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FINTECH-Gender inclusion in the world AI innovation can improve ethical outcomes in banking -B-AIM P

If artificial intelligence is to reach its full potential in revolutionising financial services, we need to diversify the people building these systems and attract more women to the industry.

So far, we are failing.

According to the Datatech Analytics for the Women in Data campaign found that only 25% of UK jobs in artificial intelligence and other specialist technology roles were filled by women in 2019 – the lowest proportion in two decades. Numbers elsewhere reflect a similar figure. The World Economic Forum (WEF) estimates that 78 percent of global professionals with AI skills are male — a gender gap three times larger than that in other industries.

The consequences of a homogeneous ‘male’ workforce is the creation of machines and systems that are designed with inherent gender and racial biases.

This will impact a range of businesses, especially financial services – where women have traditionally been underserved. This, despite the fact that they account for half the world population – and control a third of the world’s wealth under their control. They are also increasing their wealth faster than ever—adding $5 trillion to the wealth pool each year—and outpacing the growth of the wealth market overall.

AI is already ubiquitous in the sector, with 75% of banks with over $100 billion in assets reporting implementation of AI strategies. These large banks are using AI in three key areas: front office (conversational banking), middle office (anti-fraud) and back office (underwriting).

Banks like AI because it holds the promise of improving operational expenditure. The possible cost savings of using AI applications is about 20 and 25 percent across IT operations (namely infrastructure, maintenance and development costs), which adds up to around $447 billion by 2023.

If deployed effectively, AI can also help to put the customer first, by making financial services easier and more accessible for everyone.

AI-based tools that harness the use of data and machine learning algorithms can help to democratise access to loans by proving credit worthiness instantly, facilitating branchless banking and providing 24 hour support through chat bots. It can use face recognition to authenticate identity for new credit cards or bank accounts remotely- and deploy enhanced messaging apps that help banks offer better quality customer support and financial wellness spot checks. The list goes on.

The best outcomes for AI enhanced banking, however, requires diversity behind those creating and implementing the technology. And that means attracting more women into the sector. Otherwise women and other marginalised people will continue to be shut out from many important services – this time by machines – instead of humans.

We are already seeing the fallout in the banking sector from this lack of diversity. Goldman Sachs, for example, is being investigated by regulators for using an AI algorithm that allegedly discriminated against women by approving larger credit limits to men than women on their Apple cards.

This kind of bias exists because AI algorithms are “rule-bound”, in that the creators take as given a fixed position, which is usually shaped by stereotyped thinking. So men get more funding because they often make more money, and women aren’t recognised that they can earn the same as, or even more than men, and will get less.

Similar biases in AI algorithms also exist in facial and voice recognition, two innovations that are being heavily invested in by banking institutions – and which will ultimately limit the amount of customers they reach, and reduce their profitability in the process.

Diversifying the workforce

If artificial intelligence is to reach its full potential in banking, we need to diversify the people building these systems and attract more women to the industry.

But how?

First, STEM skills must be prioritised in primary and secondary school curriculums, and available to all students with an emphasis on coding and software skills.

Second, we need more mentoring programmes to encourage women and people from different backgrounds to enter technology and AI professions. This should start at secondary school to inspire the next generation of digital workers.

Mentoring should also continue throughout an employee’s career and there should also be initiatives and programmes in place that help to build communities and networks that allow people to support one another – especially in the coding world – which forms the foundation for AI. We don’t just want women to enter the professions, but to be nurtured and to thrive in them as well.

As an AI ecosystem builder, Skymind is investing in community and education – supporting programmes around the world that put training and diversity at the heart of their coursework. We have opened one of the world’s biggest AI campuses – and, with help from industry leaders, are devising educational training that reflect the types of skills that are required by the sector today – and sponsor people from all walks of life to become vital AI talent for the companies building our future.

Finally we should launch more apprenticeship programmes and insist on legislating diversity in AI. Nothing can happen without support from the government.

Whether AI helps to accelerate the challenging or the maintaining the existing status quo is yet to be seen. What we do know is that we are still at the stage where banking leaders still have the chance to design the process and make it more inclusive – before AI starts to design them.

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