By Steve Wells, Rohit Talwar, and Alexandra Whittington
How might artificial intelligence impact the jobs landscape in the financial sector?
Of all the business technologies that have come to market recently, artificial intelligence (AI) has been the one generating the most buzz, expectation, and hype. It is also spawning an ever-growing set of doom-laden predictions of how it could be society’s last big invention and bring about the end of jobs as we know them in industries such as financial services. The simple truth is that we are at a very early stage in the evolution of AI and its disruptive technology cousins. As a result, no one knows for sure the likely scale of activity automation and job losses or, conversely, the amount of opportunities that could be created by AI—either within existing businesses or in the new sectors and firms that are emerging. To help explore the possibilities, here we examine some of the ways in which AI could impact financial services and enable new FinTech ventures, particularly regarding robo-investment and chatbots.
Part of the reason that interest, experimentation, and adoption of AI is accelerating is that major “cloud services” providers such as Amazon, Google, and Salesforce, are making relatively low-cost AI services available to firms of every size. This enables customers to apply sophisticated machine learning-based AI tools to the manipulation of very large datasets, providing a real boost to start-ups and smaller firms that would not normally have the R&D resources to develop such applications on their own. This sort of AI as a Service model is spawning several start-ups –especially in the FinTech space– and enhancing the offerings of already-established companies. The overall effect is to raise the capability, reach, and competitiveness for all small- and medium-sized businesses.
The financial sector examples below should help illustrate which particular jobs or tasks AI would handle easily, and highlight the new opportunities that could arise once humans are freed from those tasks. We find it balances the discussion a little to put some attention on the possible positive developments that could also unfold, including the creation of entirely new jobs.
At the moment, the investment sector is anticipating widespread replacement of humans by bots and algorithms—and with good reason. Many current sector roles focus largely on numerical analysis of trends and performance charts, a task which AI can perform more rapidly, comprehensively, and reliably than most humans. In recent months we’ve seen Blackrock, the world’s largest asset manager, announce that 50% of its human fund managers are underperforming the market trackers, and that it is undertaking a program of replacing them with AI-based algorithms. A range of AI fund management tools have also come to market recently. For example, numerai is a crowd- sourced investment tool with over 7,000 data scientists contributing to its development. LendingRobot is an AI algorithm-managed hedge fund that invests in lending marketplaces, charges fees significantly lower than other human-managed funds, and does all its reporting via blockchain.
In the future, it’s possible that AI investment tools will predict interest rates, currency movements, and other economic indicators. For example, the advisory firm PwC has developed an algorithm with 92% accuracy in predicting national GDP. Rapid advances in the ability of AI to crunch massive amounts of financial data make its application to investment processes a no-brainer. The rapid automation of finance means that analysts, traders, brokers, advisors, and even personal bankers could at least partially be replaced by the technology.
But it is shortsighted to just think of job losses. Most current AI-based tools are learning their craft from humans, so the latter will still be required to deal with new situations and more complex requirements. We also think the technology frees people up from the “dishwashing”—i.e. routine and mundane tasks—to focus on the more creative challenges of customer engagement, designing new products and services, crafting solutions to complex internal and client challenges, scanning for what’s next, and doing genuinely game changing thinking. Clearly, realigning staff to these new roles will require individual and corporate investment in training and personal development to ensure the desired mind shift and capability building take place.
At the same time, emerging AI-powered FinTech concepts have tremendous potential to create entirely new and interesting roles and occupations. For example, banks have massive amounts of consumer spending, savings, and investment data to feed into AI algorithms; however, delivering value to clients will require humans with financial literacy, new expertise, and insights which could become the foundation for customer seminars and personalized financial planning services. This could represent a return to more traditional roles for the local bank manager.
New services and business models might be generated from the large amount of information that proprietary algorithms would make available cheaply and easily. Relationships with customers can be given priority in this scenario, which would also require new job roles and capabilities, such as people skills and emotional intelligence, not to mention coding to build the algorithms. Finance employees working alongside AI could evolve into roles that are primarily creative, educational, and supportive—which seems like a very human complement to an otherwise highly automated experience.
New players entering the FinTech scene have the blessing of zero legacy to deal with. Hence, they can start from the outset by focusing on their end-customers and designing solutions entirely tailored to their needs, be that investment, transactions, or insurance. An example would be Monzo, a constantly evolving personal finance app built entirely around the way some segments of society now lead their lives. In such cases, humans are still generally far better suited than AI software for tasks like understanding potential customers, co-creating solution concepts, prototyping, and ultimately building and refining the resulting services. In addition, new players have to build alliances, raise finance, market themselves, develop social media buzz, prove their capabilities to would-be partners and customers, and deliver ultra-fast service responses. Again, in a relationship-driven world, these are all roles for which humans will still have the edge for some time to come.
Already several banks such as Royal Bank of Scotland, Swedbank, Bank of America, and Capital One are using customer-facing bots to take requests, answer simple questions, and perform basic tasks via mobile devices, Facebook, and other platforms like Amazon Alexa. These service offerings are extending in scope and functionality. For example, messaging app Kik is releasing its own cryptocurrency tokens as a digital currency similar to Bitcoin for use within its platform. Called Kin, the cryptocurrency can presently be spent in interactions with a chatbot to buy services and products on Kik. In the future, users could also engage in peer-to-peer commerce using Kin. Such apps suggest that routine banking roles of teller, service agent, loan officer, and supervisor could all be considered ripe for automation or elimination.
Indeed, AI already lends itself well to roles requiring high volume data processing, consistency, and attention to detail. So, what new roles might emerge? For example, rather than view the human-staffed bank as doomed, it might be more inspiring to think of it as a future messaging app or social media site; rather than fire entire labor pools and replace them with robots, banks could flip the model and turn branches into “experience and learning centers.” Here staff would facilitate conversations to help customers solve problems together, connect with each other, and design new products. They could transition veteran workers into roles focused on development of meaningful experiences to touch on the day-to-day lives of customers—for example, helping them learn how to use tools such as new FinTech applications, messaging apps like Kik, and social media platforms like Facebook.
Some displaced workers might find alternative livelihoods working for the FinTechs or participating in projects such as Kin. For example, current uses of Kin include tipping others for making outstandingly good posts or shares on the platform—humor, for example, is rewarded. This might be the kind of activity that could replace a “job” in the future, with income gained via performance on social media or in virtual communities of some kind, paid in cryptocurrency.
The Post-Job Future
Companies that simply slash workforces in the name of efficiency without exploring the bigger picture could be throwing out the baby with the bathwater. The risk is that entirely automated organizations will become undifferentiated and commoditized without human ingenuity to drive constant innovation. Automation of jobs provides an opportunity to tap a vast pool of employee experience for meaningful value in the quest to develop new services and products. Veteran financial workers could be viewed as an important source of knowledge of what working in a bank is really like, and what true customer needs are. A robot can post deposits and certify documents quickly and consistently; however, designing, building, and training an in-branch chatbot is a job best carried out currently with human input. Complementing AI investment tools with behavioral and motivational advice from suitably trained staff could help customers increase their returns, generate higher profits for the banks, and create new opportunities for those with different skillsets.
It is important to acknowledge the reality of workplace automation: Experts predict up to 50% of all jobs (or more) could disappear by 2035, while others suggest that only 5% might disappear while 65% could be affected materially. However, it is much harder to predict the extent to which they will be replaced by roles that have not yet been invented, in firms yet to be born, in industries that are only just emerging. As we said at the start, predicting the outcome is nigh on impossible this early in the game. That AI will impart both creative and destructive effects is a fact of the coming technology revolution that can give us hope and guide more human-centered decisions. The key is to start acting now to train employees with new skills and start creating the new, more customer-oriented and creative roles in anticipation of relatively rapid changes on the horizon.
How can we capitalize on the changes AI and FinTech might bring to the relationship between financial service providers and customers?
How can we harness and nurture the wisdom of veteran employees?
Could AI help technology companies take over the financial industry, or might it help financial service companies to consolidate their position?
This article is excerpted from Beyond Genuine Stupidity – Ensuring AI Serves Humanity. You can order the book here.
Image: https://pixabay.com/images/id-4321886/ by geralt