Generative AI is widely deployed across multiple industries. However, implementation has been relatively slow for financial institutions due to regulatory challenges and concerns. “For financial service providers, the risks and biases associated with Large Language Models (LLMs) are even more important.
“As a regulated entity, we operate under various restrictions, particularly with respect to privacy. To ensure the security and accuracy of the information we share, we adhere to strict data and consent frameworks. We don’t want to misinform you, so we are actively exploring how we can benefit from generative models within our framework. By the way,” said Deepak Sharma, President and Chief Digital Officer of Kotak Mahindra Bank. target.
Kotak Mahindra is looking at all options, from OpenAI powered GPT models to all available open source LLMs. “With the advent of Azure and other cloud platforms, we have seen a new wave of players actively seeking ways to leverage their own training datasets, enrich them with LLM capabilities, and deploy generative AI models within their enclosed environment. A wave was born, which is closely aligned with our current goals and we are keen to leverage progress like this to effectively reach our goals.”
Sharma believes generative AI has immense potential in areas as diverse as contact centers, code generation, conversation models, predictive modeling, and graphic visual design. “These are specific areas where we are exploring the application of generative AI, rather than just thinking of it as an extension of existing AI capabilities,” he said.
Employment impact
As is often the case with the advent of new technologies, the introduction of generative AI has sparked debate about potential job losses. Similar concerns were raised when ATMs were first introduced, and the potential impact on bank teller jobs was widely discussed. “I think we’ve always seen certain jobs disappear and new sets of jobs created whenever technology changes.
“It is only natural that certain jobs will be phased out in any transforming industry. A similar scenario can be expected with the integration of generative AI. It’s important to note that new and valuable skill sets often emerge as well.”
As environments evolve, workers must improve their skills and repurpose themselves. “In today’s knowledge economy, factors such as hyper-automation are driving this evolution across multiple sectors. played an important role in creating
“So, in my view, generative AI will make humans much more efficient and productive. , contact center agents will be able to interact with customers much more efficiently,” Sharma concluded.
Banks and AI
Today, banks are technology companies, albeit long banks. Over the last few years, Indian banks have invested heavily in technologies such as AI/ML to improve various aspects of banking operations, from customer service to underwriting, risk management and fraud detection. I was. “In 2019, we were the first bank in India to build an AI-powered voice-based interface for our contact center,” Sharma said.
He believes AI will revolutionize every aspect of how financial institutions operate. This has far-reaching implications and is expected to affect all technologies currently in use within banks. AI permeates many areas and processes within the banking industry, bringing about transformational change.
It was in 2016-2017 that Kotak Mahindra Bank shifted its focus to AI. Sharma said some of his early AI models deployed by banks were to target customers based on their propensity, allowing banks to deliver personalized offers and find the next best fit for each individual. I made it clear that I was able to decide on the offer.
“We have also integrated these models into our credit decision process. Fortunately, banks have a wealth of historical data available for training these models, so we have a robust real-time credit decision engine. Over the past six to seven years, AI and ML applications have become more diverse and sophisticated as use cases have expanded.”
Furthermore, Sharma emphasizes that the best use of AI at Kotak Mahindra is in building and enhancing credit and risk models. In addition, Kotak Mahindra also deployed AI solutions to combat fraud, enhance risk management practices and strengthen security measures.
