In Future Facing: AI and the Brand Experience, we examined the myriad ways that AI is affording brands the opportunity to unleash their creativity.
With everything from friendly chatbots to customized apps, retail has led the way in building consumer-facing applications with human needs at their core. But make no mistake, the financial industry is nipping at retail’s heels. One would think that an industry known for its spreadsheets, transactions and big data would have many applications for AI from streamlining backend processes to creating customized experiences based on consumer behavior. Can the biggest disruptive tech to come along since the internet actually help make personal finance even more personal?
AI in Financial Services
The statistics on AI are staggering. More than three-quarters of bank executives are planning to deploy AI within the next three years and more than 50% of those in financial services report that they’re making “substantial investments” in AI. More than automation, AI will help financial services companies understand and integrate data – both big and small – to reduce risk, maximize resources, save time, and create real customer value in the financial industry. Automation allows replacement of repetitive activities – like cash-counting and transactions. But AI does more. At its core, AI replicates and enhances human decision-making – integrating and responding to variables at lightning speed and improving customer service through chatbots, virtual assistants, and highly personalized support platforms.
AI has allowed financial institutions to move from simply automating straightforward, repetitive processes to understanding and integrating large amounts of disparate, complex data. The result is the creation of solutions based on those learnings. Whether it’s insurance claims or mortgage applications, the information gathered from customers is highly variable and personal. In investment, robo-advisors process voluminous data and provide better recommendations than one advisor ever could. Today, financial service companies are deploying powerful algorithms to take customer information and translate it into a cohesive process that saves consumers time and reduces company resources at the same time. But how do financial services companies decide where to deploy AI?
Solving Business Challenges
With so many financial organizations looking at the power of AI, deciding how to incorporate machine learning into their processes can feel like an overwhelming prospect. Eventually, many processes will be based on an AI backbone, but eventually is not today. What’s more important than looking at all of the potential applications of AI in the future is for organizations to focus on how AI can be deployed to solve particular institutional problems today. Where does your institution struggle with overwhelming data that is lying fallow or an internal process that becomes bogged down because there are not enough resources to address it? These are real business challenges in a real-world environment that AI may be able to help institutions address.
Solving for efficiency, JPMorgan Chase starting using AI to evaluate legal documents, contracts and agreements. The image recognition software identifies critical data and information, reducing the time to review 12,000 commercial credit agreements from 360,000 manpower hours to seconds. Wells Fargo piloted an AI program to develop a customer-facing support chatbot that was integrated with Facebook messenger to help its customers reset passwords and retrieve account information. With algorithms that monitor market activity, one would think that Charles Schwab would be using AI to develop better ways to beat the market, but instead the company is using AI to enhance services. In Schwab’s case, AI monitored customer-service conversations and offered real-time help to its human representatives.
What’s Next?
In all of the real world best practices, AI has been deployed to crack the code for distinct organizational problems. As data becomes more omnipresent, financial institutions will be faced with more opportunities to deploy sophisticated tech. It’s not just about maximizing internal resources, AI has the potential to help financial intuitions assess credit quality making the lending process quicker and easier, along with identifying cross-selling opportunities based the intersection of behavior and data. Banks will be able to use AI to protect themselves by reducing risk, detecting fraud and improving regulatory compliance. Advanced AI will allow optimization of investments and instantaneous market-tracking –revolutionizing investor options. But nowhere is AI more exciting than in the customer experience realm.
Given our specialty in experience design, we find AI’s potential to reshape customer interactions some of the biggest game-changing developments for financial institutions. Analyzing consumer data and behavior patterns, AI will give consumers a customized, curated experience with their banks and credit unions. Sophisticated voice interfaces will make customer-service more intuitive, efficient and friendlier. Smartphone personal assistants and apps will interact to give us information about our accounts, but also help us improve our financial habits and make better money decisions. Personal finance is personal. So institutions that find intuitive, holistic ways to incorporate AI technology will sustain and deepen customer relationships – in an even more human way.
To learn more about AI in the financial industry, you can reach us at info@adrenalinex.com.
