In today’s time of hybrid human-machine processes, we often tend to overlook the machine part, and ignorantly accredit the human interface for all the transformations it has brought to our daily lives. Quite understandably, we humans behave superficially many times. And it is this thing that sets the machine apart from the human in this hybrid ecosystem.
The rapid technological advancement in the Banking Sector is one of the best examples to understand this phenomenon. Have you ever noticed how AI has been catalyzing the continuous evolution of the financial sector in the past 5-8 years? From a manual procedure, we have graduated to an automated world. All these recent advancements in artificial intelligence (AI), especially in machine learning and natural language processing (NLP), have brought automation to a whole range of tasks previously dependent on manual processes, making them highly efficient and effective.
Here are the 3 things that AI is silently transforming in the Banking Sector:
AI-Enabled Round-The-Clock Customer Service
Though interacting with the bank is not an everyday phenomenon, for a customer who has been duped, it is the first and foremost action. Frauds can happen anytime, anywhere. And in that case, a customer would not want to wait for “office hours”. Here comes the AI – the AI-powered Chatbots have already replaced humans as the bank’s first point of contact. Chatbots and equivalent technologies are now smartly handling the entire procedures of a huge number of common inquiries, transactions or complaints on a real-time basis. And, in the majority of such cases, AI-powered bots are almost indistinguishable from human support staff. On top of it, they do not miss dates or ask for holidays either.
Data-Driven Risk Analysis and Investment Decisions
A well-researched data has always been at the base of an insightful decision that a business takes to define its growth. Indeed, data is behind the success of a business. And therefore, companies employ teams of analysts to search, categorize, evaluate data and inculcate meaningful insights and information for the business to grow.
However, this process is challenged when there is a huge pile of data and the system needs to scale up to even categorize it properly. Scalability is a task. Unfortunately, companies that ignore this and rely on their incompetent manual system that through up out-of-date insights fail miserably.
AI offers a sustainable solution to this problem. More specifically, Natural Language Processing (NLP) helps in accurate categorization and then analysis of this huge pile of data in a most organized manner, and almost immediately. This enables analysts to focus on only that data which is meaningful and relevant. NLP in the banking sector is proving a boon to analyzing customers’ behavioral patterns and accordingly planning customized packages for better Return on Investment (ROI).
AI-enabled Automated Fraud Detection System
Since the time financial services first existed, fraud has been its unfortunate part. Customers are often fooled by fraudsters who rob off their money and investments. While such fraudulent activities gained momentum during the initial days of online banking, they have substantially reduced in the last few years. And the credit for this success goes to AI.
Artificial intelligence is a powerful tool for identifying and preventing fraud. These billion numbers of financial transactions that take place daily are an ocean of opportunities for any fraudster. At the same time, these billion numbers of transactions create a pool of data for an AI to sort them categorically and “learn” what a fraudulent activity looks like and use that knowledge to block suspicious transactions. Surprisingly, such decisions by AI are almost 100 per cent accurate in most the cases! AI has started to add significant value to any financial institution that wants to combat fraud and reduce the cost associated to it.
