A lot of times we focus on the negatives when it comes to disruptive technologies. But one that I believe to be a positive disruption is Artificial Intelligence.
AI is becoming more prevalent in our lives and I view this as disruptive because it is changing the way we interact with technology.
The finance industry has probably been through the most dramatic transformation in recent years, with the emergence of digital technologies being at the forefront. The world of finance is no longer just about crunching numbers and managing money. It’s a world where customers can now be served at any time and in any location, thanks to AI
The financial industry was one of the early adopters of AI technology. This is because it helps in improving customer service, accelerating transactions, and making accurate predictions. And reducing risks by using chatbots, robotic process automation, and other technologies.
Moreover, the World Economic Forum and Deloitte released a report that found that artificial intelligence is changing the physics of financial services, weakening the bonds that have held the component parts of incumbent financial institutions together and opening the door to entirely new operating models.
In fact, artificial intelligence (AI) has the potential to save the banking industry $447 billion by 2023.
With that, Let’s find out how these technologies are reforming the financial ecosystem.
AI is Reducing Transaction Costs
How can AI be of value to the financial sector? The first place to look is reducing transaction costs, which take two forms: the costs of execution and negotiation.
With respect to the execution, you can use AI in a number of ways. For example, you may potentially automate some transactions without needing human intervention. You can also reduce the cost of negotiation.
For example, if you are trying to buy assets through an auction and need to figure out what your best bid will be in order to get those assets, it’s useful for you to know how much others at the bidding table are willing or able to pay for these assets.
In that case, an AI could help you determine whether it makes sense for you to continue bidding on these assets or not.
Automated Customer Service
AI-powered customer service, or virtual assistants, allows both traditional and FinTech companies to offer better customer service.
They address customers’ needs in a faster and more efficient manner, freeing up human representatives to handle more complex cases.
AI-powered chatbots can handle simple questions and requests around the clock, so customers don’t have to wait for an answer during office hours. They can also be used for simple financial transactions (for example changing your address or making a payment).
So AI is changing finance in many ways. It holds great potential for improving efficiency and reducing costs across the industry.
However, it won’t replace humans or their knowledge any time soon. Instead, it will support employees and allow them to do their jobs better by helping them make smarter and faster decisions with less effort involved.
Risk Assessment and Management
Imagine you’re a finance expert. You’ve spent years studying the stock market and making investments, but you need help assessing the risks that are involved in the process.
This is where AI can help you. It can be used to detect risks in investments and help prevent losses. For example, the data obtained from social media websites such as Twitter can be analyzed to determine the public sentiment on a particular stock or investment through algorithm-based analysis of tweets related to finance topics.
AI is also helping investors get better control over their finances by offering them personalized advice as per their individual needs and risk profiles while they’re investing money in any financial instrument or industry.
The best part about this is that it’s all done at scale so there’s no need for humans to spend hours analyzing data or providing advice for each client individually when companies can simply use AI instead!
Fraud Detection and Prevention
With the increasing threat of cybercrime, AI can be used to help flag suspicious activity and provide cybersecurity. This is done by learning how customers spend their money and using that information to detect patterns.
For example, if a customer doesn’t normally use their credit card in a particular location or at a certain time of day, then AI can identify this as unusual behavior and flag it accordingly. But it doesn’t stop there.
When the data about where people are spending money and when is combined with other factors such as IP addresses and email addresses. And even more accurate picture of fraudulent activity can be presented.
In fact, some financial institutions have reported that they have been able to reduce their fraud rates by up to 50% by implementing an artificial intelligence platform into their existing fraud prevention systems.
Data Security and Encryption
Every day, millions of transactions are made across the internet. Without encryption, these transactions could easily be intercepted and tampered with.
This is another space where AI is heavily used. Encryption is a process by which a piece of data is scrambled. And then decrypted, or unscrambled as necessary.
An AI-powered system can automatically encrypt and decrypt data bits with ease and is also capable of analyzing behaviors that indicate suspicious activity on the network.
In this way, AI helps keep your data safe from hackers who might otherwise exploit vulnerabilities in your system for their own gain.
Trading and Investing
For trading, AI is used for pattern recognition based on historical data to predict stock waves and other financial trends.
Currently, the finance industry uses AI for spotting anomalies in data that are too large for humans to analyze. The ability of AI to process vast amounts of market data has also led to its widespread use in high-frequency trading algorithms.
Quantitative trading is another space where AI is doing wonders. Quantitative, algorithmic, or high-frequency trading, as well as data-driven investment, has recently grown in popularity on the world’s stock exchanges.
Here, Investment firms rely on computing and data science to accurately predict market patterns.
AI can analyze the data to identify potential triggers and prepare for them in the future. AI can also personalize investments for specific investors to assist them in making decisions.
What’s Driving the AI Advancement in Finance Industry
The advancement of AI in financial services has been rapid and will continue to be going forward. This is due to a number of factors.
The Production of Vast Amount of Data (Big Data)
Time has changed, customers today spend a significant amount of time on mobile apps and net banking.
Therefore banks now collect more ‘unstructured data’. This huge amount of data comes from social media, emails, text, images, videos, and other digital channels. And when you have big data to make better decisions — banks are now able to offer personalized services.
Plus, it’s not just about traditional banks collecting Big Data anymore — there are new financial services firms like fintech which are technology companies at their core. And the competitive nature of such organizations makes them early adopters of strategic advantage and AI.
Hence, The amount of data financial services firms have to work with is one of the most important factors driving AI adoption for two reasons.
First, it’s easier to apply machine learning and AI when you have a lot of data. Second, data is the raw material of AI. The more raw material you have, the better your products can be.
The Infrastructure Has Become More Capable
Talking about Big Data, you must also process, interpret, and make decisions based on your data. Otherwise, it’s just raw data about everything.
But it wasn’t that we didn’t have data — it was just that we didn’t have the infrastructure to process it.
We now have extremely fast and powerful computers, as well as software and hardware to support them, and cloud storage to keep the data.
All of this enables rapid processing of large amounts of data at lower costs, as well as scalability efficiency. This means that it’s going to be easier for organizations to take full advantage of Big Data and therefore — leverage AI as well.
The Ever-Growing Competition
FinTech’s (financial technology) revolution is posing a serious challenge to the traditional banking system.
M-Pesa in Africa and UPI in India are gaining new customers on a daily basis, with billions of transactions.
As a result, the battle is no longer just about providing excellent banking services. But also about providing excellent personalized services based on data.
And once again, whoever uses the latest cutting-edge technology to process data — wins. Without a doubt, banks rely heavily on AI to optimize service offerings and provide the best customer experience.
AI has already transformed the finance industry in myriad ways, from fraud detection to stock trading to offering better customer service than a human.
Businesses that incorporate AI into their customer service offerings can save money in three ways: firstly, by hiring fewer human agents; secondly, by increasing the efficiency of their existing human agents (who are now free from mundane tasks); and thirdly, by keeping customers happy with fast response times and efficient problem-solving.
Without hesitation, artificial intelligence (AI) is the future of the finance industry. Because of the speed with which it is taking progressive steps to make financial processes easier for customers. Not to mention, bots are gradually evolving as innovations in the AI sector are made. Firms that see this as a long-term cost-cutting investment are making massive investments