If there’s one industry where the introduction of Artificial Intelligence is paying the biggest dividends, it is in finance. AI in finance has given the world of banking and the financial industry as a whole a way to meet the demands of customers who want smarter, more convenient, safer ways to access, spend, save and invest their money. AI is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management.
The applications of Artificial Intelligence to the financial realm can be summarized as follows;
Credit Decisions The biggest application of Artificial Intelligence in the banking sector is as regards loans. We live in a society where a premium is placed on the availability of credit not only because we generally prefer paying with a credit or debit card, but also because so many of life’s important necessities hinge on credit history. As such, the approval process for loans and cards is more important than ever. The traditional loan approval process in terms of who gets credits and on what term is riddled with biases against protected characteristics, such as race, gender, and sexual orientation. In this context, relying on algorithms to make credit decisions instead of deferring to human judgement is an obvious fix. What machines lack in warmth, they surely make up for in objectivity. What we will see more in 2022 will be artificial intelligence solutions that help banks and credit lenders make smarter underwriting decisions by utilizing a variety of factors that would help make the bank loan approval system fairer.
Managing Risks The deadly nature of risk needs no further introduction. The importance of accurate forecasts to both the speed and protection of many businesses cannot be over-emphasized. 2020, by virtue of the pandemic saw financial markets turn more and more to machine learning, a subset of artificial intelligence to create more exacting models. These predictions help financial experts utilize existing data to pinpoint trends, identify risks, conserve manpower and ensure better information for future planning. Taking Kensho Technologies, a fintech company based in Harvard Square and New York City for instance. Their software which uses a combination of cloud computing and Natural Language Processing (NLP) is able to provide machine intelligence and data analytics to leading financial institutions like J.P. Morgan, Morgan Stanley and Bank of America.
Quantitative Trading If I was to define quantitative trading, I would say it is the process of using large data sets to identify patterns that can be used to make strategic trades. I mean, that does not sound very different from what Machine Learning is all about. As such, Artificial intelligence is especially useful in this type of trading. If the last two years are ones to go by, it is apparent that 2022 will bring forth AI-powered computers that can analyze large, complex data sets faster and more efficiently than humans. The resulting algorithmic trading processes automate trades and save valuable time.
Personalized Banking With banking and finance, anyone who has been paying attention can testify to the fact that traditional banking might just not be cutting it with today’s digital savvy consumers. A study by Accenture of some 33,000 banking customers found 54% want tools to help them monitor their budget and make real-time spending adjustments. Furthermore, nearly half of these banking customers are “very willing” to use computer- generated banking advice. AI assistants, such as chatbot, use artificial intelligence to generate personalized financial advice and natural language processing to provide instant, self-help customer service. In this space, one development that caught my attention whilst buttressing my point on how AI in finance is the next big thing is the TD Bank Group announcing plans to integrate KAI into their mobile app. Providing customers with real-time support and spending insights, KAI is a conversational AI platform created by Kasisto. Abe.AI is another major player that comes to mind when we think about AI in finance. As a virtual financial assistant that provides customers with more convenient banking, nothing could possibly illustrate the impact of AI in finance better than Abe.AI. Whilst integrating with Google Home, SMS, Facebook, Amazon Alexa, Web and Mobile, the assistant provides services ranging from simple knowledge and support requests to personal financial management and conversational banking.
Cybersecurity and fraud detection The financial domain is such that every day, huge quantities of digital transactions take place as users move money, pay bills, deposit checks, trade stocks and more via online accounts and smartphone applications. As such, the need to ramp up cybersecurity and fraud detection efforts is now a necessity for any bank or financial institution, and artificial intelligence is playing a key role in improving the security of online finance.
On a final note, the deployment of AI solutions in financial services will involve machine-led decision making affecting financial customers and the processing of customers’ personal data by machines. Whilst this creates tremendous opportunities for business, it also needs to be balanced against potential unwelcome outcomes for customers. If AI tools are not effectively designed, monitored and controlled, this may lead to unfair, unethical or even unlawful results.