The Impact of Artificial Intelligence in the Financial Services industry
We have more AI around us than we even know! Start-ups today, have brought in new applications and innovations in every sector. Looking at the investment figures, it says AI can contribute up to $15.7 trillion to the global economy by 2030 – healthcare, automotive & financial services being the top most applied sectors according to a leading research firm.
Given the impact, it’s interesting to study how quickly and aggressively AI has been making its impact on the impervious Financial Services industry felt worldwide. Very recently, China opened the first fully automated, robotized bank in Shanghai.
It was just about a decade ago, when high-speed trading was introduced making the markets more efficient and fast-paced. Today, although the AI technology itself is in a native stage, we can see its application in basic services like scrapping paper work, streamlining operations, customer interaction or even complicated tasks like hedging risks. AI is no doubt helping the financial services industry streamline itself faster and with deep insights, tap into a growing customer market. And by 2020, with 20 times more data being made available than today, AI will no doubt be the most important factor for driving revenue growth and profitability.
So here’s a quick study on some key areas of application that we can see:
Before we proceed, in case you need a definition – Artificial Intelligence is a combination of cognition, manipulation and interaction. Cognition – Ability to perceive, understand, plan and navigate; Manipulation – Precise control and ability to manipulate objects in the given environment & Interaction – The ability to learn from and collaborate with humans. The current capabilities for AI is not limited to but include deep learning, predictive and prescriptive analytics, text mining, natural language generation, machine learning systems, and recommendation engines.
Area 1: Security, risk management and fraud detection
One of the greatest areas of concern in the financial services industry is network security. There have been multiple cases of hacking and data-theft that have occurred in recent times, making it a top priority to be watchful about and take steps to prevent the same.
In order to make sure they reap the best benefits of this technology, some of the biggest banks and financial institutions around the world have started investing in AI- Bank of America Corporation made a bold push into AI technology with the debut of an intelligent virtual assistant named Erica, JP Morgan Chase introduced a Contract Intelligence (COiN) platform designed to analyse legal documents and extract important data points and clauses, HDFC Bank has developed an AI-based chat bot, “Eva” and many more such examples exist in the sector.
AI is already being used to spot abnormal activities and behaviour to detect rogue trading and market abuse, ensure compliance with principles and guidelines and set up accountability in case of fraud detection. Companies are also using AI to utilize its powerful image recognition capabilities. Through image-tech, companies can scan through hundreds of thousands of pages of contracts, documents and data to find the necessary piece of information being sought after. This helps financial firms find lapses in their own systems and create penetration-tested solutions.
AI also enables assessing risk management to also be automated. Human error may create incorrect statistics and trend models, but AI provides a much higher accuracy ratio. Also assessment of credit worthiness, as well as quantifying the risk that an investment carries can be calculated on a real time basis.
Credit card/ fraud detection, anti-money laundering, investigation optimization, transaction surveillance, and regulatory mapping are just a few of the varied applications for the financial services industry.
Area 2: Online communication and chat bots
You can chat with a chat-bot and not realize that you’re communicating with an AI bot. That’s the power of communication in the AI space. With some of the largest AI industry participants investing heavily into chat-bots, the financial services industry has seen long-strides in quality communications. With regards to scale, AI bots can simultaneously communicate with millions of customers at a time, saving cost and resources for these firms.
Financial services companies also have incentives to implement these AI chat bots as communication gets more complex for many service representatives. As language barriers and service wait-times increase, AI offers a more robust and scalable solution in chat-bots.
For example Simple is an AI combined with behavioural economics to understand a user’s individual earning and spending to advise on what is safe to spend before the receipt of the next salary payment. By automating everything it can and going without brick and mortar stores, including providing online customer service that anticipates questions as a user types them into a phone, it has cut its costs and eliminated all fees, even for replacing lost debit cards.
There are implications that go globally, when it comes to AI-based communication. However, in the financial services industry that picture is much clearer with sensitive information being shared over communication. That’s why it is safer to opt for AI-based communication for many of these firms. There is also a data analysis component to these communications, making it easier for customer service managers to review customer satisfaction in real-time.
Area 3: Process efficiencies and data-based decision making
AI has made processes streamlined in the financial services industry. It has created new avenues of growth for financial firms, banking institutions and fund managers by making it much easier to process paperwork, documents, and large quantities of information. Even something as preliminary as hiring the right people, can be optimized via AI’s advanced mapping and process-efficient technologies.
When it comes to processes within customer relations, vendor mapping, and fund transactions, AI can analyse that data and produce good and reliable insights for managers. Through increased process efficiencies, and advanced data management systems, AI aids not only in enabling better decision making but also enabling them to be much faster and in real time. This increase in efficiencies makes it easier for them to manage various portfolios and design new products as well as new features for existing products.
AI is able to run millions of data points through rigorous testing and analyses to find the loopholes in their security systems. It can handle billions of documents within hours, and find patterns, trends and analysis that a human eye may miss. AI can also run simulations to find the best approach and manage the data better on a 99% uptime.
Increasing efficiencies and delayed decision making has allowed many of the top financial services companies to invest in newer technologies and become increasingly competitive. This has opened up the market for top-tiered customer-oriented services and innovation thereby providing greater flexibility in services provided.
Prerna Goel is an Associate Consultant – Strategic Business Research at Altimetrik. Her areas of research interest pan across financial services, automobile and retail industry. She is an MBA graduate and has been into the market research field for last three years. She is an highly energetic and driven personality with a keen aspiration to help businesses transform, both digitally and financially.