How can Gen AI add value in banking and financial services?

What started as the digitalisation of the banking industry has revolutionised the way we experience banking. A far cry from the brick-and-mortar banks that were prevalent just a decade ago, we now have banks that enable online banking services for everything, right from starting an account to transactions to even closing the account. The last few years have seen even more reforms in the services, as AI and ML are being extensively utilised for providing instant and accurate updates about bank accounts. While AI has ensured that operational efficiency is better and fraud detection is better, it has also led to an improved customer experience.

However, Generative AI has become a game changer for the entire industry. While many understand that Generative AI allows users to easily create new content from a variety of inputs, these models can accept and output text, photos, sounds, animation, 3D models, and other sorts of data. Innovative thinking has ensured that generative AI can be used in creative ways to provide solutions that were unthinkable previously. Financial organisations use this technology to create credit risk reports and extract client information from credit memoranda. Gen AI may produce code to source and analyse credit data in order to acquire insight into customers' risk profiles and estimate default and loss probabilities using models.

But this is not all. General-purpose semantic and natural language applications, as well as generally applicable predictive analytics, are some of the most common AI use cases in the banking business. Generative AI uses neural networks and natural language processing to perform tasks like language generation and predictive analytics. Thus, Gen AI like ChatGPT can help banks extensively in providing 24x7 customer support. Earlier, banks relied on humans to communicate with customers and resolve their problems by helping them troubleshoot whatever issue they might be facing. However, they had their own limitations, as humans can only interact during limited hours and can face language and accent barriers. Chatbots that can handle queries around the clock, offer personalised advice, and even communicate in multiple languages are the new norm.

Apart from this, Gen AI can help in fraud detection and prevention through real-time monitoring, identifying fraud, and ultimately closing the loopholes and enhancing security. This helps in risk management too, as credit scoring, portfolio management, and scenario analysis can also be done in no time at all. By providing a personalised banking experience, banks can now create tailored financial products, automated planning, and improved user interfaces to ensure smooth functioning for consumers. With new-age Robo-advisors, investment advisory, including market analysis and wealth management, has become easier. Similar is the case with regulatory compliance, as automating compliance, monitoring regulations, and reducing errors have become the new norm. Likewise, loan processing and underwriting have also happened due to streamlining applications, assessing creditworthiness, and speeding approvals due to AI.

With such uses, there are many benefits to the banking industry, and these very reasons have ensured that banks adapt to such technology rapidly. It has led to increased efficiency and productivity. AI has also led to cost savings through automation. Lately, enhanced customer satisfaction is being seen, primarily because of higher accuracy and fewer errors. It goes without saying that better data-driven decision-making ensures that you are not blindly relying on somebody but making an informed decision. However, extensive use of Gen AI also brings with it multiple issues, the biggest one being concerns about data privacy and security. As banks share sensitive customer information, there is always a risk of hacking this data. This further raises doubt about ethical issues in AI. Thus, there is a need for high-quality data and to integrate Gen AI with existing systems. Maintaining customer trust is always of utmost importance, something that cannot be compromised.

With advancements in AI technology, we can expect all the above-mentioned problems to be resolved soon. Broader AI adoption is expected in the future, and we can, of course, expect new AI-driven financial products. With a continued focus on AI ethics and governance, the banking industry will be able to weed out the teething issues that are being faced nowadays. And of course, the future of Gen AI does look promising, as it is already helping consumers in innovative ways, and is expected to get better.

Karunya Sampath

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Karunya Sampath is Co-founder & CEO of Payoda Technologies.