex data among many other uses.

Concluding Note

Artificial intelligence has already revolutionized the way we live and work in recent years, with significant advancements still coming in frequent and rapid fashion. The business world is one area where Generative AI is poised to make a significant impact by transforming the way companies and their operations run.

The emergence of GenAI has transformed the operations of businesses that are looking to leverage its power to achieve enhanced productivity and effectiveness. The forecast that GenAI is expected to achieve a 30% share of the overall AI market by 2025 and $60 billion of the total addressable market is a testimony to the increasing impact of GenAI trends. While many businesses have already started using GenAi tools like ChatGPT-powered chatbots to assist their customers, many others have also begun to try Generative AI to generate ideas, create ad copy, analyze data, or automate time-consuming and tedious tasks themselves.

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