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Decades ago, AI was something that not only was misunderstood, but it was feared. We’ve seen the rise of blockbuster franchises such as the Terminator or more recently Black Mirror. All of these had one thing in common: they did not understand AI. 

Now decades later, AI has become man’s best friend. Artificial Intelligence is no longer a fantasy genre, it is now a reality. 

Not only has the scope of AI grown exponentially over the past few years, but it has become an essential tool of any business to thrive. Every sector is now adopting AI and the results are astounding whoever metric you look at. From cutting costs to saving time and improving accuracy, AI has revolutionized the game.

AI in Finance

One such sector where AI has become essential, is the finance sector. It makes the most sense that AI would be the jackpot in finance. After all, in Wall Street, money never sleeps, and AI is the only tool capable of working around the clock without needing a little shut eye or a little extra boost to push through the day. 

In fact, 85% of financial service providers are currently using AI. According to Forbes, 70% of financial firms are using Machine Learning to predict cash flow events, adjust credit scores, and detect fraud.

Now there is big money in AI. By 2030, the adoption of AI in financial services is expected to add $1.2 trillion in value, according to McKinsey & Company. Not only is AI making money, but it is also saving money. In fact, in 2023, Artificial Intelligence applications saved banks and financial institutions $447 billion.

Now from a business perspective, it makes perfect sense for every business owner to adopt AI. Not only will it transform your business, but it will also make your employees’ life much easier, and they will definitely thank you for it.

However, most people are overwhelmed by AI as they just do not understand it. Most companies that are looking to adopt AI, they don’t even know where to begin. It is difficult to navigate the vast network of Artificial Intelligence when you have no prior knowledge and don’t know what you’re talking about. It is even harder to find the right talent suited for your business needs. You can spend a lot of time, money, and resources trying to find a talent and in the end find out that they were not suited for what you need. That’s why you need the correct consultancy to guide you and make sure you get the most out of your time and money.

AI in Finance Use Cases Adoption Rates

                                                                             according to University of Cambridge

How It Works

The most important thing that you need to learn first before venturing into AI, is finding out exactly what branch of AI you need. You see, AI is not just one thing you throw into a business and ask it to take over. AI is just like any other software you optimize. You code it, build it, and train it to perform something specific that you need.

AI has different functions that differ from one another. The most common use is Machine Learning Algorithms (MLA). Machine learning is when you teach it just like you would teach a human by giving it algorithms and having the AI learn just as a real person would. 

Computer Vision (CV) is the next function that implements biometrics and other technologies to read from a real image or real text and translate it into information, just like a human with eyes would take in visual information.

The most common function is the use of chatbots. Exactly how it sounds, chatbots incorporate intelligent solutions and voice assistants to automate fundamental customer service tasks. 

You would be amazed to find out just how many big corporations have adopted AI into their business. It is not just a tool to assist in some of those companies, but some departments have fully adopted it. In fact, Morgan Stanley reported that through the first half of this year, 98% of financial advisor teams have adopted an AI assistant that they developed for the company. This assistant gives company investment advisors fast access to Morgan Stanley’s entire inventory of investment-based intellectual capital.

But that is not the only use case of AI in the world of finance. AI pretty much covers all the essential departments in the world of finance, you just need to know how to properly utilize it and trust in the right experts to help you adopt it.

AI Use Cases

Fraud Detection

In the world of finance, you are constantly dealing with sensitive information and huge amounts of money. Naturally, security is a top priority. As online hackers and scammers are always fishing around the internet, constantly updating their tactics and methods of stealing your money or information, traditional security measures may sometimes become obsolete. That’s why AI has been introduced to the mix. With AI overlooking your fraud prevention systems, it is a foolproof security system that is almost impossible to bypass.

It is no surprise that AI is used by JPMorgan Chase to identify fraud in the credit card business. The bank created an algorithm that studies each user’s spending habit and spots patterns that deviate.

To put it simply, AI operates non-stop by analyzing patterns and behaviors to detect anomalies. It implements machine learning algorithms to detect potential fraud. The system is fairly simple and runs through specific steps to ensure the safety of your business and network.

Data Collection

The first step is Data Collection, which means that the AI system just studies large amounts of transactional data and sets it as the normal parameter. For example, if your company has been transferring money regularly on a consistent basis, it will study that and set it as the default setting with the usual amounts.

Feature Engineering

The next step is Feature Engineering. AI will identify any possible deviations, such as irregular large transfers or incorrect or inconsistent numbers that might arise. After that it will apply Model Training, which uses data to train the machine to recognize fraud patterns. 

Anomaly Detection

Anomaly Detection comes next, which AI uses statistics and algorithms to identify outliers and actual deviations in the system. Anything out of the ordinary from the regular pattern will be detected, no matter how big or how small. 

Continuous Learning

After it detects potential fraud cases, it goes through Continuous Learning, which constantly updates the model and evolves it, ensuring that the system is always evolving to deal with the never ending fraud tactics.

When the system detects any suspicious activity, it flags and provides detailed reports to the supervisors. The systems are put on hold and it can even block off any transactions from happening, even if the staff has approved it. It takes into account that the human eye can miss details and can even be duped, so it ensures the maximum safety possible and just takes matters into its own hands, becoming the most reliable right hand artificial man a CEO can ever ask for.

Now when you think about finance, you naturally think of trading. Usually, the biggest issue when it comes to trading is getting market analysis too late or after the trend has passed. You end up missing out on valuable opportunities just because you failed to recognize it in time. Well, with AI, you can now predict trends before they even start. You can get ahead of highs and lows and act accordingly, always staying one step ahead in the market.

AI Finance tools outperform human trades and bring instant analysis and decisions with much more accurate predictions. Nowadays, a lot of well-known hedge funds use AI for these purposes. The technology is quite popular for data science as it helps a company build its trading system.

AI systems can continuously monitor portfolios, analyze real-time data and generate alerts about potential risks such as market volatility or asset correlation changes. Additionally, AI systems can not only process historical data, but also use machine learning models to predict future risk factors, such as price fluctuations or credit risks, and suggest adjustments to the portfolio to mitigate potential losses. Talk about a cheat code in your trading portfolio. Now imagine when investment firms can use this power of AI with millions behind them to invest. It is no wonder why this industry is booming under the advancements of AI.

Risk Management

Usually, when financial service companies lend users money or invest into projects, a lot of study is put into the decision-making process. There is a lot of risk involved, and that's why there is an entire department of risk management

Artificial intelligence in financial services makes a huge difference in investment management and risk analysis. AI factors in multiple aspects to determine whether a person or an entity is reliable or not. Transaction history, credit score and history, income growth, and market conditions are taken into consideration as well as other things to create predictive analytics, ultimately predicting behavior and micro activities to determine if investments should occur.

Lenders can now make more informed decisions, improve risk management, and offer competitive interest rates to those the AI deems worthy. AI in banking also offers real-time monitoring of credit risk, continuously analyzing data and market conditions to provide early warnings regarding a deteriorating credit score.

AI in finance Use cases in risk management adoption rates

according to University of Cambridge

Customer Service (Chatbots)

One use case that might fly under the radar is the use of customer service chatbots. You might even be using it without realizing as you are chatting with a chat account while using a service. Customers like to stay in touch with their bank accounts 24/7, AI can make this possible through AI Finance Technologies by running chatbots. AI Banking services simulate real conversations, Chatbots use the natural language and terminology to answer customer inquiries and assist them in real time in an instance. Say goodbye to customer call centers, incompetent call center agents, waiting rooms, and inaccurate feedback.

Robo-Advisory

There is a rising use case today that is being used by more and more businesses. The use of robo-advisory has been gaining traction and showing impressive results. The considerable interest in passive investment makes fintech companies invest in AI solutions. Robo-advisory is based on providing recommendations based on investors’ individual goals and risk preferences. Finance AI automates the investment process so that the only thing investors need to do is deposit money into an account. The most significant benefit of using this tool is offering the ability for people not familiar with finance to make investments. You don’t need to do financial analysis to succeed in passive investment! And it is also cheaper for financial institutions to have robo-advisory than human asset managers.

You might ask what’s the difference between robo-advisory and trading algorithms. Well, it is a little similar since both are involved in trading. However, the difference between them simply is that robo-advisory is long-term investment while trading algorithms are short-term, or fast trading decisions.

Regulations & Compliance

As we live in a dynamic world, everything is always changing and on the move. Even the laws and regulations are always changing, even if it is one small deviation in a random law. This small deviation can land your business in a world of trouble. Corporations have established an entire department dedicated to regulations and compliance. Financial companies have to comply with tons of laws and regulations that are hard to keep track of. Reports are extremely time-consuming and one tiny detail missed may lead to minor complications or even huge issues with the law. AI has all the laws and regulations stored away and memorized. It will detect deviations, analyze data, and follow the rules and regulations accurately. Thanks to the complete automation of the processes, it is possible to avoid issues with the help of AI.

Process Automation

Speaking of automation, we arrive at the final notable AI use case which is process automation. There are always time-consuming tasks that are usually done manually by employees. For example, preparing documents for clients or accessing information. These tasks are what is commonly referred to as “donkey work”. In fact, this kind of work was the very first reason why LyRise was started in the first place, to eliminate all the time wasted doing grunt work and free more time for more analysis and more strategic tasks.

AI can do all of that in a few minutes. It can also verify personal IDs and make sure that it is not being used for fraud. This is an example of the Computer Vision function. Another example of that is a bank acquiring a new client and processing their information to enroll them in the system. AI can be used to automate financial and Compliance Regulatory reporting, using Natural Language Generation (NLG) to compose full-text reports with little or no human input. According to Cambridge University, 55% of all leaders are utilizing AI to automate compliance. 

AI Use Case in Finance, Automation & Process re-engineering adoption rates

according to University of Cambridge

Benefits of AI in Finance

Aside from the use cases, AI offers so much more to a business than just specific use cases. AI does not need rest time and does not suffer from fatigue. It can process thousands of transactions per second with a consistent and incredibly high accuracy rate.

As mentioned before when it comes to fraud detection, any fraudulent activity will be detected accurately to the highest level possible, while legitimate transactions will go through smoothly without someone stalling them. AI also works in real time, meaning anything suspicious will be detected the moment it happens. It can also be fine-tuned for a specific target approach when it comes to fraud prevention. AI can detect and prevent payment fraud, chargebacks, account takeovers, fake account creation, content scams, and return fraud. Chargebacks alone were estimated to have cost businesses $100 billion in 2023. Additionally, a report from 2022 suggests that organizations lose out on 5% of its yearly revenue due to fraudulent activities.

The uses are not limited to just those mentioned. AI can also be customized to meet your specific business needs and it can cover every single scope, regardless of your business size or budget. Custom AI solutions have a large range between $6000-$300,000, while third-party AI software comes in at only $40,000 per year. Finally, AI consulting services cost around $200-$350 per hour.

Challenges of AI in Finance

Now AI is not all sunshine and rainbows. There are a few setbacks when it comes to using it, as with any other product or service. One of the challenges is that if you have incomplete or outdated data, this will hinder the AI’s ability to function properly. Also, if your data is incomplete, AI may give inaccurate analysis or projections. AI may start to Hallucinate, which is a common term for when AI starts making things up.

Even when things are running smoothly, AI does need ongoing training of the latest data on fraud activities, detection, and general uses. It will also need constant updates to reduce the occurrence of false positives and maintain customer satisfaction.

As with anything else when it comes to money and numbers, security is always a risk. With AI, it has access to all of a company’s data as well as personal information of customers and clients. Security is always the biggest concern when it comes to AI. Don’t worry, AI is not going to take over your company and kick you out like the Terminator. The issue, however, is information leaks. Sensitive information from banks, firms, etc can be shared with risky third-party AI models.

There is also another issue that is referred to as “Black Box AI”. Black Box AI is when an AI system is not transparent or clear in its function. It does not provide its input and operations to the users and other parties involved. Black Box AI makes decisions and conclusions without providing explanations to how they made that decision. Accuracy validation is also an issue since it is hard to trust information when you don’t know where it came from. AI is also known to sometimes be biased and may give incorrect results sometimes if it is not properly trained.

AI Finance Case studies

The benefits of AI are not something that we predict or foresee coming in the future, but it is something that can already be measured and proven today. LyRise alone has a large track record of successful AI uses and helping out multiple businesses adopt AI and apply it to their systems. From successfully predicting and increasing ROI, to cutting talent acquisition costs and improving AI models. 

Whether it is in the hospitality industry, tech industry, or financial industry, AI has already proven itself to be a game changer. You can read about multiple case studies where AI helped businesses overcome huge obstacles in ways that no human would have ever done. 

This can be your business as well, it is all within the click of a button

Adopting AI

If we can throw in a word of advice to any businesses or entrepreneurs and leave you with something, you should invest in AI training for your employees. Train your staff in the future of the business world. You should also develop a clear AI strategy for your organization right now. It is never too late to catch up with the AI storm that has taken over the world. Partner with AI vendors to get the most out of AI technology if you are not familiar with it and have no relevant experience using it. Use AI to improve customer service, detect fraud, personalize financial products and services, manage risk, and automate marketing tasks. The possibilities are just endless.

You will save so much time and money, become more efficient than ever, and you will thank the day that you decided to adopt AI into your business. Join the ship as it is sailing and take part in the AI revolution that has already happened. Lead the charge and harvest the fruits of the AI labor.

They said AI is the future. That statement is no longer true, because AI is the present. The gift that keeps on giving.

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