Just as with many other technological advances, artificial intelligence first came into human awareness on the pages of fiction books, whether it be HAL 9000 C-3PO and R2-D2, or data from Star Trek. Humans have been imagining machines that are able to solve problems and reduce human workload for quite some time now, less than 70 years from the day when the very term artificial intelligence came into existence. It’s become an integral part of the most demanding and fast-paced industries.
There is not a single industry that has been left untouched by the transformative impact of AI technology in the last decade. And the financial sector is no exception. Forward-thinking executive managers and business owners actively explore new AI use and finance to get a competitive edge on the market.
Five ways artificial intelligence is transforming the finance industry.
1. Cybersecurity and fraud detection
The most recent McAfee analysis estimates that cybercrime currently costs the global economy $600 billion, or 0.8% of GDP. Fraud costs banks and their customers billions of dollars every year, posing an increasingly significant threat to both. Detecting fraud in a dynamic global corporate environment with an overwhelming quantity of traffic and data to monitor can be difficult.
This makes fraud detection an excellent application for machine learning and AI and fraud detection means using a group of algorithms that monitor incoming data and stop fraud threats before they materialize. AI learns with historical data and can adjust its rules to stop threats it may never have seen before. Something standard fraud software cannot do. I can detect common types of fraud in banking, including credit card fraud, fake account creation and account takeovers because AI is dynamic. It also continuously works to reduce the number of false positives or genuine users being blocked by improving the accuracy of its rules.
It does all of this at such speeds that it doesn’t impact the user experience. The best AI cybersecurity solutions are so lightweight that they won’t impact the performances of websites or mobile apps either. Overall, AI is increasingly becoming the only viable option for keeping financial institutions secure and trustworthy.
2. Trading
Quantitative trading is the process of using large data sets to identify patterns that can be used to make strategic trade. Artificial intelligence is especially useful in this type of trading. AI-powered computers can analyze large, complex data sets faster and more effectively than humans. The resulting algorithmic trading processes automate trades and save valuable time.
Algorithmic trading is the practice of purchasing or trading security, according to some prescribed set of rules tested on past or historical data. These sets of rules are based on charts, indicators, technical analysis, or stock essentials. For instance, suppose you have a proposition to purchase a particular stock, assuming that the stock will end up in losses for three consecutive days before it rises in price. In this case, one can write and design an algorithm in such a way that the buy order for the particular stock is met when the price is at a pre-specified low and sold when the price is at a pre-specified high. A popular form of algorithmic trading is high-frequency trading or HFT, where vast volumes of stocks and shares are sold and bought mechanically at very high speeds.
Currently, most of the regulators and regular stock market investors have moved in the direction of HFT and algorithmic trading in the US stock market. About 70% of the comprehensive trading volume is initiated through algorithmic trading, and that figure is consistently increasing every year.
3. Credit decisions
Credit applications are on the rise, and the need for the approval process to be automated is more critical than ever. Credit decisions have traditionally been made by humans using a scoring method that considers the borrower’s previous performance. This can frequently result in bias as well as a lengthy manual process. AI can help financial lenders make more accurate and quicker decisions apart from automating and speeding up the entire process.
AI can also accurately assess potential borrowers at lower costs and bias. This enables financial services to make informed decisions about their customers. Helping lenders differentiate between high-risk and creditworthy individuals. AI first, banks have designed streamlined lending journeys using extensive automation and near-real-time analysis of customer data to generate prompt credit decisions.
They do this by sifting through a variety of structured and unstructured data collected from conventional sources, such as bank transaction history, credit reports and tax returns, and new ones, including social media, browsing history, telecom usage, data utility bills and more. This decision process is automated from end to end so it can be completed nearly instantaneously, enabling the bank to predict the likelihood of default for individuals in a vast and potentially profitable segment of unbanked and underbanked, consumers and enterprises.
4. Personalized banking
Traditional banking doesn’t always cut it with today’s consumers. A study by Accenture of 47,000 banking customers found 54% want tools to help them monitor their budgets and make real-time spending adjustments. Additionally, 41% are very willing to use computer-generated banking advice. AI assistants such as chatbots use AI to generate personalized financial advice and natural language processing to provide instant self-help.
Customer service with approximately one-third of adult Americans owning a smart speaker. Voice commands are gaining traction, and the adoption of both voice and video interfaces will likely expand as in-person interactions continue to decline. Several banks have already launched voice-activated assistants, including Bank of America with Erika, an ICICI Bank in India with AI pal banks that leverage AI and analytics to deliver smart servicing and superior experiences stand to increase customer satisfaction and loyalty by adopting an AI-first approach in their vision and planning.
Innovative banks are building the capabilities that will enable them not just to deliver intelligent services, but also to design intuitive, highly personalized journeys spanning diverse ecosystems from banking to housing to retail, commerce, B2B services and more.
5. Blockchain
Blockchain is a shared, immutable ledger that provides an immediate, shared and transparent exchange of encrypted data simultaneously to multiple parties as they initiate and complete transactions. Blockchain is difficult to manipulate, deceive or hack, making it a very efficient storage front. AI and blockchain are both used across nearly all industries, but they work especially well together.
AI’s ability to rapidly and comprehensively read and correlate data combined with blockchain digital recording capabilities allows for more transparency and enhanced security and finance. I can effectively mine through a huge data set and create newer scenarios and discover patterns based on data behavior. Blockchain helps to effectively remove bugs and fraudulent data sets the authenticity of new classifiers and patterns created by I can be verified on a decentralized blockchain infrastructure. This can then be used in any consumer-facing business.
For example, AI models executed on a blockchain can be used to execute payments or stock trades, resolve disputes, or organize large data sets. The financial technology industry, as we know it now is highly specialized and centralized. Blockchain and I can be catalysts for the new era of fintech focusing on holistic solutions with increased transaction speeds, transparency and security. All in all, it is clear that artificial intelligence is rapidly transforming the finance industry, bringing with it a host of exciting and innovative possibilities from automating complex financial tasks to providing personalized recommendations.
AI is changing the way finance companies do business and serve their customers. The potential of AI to revolutionize the finance industry is truly staggering, and it is only set to become more influential as technology continues to advance. Whether it is used to improve risk assessment, increase efficiency or identify new business opportunities. AI is sure to play a pivotal role in shaping the future of finance.