Artificial Intelligence (AI) has truly revolutionised the finance industry and it is one of the industries likely to adopt new forms of AI technology faster than others. Today, AI encompasses everything from simple AI tools like chatbots or digital assistants to fraud detection and automation.
The financial institutions continue to see huge benefits in the use of artificial intelligence for a number of services. With technological advancements happening in AI, machine learning, natural language processing (NLP), and computer vision, financial institutions are only likely to invest more in AI tools and services.
In today’s finance industry, AI is being used to increase user acceptance and navigate shifting regulatory frameworks. AI is also being used to streamline tedious processes, automate repetitive tasks, and often to improve the customer experience. With that in mind, let us now look at some of the most common applications of AI in the field of finance.
Artificial Intelligence is making it possible for banks and other financial institutions to assess risk. This means that AI is being used to determine whether someone is eligible for a loan. There are now machine learning algorithms to determine a person’s eligibility for a loan and the same algorithm is, at times, used to offer personalised options too. With AI, loan disbursement is becoming faster and more accurate for financial institutions.
It is one thing to assess risk and another to manage that risk. With the help of machine learning and vast amounts of data, algorithms are being used to analyse the history of risk cases and even identify early signs of potential future cases. AI can be used to analyse real-time activities in any given market or environment. This allows financial institutions to mitigate risk and better plan for the future.
Fraud Detection and Prevention
AI is now being used to prevent credit card fraud, which has grown in recent years. With consumers using credit cards to make purchases online, they are also becoming victims of credit card fraud. With AI, credit card issuers, as well as financial institutions, are using fraud detection systems to analyse the behaviour of their clients, locations, and buying habits.
These systems are capable of triggering a security mechanism when something seems out of ordinary or contradicts a user’s traditional spending pattern. Machines are not only capable of recognising suspicious activity but also preventing financial crimes like money laundering that have plagued the industry for several years.
One of the factors used by financial institutions before assessing a potential borrower is the credit score. While there are credit score providers out there, AI can predict the credit score of a borrower using several complex and sophisticated rules compared to those used in traditional credit scoring systems.
An AI-powered credit scoring system will thus be more accurate in classifying between a high default risk applicant and those who are creditworthy but lack an extensive credit history. There is also a possibility of AI being unbiased when offering credit scores to a person. Digital banks and other fintech services rely entirely on AI and machine learning algorithms to evaluate loan eligibility and offer personalised options.
Improved customer service
In this new hyper-connected world, financial institutions are also highly connected. This is possible with the help of artificial intelligence, virtual assistants, and chatbots. Customers can now ask questions at any time during the day and get their queries answered. This is also a prime example of automation at work in finance.
A lot of the time, the questions asked by customers are simple and can be answered by AI assistants like chatbots. Hence, AI is being deployed to answer simple and most repeated questions while questions requiring in-depth answers are handled by a human agent. This allows financial institutions to offer a continuous, available at any time service to their customers, which drives satisfaction and adoption.
We all know how good AI is at automating a number of mundane, time consuming tasks that would take thousands of work hours for humans to process. An AI-enabled software is able to verify data and generate reports faster, review documents, and even extract information from them. With robotic process automation, financial institutions are able to automate high-frequency repetitive tasks.
This helps with eliminating human error and refocus efforts of their workforce on processes that require human involvement. According to Ernst and Young, there has been a reported 50 to 70 per cent cost reduction due to these activities.
Artificial Intelligence is also being used to offer financial advice. An AI program can analyse a person’s portfolio and match it with their risk appetite to offer them insights on financial tools. An AI program can also do this faster than humans allowing them to make decisions faster.
AI is driving the new form of trading also called algorithmic, quantitative or high-frequency trading. This form of trading has been growing rapidly since 2018 and this is because of the benefits offered by artificial intelligence. An AI system is able to monitor both structured as well as unstructured data and process it in a fraction of the time needed by humans.
By processing the data faster, AI is able to make faster decisions, which results in faster trading actions or transactions. AI is also able to make accurate predictions about stock performance and even offers some of the strongest recommendations for portfolios.
The growing impact of AI in finance can also be felt in personalised banking which is changing how financial institutions offer additional benefits and services to individual users. This personalised banking goes beyond smart chatbots that already take care of a large set of services being offered to consumers.
With personalised banking, financial institutions are mostly looking at offering personalised financial advice and helping individuals achieve their financial goals. This is done using machine learning and recommendation algorithms wherein the system tracks income, recurring expenses, spending habits, and offers an optimised spending plan and other financial tips.
One of the areas where AI makes its impact felt almost immediately is in the field of cybersecurity. With artificial intelligence, even financial institutions are becoming extremely adept at tackling cybersecurity frauds. One of the key themes being the ability to become proactive and not reactive to the situation.
With cybersecurity and the use of AI, financial institutions can eliminate up to 95 per cent of breaches caused by human error. AI is also being used to boost security by analysing and determining normal data patterns and trends. Lastly, they are becoming central to alerting about unusual activities on the network.