Artificial Intelligence In Banking & Finance

If we look at evolution of modern banking and finance industry,a few milestones have changed the course of banking and finance industry. These milestones were driven by technology. In 1960s the automatic teller machines (ATM) made an appearance and revolutionized the banking industry, as customers no longer had to visit a bank for basic financial transactions. With the rise of the internet boom in 1990s, came electronic fund transfers and internet banking. Soon online banking was officially introduced by mainstream banks. In 2000s, Mobile banking and digital banks gave mileage to the banking and finance industry. In some regions mobile banking became a preferred mode of banking for customers. The ease of carrying your bank in your wallet opened up new avenues for banks. While in other geographies, it served socio economic growth by covering the unbanked population. If all the above milestones are observed well, early adopters saw the potential opportunity, adapted the technologies and reaped the benefit and convenience of it straight away.

Traditional banks excelled by giving customers personalized services. However, today customers do not visit banks unless it becomes a matter of urgent concern. Nor do customers prefer contacting the call centre and being on kept on hold forever. So how does bank develop relation with its digital customer? The answer lies in constantly evolving and offering customer highly personalized, tailored and customized products and services that have been adapted to the current situation.

Today customers demand evolved digital channels. Gone are the days that look and feel of branch mattered for choosing a bank. Now the look and feel of the mobile and digital channels is the deciding factor to choose a bank. Banks have to remain competitive and keep up with rising customer expectations. Digital channels need to be constantly fine-tuned with new technologies to attract and retain customers. Banks are no longer the traditional bearers of financial services, they are now trying to become more agile and fast in connecting with the consumers of financial services. The obvious reason is that fintechs and other non-traditional players in the market have unbundled banking products and services. Not to mention the aggressive use of latest technologies while providing financial services have made nontraditional players popular in the market. Ongoing competitive disruption is continuously forcing banks to reinvent themselves.

Artificial Intelligence (AI) is the next milestone for digital channels. This is understood whether the incumbent is a bank or fintech, AI is the next step. Artificial intelligence always conjures up images of robots working around or is comprehended as something excessively complicated. If we look at the tech industry built on AI models, it’s astounding to see the role played by AI in generating revenue and retaining customers. AI has become a mainstream technology rather than being part of experiments.

Industries worldwide have started utilizing AI. Some regions or banks are already in forefront in AI implementation. While some banks or sectors have still not capitalized, even the digital wave. The book lays out the growth of digital landscape and role of AI in banking and finance industry. Financial sector is now dealing with millennial generation who are used to recommendations from Netflix, Amazon, facebook feeds, and virtual assistants like Alexa or Siri. So, the question is, how does bank sustain in this model and retain the technically smart and upwardly mobile millennial as their customers? The book discusses the expectations of digital millennial in terms of financial services.

Executives across the world are increasingly looking to artificial intelligence to create new sources of business value and revenue streams or cost saving opportunities. This is especially true for leading adopters of AI, those that have invested in AI initiatives and have realized impressive results. AI is a continually evolving technology. The book talks about the business applicability of AI. There are various branches of AI which are trending, the primary focus is Enterprise AI. The approach road to AI is not from an experimentation point of view, “Which AI model to use” rather understanding and implementing “how can banks use AI”.

AI sounds mystifying and what the book does is demystify it. The book takes in depth look at participants of the financial ecosystem who have adopted AI in their daily operations thereby looking at AI through different vision and outlook. Apart from the potential, Enterprise AI model needs to be made more accountable and with clearly defined role of regulators where they need to collaborate to make implementation successful.

There is discussion on the pathway to initiate the AI journey. Some banks are looking at AI to improve processes and cut costs while others to give their customers a unique experience. All this requires a strategic roadmap, rather than an offhand business decision. AI cannot be implemented like the usual technology suites. It requires a completely different approach right from executive level. The book lays out a roadmap for the executives for the AI journey, a top down approach required for successful implementation of AI.

My previous book “Digital the new normal for banks” was written keeping the digital revolution in mind. This book is an update on the latest technologies that have seen incredible growth in past few years. The focus is on insights on AI development driven by data. More often than not machine learning and robotic process automation are often confused with each other. We will look at the clear distinction between machine learning and RPA. The book covers RPA implementation roadmap including questions like should RPA be a stepping stone for intelligent automation.

This book covers data framework, infrastructure needed for AI and also the technology from the “best fit” point of view. The aim is to look at the business requirement, decide the machine learning model rather than just adopting AI, review the role of data warehouse in a data driven organization. How banks can leverage and channel data for AI. Banking industry was known for its legacy systems overloaded with paper trails and manual processes. Banking processes became synonymous with sluggish processes. Technology resolved these major issues of banking industry. At the same time, it has raised the expectations of customers. Decades earlier if your bank issued debit card, it was a big deal. Now receiving ATM or debit card is a matter of fact .Or to put to otherwise it is no big deal now. The customer today is asking their banks, “What’s next”? And if AI is not a part of their journey, do banks need to second guess where the customers will head? AI is the next chapter of digital journey of banks and the journey needs to begin now.