This article by Lloyd Wahed, experienced headhunter, podcast host and Mana Search founder explores how developing technology such as machine learning will change the way financial services, banks and agile start-ups operate.
Introduction - AI and the future of work
Lloyd Wahed, experienced headhunter, podcast host and Mana Search founder, shares his perspectives on how AI will impact on the future of work. In particular within financial services, Lloyd looks at how incumbent banks and agile start-ups are embracing the potential of machine learning, and how that technology will change not only the work banks do, but the ways they work.
HOW WILL AI IMPACT THE FUTURE OF WORK?
“Artificial intelligence” is the word on the lips of executives worldwide, but the buzz is especially loud in financial circles. Accenture recently reported that eighty-three percent of surveyed banking executives said machine learning was essential to their companies’ growth objectives. Needless to say, adoption is already happening. Polling more than 300 firms, the Bank of England found that over two-thirds had already implemented artificial intelligence initiatives; many of these companies planned to significantly expand these capabilities into other business areas over the next three years.
It’s not just happening behind the scenes, either. Much-hyped fintechs have already launched novel features that leverage machine learning to create a more convenient user experience. Tide, for example, has made processing receipts as easy as taking a photo, while Monzo applies AI to everything from customer support to spending reports.
So it’s obvious, then, that this technology is powering the products that banks offer. What’s less apparent is how it’s changing the way these institutions actually function. Already, machine learning is exerting its influence on everything from hiring to long-term strategy. The takeaway is clear: artificial intelligence will play a primary role in shaping the ways we work for years to come. Here are just a few glances at what that future will look like.
1. PEOPLE MUST STILL BE THE DRIVERS OF CHANGE
Mention artificial intelligence to a layperson and one question is bound to come up: “What about the job losses?” It’s a complex issue, and reports vary as to whether the creation of new AI-related positions can outpace redundancies.
Based on what we’ve seen, though, it’s unlikely that financial institutions will be replacing entire professions with algorithms any time soon. Labour-intensive tasks may become the responsibility of machines, but in many cases human beings still need to be at the switch to help artificial intelligence reach its full potential.
Earlier this year, I interviewed iwocaPay Co-Lead Lara Gilman on my podcast, Searching for Mana. She raised an important point during our discussion: while artificial intelligence initiatives have shown great promise in analysing data and patterns, they’ve had limited success in areas that are less concrete and more abstract. Making decisions about intangible issues, like a client’s risk concentration, is still the domain of humans rather than algorithms.
With this in mind, the future of work will not be a matter of machines replacing humans. Instead, companies will need to play to the strengths of each group in order to achieve optimal results.
2. AI WILL STILL FACE A BIAS PROBLEM
AToo often, the discourse surrounding AI adopts an overly optimistic tone: by letting algorithms make decisions for us, it suggests, we can reduce problems attributed to human error, bias and irrationality. Take hiring, for example. There’s a common assumption that machine learning can be used to source and recruit more diverse talent, leading to workforces that are more representative of the general population.
In fact, the opposite may be true. A 2019 study from Cornell University and Microsoft makes the point that vendors for AI-based employment assessments often don’t disclose how they offset or control for algorithmic biases. Instead of removing bias from the hiring process, this technology can actually reflect and perpetuate it.
Amazon’s recruiting engine is a prime example. Rather than taking a gender-neutral approach to scoring candidates, the resume matching machine frequently penalised qualified female applicants at a disproportionate rate. Since scores were based on resumes submitted to Amazon over the course of a decade and the company operates in a particularly male-dominated industry, the algorithm acted on existing hiring biases instead of alleviating them.
The lesson here is both clear and sobering: this technology won’t automatically transcend the limitations of the people who create it. The solution to issues like diversity and inclusion will ultimately come from human minds rather than artificial ones.
3. THE APPLICATION WILL BE ENDLESS
So far we’ve spilled a lot of virtual ink discussing what AI won’t be able to do, but what it will be able to do is truly extraordinary. Already we’re seeing nimble, forward-thinking fintechs take machine learning and use it to revolutionise even the most staid areas of the industry. If that progress remains apace, there’s no limit to what artificial intelligence can achieve.
Case in point: when Charles Delingpole of Comply Advantage came on the podcast a few months ago, I was amazed at his ambitions for the anti-money laundering sector. As he described how AI powers the company’s massive network of customer behaviour and transactional information, the scale of machine learning’s applications suddenly seemed massive. As Charles put it, AI allows the company to build “one massive graph of everything”.
Plenty of other fintechs are already hinting at the massive scope this technology offers. Onfido – whose CEO, Husayn Kassai, is a past guest on the show – has made such incredible use of AI in the digital identity space that the UK government consulted it about possible coronavirus immunity passports. Other services like Plum use machine learning to analyse behaviours and set out savings plans with an unmatched degree of precision and personalisation. The list goes on and on.
While financial institutions have taken to AI like moths to a flame, there’s still plenty of light to look forward to in the future. Expect existing players and a new crop of algorithm-assisted fintechs to follow through on this promise.
Conclusion
Artificial intelligence has garnered a lot of hype in financial services, but based on the results so far, it will continue to be a going concern for years to come. If institutions – from the smallest start-up to the biggest bank – want to capitalise on this technology, they can’t take an approach that’s either too utopian or too pessimistic. Machine learning won’t automatically overcome human flaws, and it’s not to do the job of an entire workforce. But if companies follow the lead of some pioneering innovators, they too will be able to harness artificial intelligence to brave new ends, fundamentally changing the future of work in the process.
Lloyd Wahed is the founder of Mana Search and host of Searching for Mana podcast, interviewing some of the leading and influential men and women building the future in tech innovation and finance.
Searching for Mana is available on Apple, Spotify and all major podcast platforms.