Not many may realize that they have AI in their pockets with their smartphones that have virtual assistants and AI cameras installed. Artificial intelligence is quite commonplace nowadays. Its ubiquity extends to finance with many banks and financial institutions now integrating AI into their systems.
But how exactly does artificial intelligence improve financial services? Is it a necessity or just a trendy piece of technology that has drawn the interest of many? The AI market is projected to be worth $733.7 billion by 2027, with a compounded annual growth rate of 42.2%. It has to have some real value for it to have such remarkable growth potential.
The core idea of AI transcends gimmickry. There may have been instances when it was used for gimmicky features, but real AI has real practical applications. You can find many apps, for example, that claim to be AI-powered but all they actually do is automate tasks or churn out programmed responses based on keywords or cues.
In finance, artificial intelligence is a serious technology many of the world’s biggest companies utilize. JP Morgan, for one, established its AI Research program to support cutting-edge studies in the financial applications of artificial intelligence, machine learning, as well as blockchain and cryptography.
A research report published in Narrative Science says that around 10% of organizations at present are already using AI to be competitive and to help identify opportunities they tend to miss. “It is the early days of AI in the financial services industry but the technology is increasingly going to be more important to organizations to innovate and remain competitive,” the report writes. Also, the report highlights the benefits of improved communication with staff and customers and better data analysis when using artificial intelligence.
Real world applications
Risk management, investment, credit, and personal banking are some of the segments of finance where artificial intelligence is prominently used. Here are some examples of AI solutions used by real companies with successful outcomes.
Effective risk management
Massachusetts-based software developer Kensho offers a financial analysis solution that integrates natural language processing, AI, and cloud computing to answer complex financial questions. As reported in a leading publication, this solution helped investors prepare for the consequences of Brexit. Bank of America, J.P. Morgan, and Morgan Stanley are some of the high-profile users of Kensho’s technology.
Another notable example of improved risk management with the help of AI is the use of Ayasdi, a machine intelligence system designed for enterprises and organizations with complex activities. Ayasdi claims to have helped reduce investigative volume at HSBC by 20%. “It’s a win-win. We reduce risks and it costs less money,” says HSBC COO Andy Maguire as quoted in a study conducted by Ayasdi.
Informed and automated investment
In the field of investing, AI helps investors find opportunities they would have ignored if they followed their conventional ways of investing or trading in the financial markets. Arbitrage trading, for example, is not as popular as stock and forex trading, but it is something worth giving a try. “Arbitrage trading works as a result of market inefficiencies in the financial markets,” according to a Jubilee Ace study on arbitrage and its applications. There are potential profits in these inefficiencies, but investors need to be quick in finding and taking advantage of the opportunities. As such, automated and AI-powered trading systems are necessary to spot and make use of these chances for arbitraging.
On the other hand, AI has been helping investors make informed decisions through forecasts. One of the best examples of these forecasts is the “AlpacaForecast AI Prediction Market,” which is used by Bloomberg as part of their financial market projections. Alpaca fuses deep learning and high-speed data analysis to generate short-term and long-term market predictions after detecting patterns in market price changes.
Loss-cutting credit decisions
Many auto lenders were able to reduce their losses by 23% per year by using ZestFinance’s Zest Automated Machine Learning (ZAML) platform, an AI-driven underwriting solution that helps businesses in assessing borrowers with scarce credit information. ZAML is an end-to-end system that covers thousands of data points to achieve transparent and comprehensive creditworthiness evaluations.
Scenaptic Systems, on the other hand, claims to have helped a major credit card company avoid losses amounting to $151 million through its Ether platform. This underwriting system designed for banks and credit institutions analyzes a vast multitude of structured and unstructured data to generate contextual underwriting intelligence. It allows financial institutions to cut losses while achieving greater transparency.
Enhanced personal banking
Even personal banking benefits from artificial intelligence. An Accenture study found that nearly 6 out of 10 personal banking customers want to use tools that can help them oversee their budget and implement real-time spending adjustments. One excellent example of these tools is KAI, a conversational AI system created to enhance banking customer experiences. TD Bank Group, as reported by Kasisto, has already integrated KAI into their mobile app to provide customers with insightful spending information and real-time support.
Another useful personal banking AI tool is Abe AI, which is a virtual assistant that can be integrated with Amazon’s Alexa, Google Home, and Facebook. It improves banking services by providing enabling conversational banking, which simulates the experience of banking with an actual bank teller. It also answers customer queries and offers personal financial management insights.
Artificial intelligence brings palpable benefits to financial service companies and their customers. The use cases mentioned above are just a few of what AI can do for the finance industry. There are more to come especially as technology advances and more people embrace tech-driven solutions.