How the Banking Industry Benefits from AI
Let's take a look at Artificial Intelligence and Machine Learning in the banking industry, as well as AI vs. ML.
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The AI vs. ML Dilemma
Machine Learning and Artificial Intelligence are two terms that are used interchangeably all the time. So, are AI and ML the same? Most definitely not!
Any technology that makes a system exhibit human-like intelligence is AI. Machine Learning is actually one type of AI. Machine Learning makes decisions by relying on the use of mathematical models that are trained on data. ML models are capable of making better decisions when more data is available.
Machine Learning algorithms, believe it or not, are seen on a daily basis. Recommendation engines on websites like Amazon, sounds familiar, yes? These recommendation engines are all ML-powered. Machine Learning is based on what you call "Neural Networks." Neural Networks are built with the objective of training and learning. Neural networks depend on factors of importance that impact the likely outcome of a situation and they are programmed by humans. Usually, a Neural Network is perfected and the machine will learn how to adjust the factors of importance on its own. Once the machine is trained, it will produce extremely accurate results in real-time. Machine learning, in fact, does not possess any real intelligence but is a trained model.
Artificial Intelligence is the stage where machine learning can reflect and interact with humans in a convincing way and makes decisions by itself. Here’s a curveball: “AI cannot exist without ML, but ML can exist without AI.” Give it a little thought and it will definitely make sense to you. When a machine takes a decision, AI is born, meaning it has gone beyond Machine Learning.
The AI Infiltration
When we talk about the banking industry, there are loads of new technologies that are making waves. These technologies are disrupting the banking industry as we know it. Data science, cloud computing, biometrics, and blockchain are a few of the technologies that are taking this industry by storm. However, these technologies are beginning to catch fire only now. Artificial Intelligence, on the other hand, has had a profound impact on the world of banking and how it functions. The ability of a machine to replicate human efforts and evolve without requiring any human intervention whatsoever is an advancement that the banking industry desperately needed. AI is definitely the future and with respect to the banking industry, it is safe to say that the "Future is Now!"
Let’s see how AI is shaping the world of banking today:
- Algorithmic Trading: Plenty of hedge funds today make use of sophisticated systems to deploy artificial intelligence models. These models learn by obtaining inputs from various sources of fluctuation in financial markets and sentiments about the entity to make decisions regarding investment on the fly. Automated AI systems are responsible for nearly 70% of the trading today. High-Frequency Trades are made as soon as a trading opportunity is identified based on the inputs obtained by the AI models. Different strategies are followed by different hedge funds to make trades like these. The AI model deployed must be extremely accurate in order to base your trades on the inputs from thee models.
- Detecting AML patterns: AML stands for Anti Money Laundering. AML is a set of laws, regulations, and procedures designed with the intent of stopping money laundering. Money laundering is the generation of income via illegal means. The act of money laundering is where a money launderer covers their tracks to make it seem like the illegal earnings have come in legally. Watching ‘The Wolf of Wallstreet’ will give you a better idea about money laundering. The major banks are moving from rule-based software systems to AI-based systems. AI-based systems are a lot more robust and are the most intelligent at detecting money laundering patterns.
- Fraud Detection: The area in banking where AI made its debut and had a phenomenal impact is in fraud detection. AI systems have excelled the most in the field of fraud detection. The FICO Falcon Fraud Management Solution is the earliest and best example where a software made use of artificial intelligence to combat the problem of transactional fraud and security threats. The AI models learn through tons of transactional data and discover unorthodox or fraudulent trends and activities.
- Chatbots: Chatbots are automated chat systems that are AI based. Chatbots simulate human interaction and work with zero human intervention. How a chatbot works is it identifies the emotions and context in the text and sends out what would be the most appropriate reply. Chatbots learn and evolve all the time. Chatbots are extensively used by banks with the aim of improving customer relationships at a personal level. Bank of America has their own financial digital assistant known as "Erica" which is AI-powered.
These are a few of the ways in which Artificial Intelligence is shaping the world of banking today. There are various live examples of Artificial Intelligence that you see today. Faster decision making, increase in revenues, better customer relationships, faster and efficient processes are all possible only with the advent of AI in the banking industry.
Make Use of the Best
We made it clear at the beginning of this article that Artificial Intelligence cannot exist without Machine Learning. Here, I am going to list the top ML/AI platforms in 2018 that you can put to use to provide the best banking services:
- Microsoft Azure Machine Learning
- Google Cloud Prediction API
- Infosys NIA
- Wipro Holmes
- Vital A.I
This list is not exhaustive, but the list sure does encompass the best tools in the market today.
Thank you, and let me know your thoughts in the comments.
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