Following the launch of Chat GPT, GenAI has captured all the focus, making us often forget its traditional sibling. Let’s take a look at how they compare and differ using financial services’ use cases. Artificial intelligence existed long before GenAI. Known under the term Predictive AI, it is all about predicting outcomes, future developments, and forecasting trends.
Predictive AI, also known as predictive analytics, is a subset of AI technology that focuses on using historical data and machine learning algorithms to analyze patterns and make predictions about future events or trends. This type of AI technology aims to help companies and individuals make informed decisions by forecasting likely outcomes based on available data.
Predictive AI is focused on training machine learning algorithms on historical data to identify patterns, relationships, and trends. These models use the insights gained from the training data to make predictions about future occurrences.
Generative AI refers to a type of artificial intelligence that involves training models to create original content. These models learn patterns from existing data and generate new data based on those patterns. In the context of images, text, or even music, generative AI tools produce outputs that are not directly copied from the training data but rather are unique creations inspired by the patterns it has learned.
Generative AI models, such as Generative Adversarial Networks (GANs) and autoregressive models, work by learning the statistical patterns present in a dataset. GANs consist of a generator and a discriminator that compete against each other to create authentic-looking content. Autoregressive models generate content step by step, conditioning each step on the previous ones.
While predictive AI and generative AI serve distinct purposes, their comparative strengths and limitations merit consideration for financial institutions:
The use of predictive AI in financial services is well-established, and its combination with generative AI holds promise for driving innovation and enhancing customer experiences. However, addressing challenges such as data availability, integration, and workforce upskilling is crucial for realizing the full potential of AI in transforming the financial sector.
What are your thoughts on the future of predictive AI and generative AI in financial services? Share your insights and experiences in the comments section below and join the conversation!