Artificial intelligence (AI) is rapidly transforming the way work is performed across a myriad of industries. Financial services are no exception. The transformation is exciting and incredibly compelling, but it also induces significant anxiety. This guide is designed to highlight a few ways AI has already impacted the sector and foreshadow the ways it could revolutionize the future.
Before delving into things, I want to give a special thanks to Christopher Dole, who spoke with me about AI and business. Dale is the cofounder of Soothsayer Analytics, a data science firm that helps companies leverage AI to explain the unknown, predict the future and optimize their businesses. His expertise was invaluable in shaping the ideas presented.
Automated Customer Service
For most financial institutions, basic customer service is the extent of the chatbot offering. However, large brokerage firms and nimble technology firms have taken chatbots to the next level – with robo-advisors. These client-facing programs leverage sophisticated computer algorithms to provide personalized financial advice, investment recommendations and ongoing investment management.
The robo-advisory process begins via an online interface where the bot gathers key information about you. At a minimum, this includes personal financial details, your investment objectives and your tolerance for risk, which is largely reflective of your time horizon.
Then, the bot analyzes the information and establishes a customized investment strategy for you. Typically, the strategy will reflect a predefined, passively-managed, asset allocation framework that matches your profile.
Robo-advisors offer cost-effective alternatives to traditional financial advisors, providing convenient options for those who prefer spontaneous interaction and instant feedback over formal meetings and discussions. However, investment management is currently the extent of the robo-advisory service offering.
Conversely, the most competitive human financial advisors offer a full gamut of financial services, helping their clients’ budget, bank, manage debt, optimize insurance coverages, minimize tax burdens, plan for retirement and manage investments.
Financial services firms are harnessing AI for task automation, also known as intelligent process automation or digital process automation. The goal is to leverage AI to automate laborious manual processes, freeing up resources for more valuable tasks.
Implementing AI-driven automation can lead to streamlined workflows, heightened productivity, and decreased operating costs. Moreover, it has the potential to eliminate human error, enhance accuracy and contribute to employee satisfaction by fostering more fulfilling work environments.
Apart from customer service, financial services companies commonly strive to automate various areas such as transaction monitoring, document and data management, accounts receivable and payable processing, collaborative project management, as well as employee-related functions like onboarding, payroll processing and benefits administration.
Beyond automated customer service, robo-advisory solutions and task automation, AI is just beginning to scratch the surface in the financial services sector. Its reach and economic potential are massive.
The power of AI lies in how it takes into account an infinite range of variables and adapts organically based on data of any scale, arrangement or intricacy. Dale believes the benefits of AI are especially compelling for transaction-heavy organizations that struggle to glean forward-looking insights from their data.
Fraud Detection and Prevention
One area with immense promise is fraud detection and prevention. This application is especially attractive to banking institutions, brokerage firms, asset managers and insurance companies, which execute a staggering volume of financial transactions on a day-to-day basis.
Machine learning algorithms can analyze these transactions and identify patterns and anomalies indicative of fraudulent activity. According to Dole, the most sophisticated AI-powered systems detect and prevent fraud in real-time, dramatically bolstering security and reducing the risk of financial losses for both financial institutions and their clients.
That said, the potential for algorithmic bias exists, which can lead to inappropriate determinations and elevated liability exposures for firms embracing this technology. The only way to avoid this is to ensure that AI-powered fraud detection systems are trained with unbiased data sets that represent the diversity of the populations on which they focus. This entails a high degree of data science competency, meticulous planning and continuous monitoring.
Perhaps the most significant opportunity of AI utilization in the financial services arena is enhanced decision-making associated with tactical maneuvers, strategic endeavors and the allocation of capital. Dole says, “Leveraging AI enables financial institutions to transform the decision-making process to be more holistic, accurate, regulatory compliant and effective.”
In his experience, many financial institutions make critical risk assumption and capital allocation decisions based on a very limited amount of data available to them. Surprisingly, this notion holds true as it addresses the challenges faced by numerous companies in accessing and interpreting the data they require, primarily due to its high cost or complexity.
According to Dole, “Introducing AI into the decision-making process can drastically improve outcomes, the byproduct of significantly raising the utilization rate of available data, while incorporating an engine that is able to assess an infinite amount of data, pinpoint trends and formulate actionable insights.”
AI has significantly impacted the financial services industry ever since the emergence of chatbots, robo-advisors and task automation tools. However, these programs are just the tip of the iceberg when it comes to the transformative potential of AI.
Two areas that hold vast promise are fraud detection and prevention and enhanced-decision making associated with tactical maneuvers, strategic endeavors and the allocation of capital. On the surface, the future is overwhelmingly bright.
However, there are significant challenges associated with the use of AI in the financial services industry. Inadequate human oversight and algorithmic bias are top-of-mind. Therefore, as financial services firms implement advanced AI technologies, it is essential that they do so in a responsible, risk-conscious fashion.
An overly methodical approach is not advised. According to Dole, traditionally conservative firms need to shed the “wait and watch” mentality and work to develop an AI strategy right now. Doing so is imperative to remain competitive in this rapidly evolving environment.