How AI Is the Next Step In the Digitization Of the Finance Sector

With the rapid advancement of technology, human lives have undergone a phenomenal change. By leveraging a slew of revolutionary next-gen technologies such as AI, ML, and Big Data, we are venturing into a new age of innovation wherein Industries across the spectrum are automating manual processes. This has helped in making our lives easier and seamless to a significant extent. The financial industry has also embraced this widespread digitization. Artificial intelligence has emerged as the flagbearer of this contemporary digital transformation. As per a report by Mckinsey Global Institute, it has been estimated that utilizing AI to enhance core banking functions and provide customized services to customers across the globe will extend a value of over $250 million across the industry.

A plethora of new-age tools such as voice assistants, chatbots, process automation, and predictive analytics are redefining financial services as we speak. And this is merely the start. As we move to the next frontier of technological discovery and R&D, let us delve into the role of AI in disrupting the financial sector, its impact on businesses, and how it unravels a new vista of unique opportunities.

The financial industry is waking up to the tremendous transformative potential of AI. Industry experts believe that leveraging AI will help the banking industry save a whopping $1 trillion come 2030. Another report by Narrative Science in 2018 revealed that over 32 per cent of banks out of the total surveyed had already adopted advanced AI-based techniques such as predictive analytics, recommendation engines, voice recognition, and response times in their operations.

This novel wave of innovation focuses on enhancing customer experience. Conversational AI, such as chatbots, is also becoming a popular must-have for brands at the front end. Process and task automation and algorithmic analytics fortify and elevate finance at the back end. Robots have increasingly started replacing employees. As reported by Gartner, Robotic Process Automation (RPA) is highly cost-effective, amounting to one-third of the compensation provided to an offshore employee and one-fifth of that given to an onshore employee. RPA does the grunt work, a rule-based system that automates repetitive tasks and has no intelligence but is often categorized under AI.

AI in finance is dominated by machine learning, but automation also plays a significant role in banks. The financial sector has significantly benefited from machine learning; banks can collate and analyze vast amounts of data in finance. Machine learning is a subdivision of AI, which allows machines to learn and evolve using data without depending on human intervention.

Voice recognition is another new-age innovative capability that uses AI to conduct banking operations through voice commands. At the heart of this innovation lies Natural Language Processing (NLP). This AI-powered technology is used to develop numerous virtual assistants (augmented agents) and chatbots such as Capital One’s Eno.

In the financial sphere, leveraging AI offers two distinct advantages: one, a sharp increase in efficiency, and two, fewer loopholes that can be exploited for fraud. This trend of AI-driven lending initially manifested—like so many others—among the tech startups of Silicon Valley, but Wall Street and various Indian entities have rapidly adopted it. Since market investment is generally dominated by individual fund managers empowered by a mandate of popularity, it might be hard to imagine their influence supplanted by AI. However, AI-driven beta funds can significantly reduce the chance of human error through their constantly evolving rules and algorithms.

Other significant factors behind the increasing demand for AI in finance include the proliferation of cheap and efficient computing resources, the corresponding digitization of financial services, and the explosion of available data on individuals and organizations.

The newfound permeation of advanced tech paradigms such as Artificial Intelligence has taken the financial industry by storm. With a plethora of next-gen tech applications and use cases disrupting the industry, technologies like AI and ML have enormous potential to transform the sector for the better. Unsurprisingly, countless investment banks and financial startups utilize the best AI to boost profits, maximize efficiency, reduce errors and yield the highest possible returns.

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