Finance is integrating artificial intelligence (AI), machine learning and predictive analytics at a striking rate for both customer-facing and back-end operations. As PWC has noted, 81% of banking CEOs are concerned about the rate of technological evolution in their industry – and Forbes reports more than $4 billion in newly funded ventures focused on financial services AI applications in the last two years. In one study, 32% of financial services executives were already using AI, and that number will only increase as technologies become more sophisticated. Accenture found that 76% of banking executives intend to deploy AI within the next three years to improve their customer interface. Every day, new technologies are emerging that help companies be more efficient with their operations and deliver a better customer experience. Here’s a closer look at some of the different ways the financial services industry is using AI and how that trend is likely to take shape in the years ahead.
From Chatbot to Sophisticated Virtual Assistant
Within banking, ATMs and online banking have made it easier for people to complete tasks quickly and easily. Yet if they had a question or wanted to open a new account, they either had to contact a call center or drive to the nearest bank branch. Employing staff, training them and monitoring the consistency of the customer experience is a challenge – and costly to the bottom line. For banks, one of the earliest uses of AI has been to improve customer experience. They have been leveraging chatbots – technologies that use natural language to mirror human customer service – for routine tasks; and, as Gartner predicted, the sophistication of chatbots has increased significantly thanks to a deeper integration with AI.
A number of banks are beginning to launch virtual assistants that use predictive analytics and cognitive technologies to provide users with highly personalized support. For example, instead of simply using a text chat interface to get help with resetting your password, next-generation personal assistants will access your full financial portfolio, banking history and goals to make recommendations, automate trades and much more. Via voice-activated devices, they’ll be available through the support functions of bank websites and on kiosks at physical bank branches.
Processing Claims: Bringing AI to Complex, Repetitive Processes
Within the financial services industry, there are a number of processes that are both complex and repetitive. Consider the process of filing a claim with an insurance company. There are a number of steps that need to be completed, from initiating the claim to gathering the supporting documents to evaluating the outcome. A similar process occurs when someone applies for a mortgage. Today, financial institutions increasingly rely on AI to guide users through the process, and even make preliminary decisions.
For example, process guides might advise someone opening a claim to fill out a form. The AI claims interface would then prompt the user to visit a website and schedule an appointment with an advisor.
In some innovative cases, insurance companies are experimenting with drones that fly over damaged cars and take the necessary pictures, to avoid having to send a staff member or disrupt the car owner’s schedule. With this technology, staff members or the client can log in and upload supporting documents, such as pictures they took at the scene, police reports or witness information. The algorithm then determines if all the necessary information is provided and flags the claim to be evaluated by a team member, or it may even analyze the submitted information and make preliminary recommendations.
AI is also helping major financial services brands dramatically reduce the time spent on back-end processes. For example, Tech Emergence reported that JP Morgan Chase invested in AI-powered technologies to help analyze legal documents and extract critical points and clauses. Reviewing 12,000 commercial credit documents requires more than 360,000 hours annually. With the new technology, JP Morgan Chase reduced the total time needed to seconds. The potential for AI to streamline back-end operations has significant implications for cost savings, faster service and the capacity to redirect staff to high-value activities that can’t currently be completed by AI-powered tools.
Robo-Advisory: Powering Smart Operations
Increasingly, these algorithms are being used to help concurrently process thousands of pieces of data and provide better recommendations than an individual broker or advisor could. An example of these algorithms is the use of AI-powered robo-advisory services by wealth management brokers. Based on market forces and programmed information about a client’s financial goals and risk tolerance, these advisors can automatically rebalance portfolios and make recommendations about specific actions. For instance, if a client’s stock holdings have significantly appreciated in value and that customer has indicated a goal of making money toward the purchase of a house, an AI advisor might recommend that the investor sell to capture the market upside. Similar “smart” operations tools are being developed and deployed across the financial services landscape, providing people with entirely new options for how they manage and view their money. With the introduction of AI analysis, predictive-powered advisory helps customers make financial decisions in real time, providing a better level of service and more positive outcomes. From automated portfolio management to algorithmic trading, the potential for this emerging class of FinTech is nearly unlimited.
AI Improves Bank Security
Few industries face as many security concerns from consumers as the financial services industry. New AI technologies are helping banks identify and prevent fraud and security hacks in real time. Using artificial intelligence and machine learning, it’s possible for financial services firms to review a huge number of transactions and flag any anomalies; however, cybersecurity threats are evolving at an alarming pace with new scams emerging frequently. AI-powered security systems are able to “learn” from one instance, and continuously improve the security delivered at scale to the bank’s customers. Some institutions are also extending these tools to payment providers, supporting security operations throughout the payment ecosystem. As AI-powered security tools continue to increase in sophistication, this will offer a higher level of security and help reduce both breaches and the risk of fraudulent activity.
AI is reshaping the money management experience. As today’s consumers demand a more personalized experience and large enterprises look for ways to streamline their operations, algorithms are the leading tools for getting more done.