When discussing the increasing prevalence of automation in the modern workforce, it is easy to conjure up science-fiction stories. As more industries are disrupted and technology penetrates all corners of society, these stories, which felt far off in the distance, are becoming less and less far-fetched.
For years, Hollywood has been obsessed with the potential evils of technology. One of the first instances was HAL, the voice-activated computer in the film “2001: A Space Odyssey,” which malfunctions and starts making its own decisions. There are the machines in the “Wall-E” movie that make life so easy for humans that they can no longer move on their own. There is the Skynet computer grid in the “Terminator” movies that concludes that humans are the real threat to a stable, well-run world and must be eliminated.
Disregarding blockbuster movies, most types of technology and automation revolve around making humans more efficient. Much of the workplace automation of today is the kind that improves workplace efficiency, helps serve customers and clients better, and completes routine tasks, freeing humans up for more complex work.
For instance, some banks are using bots—or sets of smaller programs that have specific functions—to scan loan documents, spot inconsistencies in numbers or formatting, and automatically correct them. These tasks can be performed in seconds compared to the time it would take a human do complete the same task. This speeds up the approval process, frees up employees for other duties, and even helps the company’s bottom line.
The software is also being used to find anomalies that indicate fraud, to recommend specific investing decisions based on a client’s previous activity, and to assess the creditworthiness of potential borrowers. These advances in automation and artificial intelligence (AI) can be exciting for a variety of white collar industries, including law, insurance, banking, investing, or the general financial field.
Technology research firm Accenture reported that the excitement does not end there. Provided that the push to integrate multiple technologies continues, it could boost corporate rates of profitability by 38 percent by 2035, and boost the U.S. economy by $14 trillion in 16 industries.
That said, automation can also have less beneficial impacts. It can potentially can cause disruption such as lessening the need for lower-skilled jobs like administrative assistants, clerks, proofreaders, or underwriters. Even some higher-skilled positions like attorneys or loan officers may be deemed unnecessary or less efficient as programs begin to perform more of the heavy lifting. Front-line customer service agents could also be in danger of being replaced by programs with basic vocabularies and pre-programmed responses to common questions.
There are many ways automation is impacting the world at large. Read on to explore the primary trends within the financial industry.
Right now, Alexa, the artificial persona contained in the Amazon’s interactive voice-powered Echo device, is considered more of a novelty rather than a necessity. She can put on your favorite music, search the Internet to answer your most pressing and obscure questions, provide directions or start a timer. She can even tell you a joke. Of course, Alexa would also be happy to order anything you want from Amazon.com.
Many similar personas are found in smartphones like Siri, Cortana, and Google Assistant. They offer identical voice-dependent features, from restaurant recommendations to traffic navigation. As more and more people familiarize themselves with these voice-activated assistants, other industries will begin to adopt them, including the financial sector.
Voice-activated programs are used to save time searching for customer information in a database or through piles of documents. Some banks and investment firms are connecting their technology into Alexa, where customers can inquire about their account balances, make payments place orders, or ask for customer service to help them.
Though opinions are mixed on the value of automated customer service centers, they remain popular with companies as a way of answering basic questions and taking care of simple customer service functions like paying bills or checking account balances. The better ones offer the option to reach a human customer service representative or to call customers back who do not want to wait on hold.
In these latter cases, human customer service staff will be used for more advanced conversations or complex situations that require nuance and explanation. It potentially reduces their workload as well, since fewer people will be needed to tackle the same fundamental questions all day long.
Additionally, automated phone programs could also provide customer information and history to each agent, right when a customer calls, rather than requiring them to spend valuable time searching for the information when a call is initiated or asking a customer to provide that data.
While the human touch is still needed to some degree in automated call centers, it is not always required in online chats. Many companies have implemented automated chatbots, which are programs that can offer limited text conversations with users. They can ask customers what they need help with, provide essential solutions from prepared answers, collect necessary information, and seamlessly put customers in touch with the right people according to the customer’s issue.
Although they are not typically as responsive and their responses are not as individualized as a human’s, they do have advantages. Chatbots are available 24 hours a day, seven days a week so customers can get answers to their questions as soon as possible. Additionally, chatbots can hold multiple conversations at once and do not have to be paid.
Although the conversations are not with humans, they can still feel reassuring compared to sending a general email or calling a phone number. This year, Chatbot Life estimates that 30 percent of Google’s interactions will be with these bots.
A big part of AI is to help companies improve their processes, especially in conditions where even the fastest human can only go that fast for a specified period. While dedicated, motivated humans may be willing to jump in and pull out all the stops for a particular project for a specified period, they eventually will need a break. Otherwise, performance and motivation will decrease.
Rather than pushing employees to reach impossibly high levels of production, some companies are exploring avenues of machine learning to look for faster alternatives. JP Morgan Chase & Company created a program called COIN, responsible for a variety of filing, organizing, and reviewing of documents.
The reviewing process is especially critical: the program searches for errors in formatting, such as incorrect numbers, wrong data, or formatting problems that could be caused by humans in the creation process. After COIN was initiated, the bank reported that the system was able to run through 12,000 documents in seconds. Not only did it reduce errors, but it saved 360,000 employee hours each year who typically had to work on these documents, including skilled positions such as loan officers and lawyers.
As much as the investment market can change from day to day, some fundamentals do not, such as the importance of long-term planning. Because of this, some investment firms are leveraging automated processes to help customers who may not want or require much hands-on service.
Through a combination of automated texts and informative site pages, some firms are gathering information about customers so that they can provide them with more relevant recommendations based on their age, current income and savings, retirement goals, risk level, and other criteria.
All of this can be done online, including regular check-ins where the bot can summarize current balances and provide suggestions about possible options, such as trying different funds or increasing deductions if a job changes. Indeed a human can be contacted for questions or complex transactions, although it may take hours or days, which is why a simple conversation with the bot may be easier and faster for people used to more rapid responses.
One of the firms that specialize in this type of interaction, Pefin, is willing to help keep track of a customer’s spending habits and annual financial goals, not just retirement objectives. Pefin doesn’t like the term ‘robo-advisor,’ and instead encourages a human advisor to work closely with clients to assess their comfort level and overall knowledge. The advisor is encouraged to adapt to newer technology for their contact methods, especially what the client prefers, such as texting.
Regardless of how clients receive their info, advisors can still access AI for their own planning. They can research different funds, look for patterns, predict the performance of individual funds, and better advise their clients based on their expressed goals and habits.
Overall, advances in automation have all sorts of potential to help financial companies see more efficiency and possibly increase their bottom line. But companies do need to keep some challenges in mind.
All this advanced computing power required for applications, including developing apps, running bots and collecting and retaining user data will come with high costs not only at implementation, specifically as they relate to greater processing power and additional storage needs. To reduce these higher costs, companies utilize the services of the data cloud and off-premises storage compared to local servers. Companies also have a larger commitment to security, especially if customer data is within easy reach for hackers.
All technology has vulnerabilities—even voice services. Amazon Echo owners have discovered that because these devices do not yet distinguish individual voices, it is currently possible to interact with and order things from other people’s Alexa’s. All potential vulnerabilities must be anticipated: breaches could not just cause loss of data but could reduce customer confidence in the organization.
The need to put additional resources into digital security could be offset by changes in the makeup of the financial sector workforce. With less demand for menial tasks like document scanning, compliance and making copies, employers will not need as many employees in these roles.
In the legal industry, which is also experimenting with automation, support staff is being cut. If customers can now find the proper forms online and get details about their case, they may not need to spend as much billable time with an attorney.
Technology news site Futurism warns that some parts of the developing world are at high risk of job loss due to automation for various reasons, including areas of Africa, Asia, and Central America. Other domestic communities can suffer as well, like formerly industrial or agricultural strongholds or simply larger population centers like San Francisco, New York City or Houston.
To counter this push toward automated help, the site suggests that all humans be paid a Universal Basic Income (UBI), regardless of current employment status. Each government would need to subsidize this in their own way.
While the Accenture report does not mention UBI, it does suggest that employers who embrace technology must also make sure to have a focus on their human assets. A people-first mindset can include making sure new policies, and actions fit into the current culture, all managers have high technical knowledge rather than just the middle and bottom level employees, and someone oversees all AI efforts, not unlike a human resources position.
While chatbots and voice systems will be able to take the burden off overworked bottom-level employees, some interactions still benefit from human involvement. The employee that can resolve a customer’s complex problem, especially to their satisfaction, will quickly build up goodwill. Despite being programmed to be friendly, a chatbot is not able to have the flexibility to reverse payments, walk someone through a complex menu, or credit an account, which can be a determining factor in a customer’s satisfaction.
Wired suggests that businesses should develop a hybrid system to stand out from the competition. For brands that are serious about helping their customers wherever they are—on phones, in person, over social media, online, and through any other format—customer service strategy should enable call center representatives to act more human by freeing them up from more menial tasks and create the technology so that chatbots can be more human as well.
The same is true where investing is concerned: big data can predict which purchases might be interesting for an individual according to specific characteristics, but may still need some human guidance.