AI’s ability to increase financial inclusion and transparency

As I’ve acknowledged in my previous posts, one piece of technology which is debated constantly and seen by some as holding the keys to a positive future is artificial intelligence (AI). One of many industries the technology is seen to have the potential to revolutionise is the financial sector.

Currently, the World Bank estimates there are 1.7 billion adults around the world who do not have a bank account and are financially excluded. I would argue AI has the capability to address this and improve financial inclusion globally, by providing equitable access to financial services for everyone, regardless of income level, social status, or geographic location.

As it stands, a barrier to entering the financial system is that an adult generally needs a financial history to be approved for a bank account or credit. Traditional systems often rely on credit history, collateral, and other factors to establish whether or not an individual reaches these requirements. Access to a bank account or credit is often taken for granted in developed countries, however, in developing and emerging economies millions fall at the first hurdle.  

Introducing AI with its clear ability and capacity to analyse large amounts of data could solve this issue. With this capability, AI can be utilised to assess the creditworthiness of borrowers. AI can be used to evaluate a wider range of data, such as mobile phone usage, social media activity, and online shopping patterns, to get a more accurate picture of someone’s creditworthiness. Providing a detailed overview with AI, and therefore not having to rely on traditional systems will help to provide access to credit for those who are otherwise excluded from the traditional lending system.

Building on this, AI should, and in some cases already is, being used to develop new products and services that are tailored to the needs of underserved populations. The technology is unique in its ability to identify specific financial needs. For example, AI is already being used to develop micro-loans that are specifically designed for entrepreneurs, as well as mobile banking solutions that are accessible to people in rural areas. Building on this tailored approach, AI is currently providing financial education and literacy to millions of people, with the technology used to create personalised financial education programmes that are fine-tuned to the individual. This is helping to improve people’s understanding of financial concepts and improve confidence regarding financial matters.

Another aspect is AI’s ability to reduce the cost of providing financial services. AI can automate many of the tasks that are currently performed by humans, such as customer service and fraud detection. This can, in turn, help reduce the cost of providing services, making them more affordable for everyone. Tasking AI with combating fraud is something institutions are attuned to; the technology is used to identify and prevent credit card fraud and identify theft already. This helps to protect people from financial losses but more importantly, it makes people more likely to trust the financial system, an important factor, especially in developing countries where trust is often lower.   

Undoubtedly, the use of AI for financial inclusion is still in the early stages, and there are a multitude of reasons why institutions have been slow to adopt AI, particularly when it comes to loans and credit decisions. These range from simple issues such as core banking systems not being designed to operate with new types of data to slightly more complex programmes and coding points. One such complex issue is ensuring there are relevant monitoring and safeguards in place to guarantee systems operate as intended, without adverse action or disparate impact. With that being said, there is a lot of potential for this technology to make a significant impact. By helping to improve access, develop new products and services, and reduce the cost of financial services, AI is a powerful tool that has the potential to help millions around the world access the financial services they need to improve their lives.


AI’s ability to drive sustainable energy sources

The push towards a more sustainable future is of global importance, and the energy sector is a key player in this task. To achieve this goal, we need to fundamentally shift the way we produce and consume energy. Harnessing the power of artificial intelligence (AI) is one way to achieve this, and this point has been consistently reiterated to me during my career investing in small and medium-sized enterprises and emerging technology companies that look to harness AI.

As I noted in my recent blog post on artificial intelligence and education, AI is changing every industry and will impact society in ways we are only beginning to understand. Many people view AI as the beginning of the fourth industrial revolution, and I wholeheartedly agree. Considering this, I would like to observe the energy sector and examine how the application of AI is transforming energy production and distribution, and the positive consequences it is enabling to ensure we adopt a more sustainable energy system – something we can all agree is necessary.

Our current reliance on fossil fuels is no secret. In particular, Europe’s dependence on fossil fuels recently became evident, as it was exposed to the biggest global fossil fuel price shock since the 1970s. If we continue down this path, it is estimated that all reserves will be depleted by 2060. Therefore, the introduction of AI and its ability to deliver energy optimisation and drive sustainable energy must be seen as a key tool and enabler. By using AI algorithms and machine learning, we can reduce energy waste and improve efficiency. This technology is already being deployed by a host of energy giants, yet there is still a long way to go to ensure we catch up to the pace.

From a consumer perspective, AI has the ability to analyse your home in real time, monitoring your energy consumption patterns. This allows it to adjust heating, cooling, and lighting systems, which can lead to potentially significant reductions in energy use. Similarly, but on a much larger scale, AI can now optimise the operation of power plants, whether they are operating on fossil fuels or sustainable sources, predicting energy demand, and adjusting outputs. Imagine the energy consumption savings that can be made with fossil fuels and the knock-on effect this can have on emissions targets.

Another critical aspect where AI can and must drive sustainable energy sources is by predicting energy demand and supply. Accurately predicting energy demand and supply is vital for efficient energy production and distribution. By using historical data and real-time information, such as weather forecasts and energy market trends, we can predict and plan accordingly. This information can then be used to adjust energy production and distribution systems to ensure that energy is available when and where it is needed.

Most importantly, in my opinion, AI can play its most crucial role now in integrating renewable energy sources into the grid. In the UK, for example, renewables now account for more than 43% of the total electricity generated, and this figure is positively growing worldwide – but still has a long way to go. However, sources such as solar and wind power are intermittent, making it challenging to manage energy output. Where AI can step in and help is by managing this variability, predicting energy output from renewable sources, and adjusting energy production and distribution, ensuring more efficient and reliable integration.

Ultimately, the application of AI in the energy sector has the potential to drive sustainable energy sources. By optimising energy systems, predicting energy demand and supply, integrating renewable energy sources into the grid, and reducing the environmental impact of energy production, we can create a more sustainable and secure energy system. As we continue to face the challenge of climate change, as well as the short-term threat of energy security, it is crucial to leverage the power of AI to achieve these goals.


Artificial intelligence’s ability to bridge inequality in education

Education has long been considered the key to unlocking social mobility and economic prosperity. However, inequality in access to education remains a pervasive issue, particularly for marginalised communities. An area I have long held an interest in and offered early-stage investment to is companies utilising Artificial intelligence (AI). Thanks to the recent boom of tools such as Chat GPT and Google’s Bard, AI is now emerging or at least being recognised as a potential solution to bridge these inequalities by providing a personalised and equitable education to all students, regardless of their background or circumstances.

While I have not yet invested in one specific company utilising AI for educational purposes, one observation I have noted through various conversations with industry leaders is how AI can help address educational inequalities. The tech now has the ability to provide adaptive and personalised learning experiences, which can be tailored to the needs of each student. By leveraging data on students’ learning styles, abilities, and needs, AI-powered adaptive learning systems can help students who struggle with traditional teaching methods or require extra support to succeed. For example, an AI-powered language learning system can adjust its curriculum to a student’s individual language skills and learning pace – this ultimately provides them with a more effective and personalised learning experience.

Building on this, AI in education now can provide greater access to education for students facing physical or geographical barriers. Students living in rural or remote areas often lack access to quality educational resources or teachers, but with AI there is now the potential to access high-quality education through virtual learning platforms. AI-powered translation tools can also help students who speak different languages overcome hurdles in the classroom, further improving access. Only recently, Google’s chief executive Sundar Pichai told CBS’s primetime news show 60 Minutes, that Google’s AI has taught itself the Bengali language, even though it was not asked to do so. “We discovered that with very few amounts of prompting in Bengali, it can now translate all of Bengali,” Sundar continues by saying his top researchers don’t really know how it managed the feat, adding that “all of us in the field” refer to the whole system as a “black box” – something “you don’t fully understand”. This is a slightly worrying yet fascinating revelation which highlights AI’s potential amongst a whole host of other things for language learning.

Despite its potential, it is crucial to recognize that AI is not a panacea for educational inequality. Biases can be introduced into AI algorithms if the data used to train them is not diverse and representative, which can and will perpetuate existing inequalities if this is the case.

To ensure that AI is developed and implemented ethically and equitably, it is essential to address bias in data, involve diverse stakeholders in the development and deployment of AI systems, and regularly monitor and evaluate the impact of AI on educational outcomes. These are points that are continually reiterated in conversations I have had with leading minds in the space and are not mutually exclusive to education, this should be the case with all development and deployment of AI technology.

AI has the potential to be a powerful tool in addressing educational inequalities by providing personalised and fair education to all students. While there are challenges to ensuring that AI is advanced and implemented in a right and unbiased manner, the potential benefits of AI in education cannot be ignored. As we work towards creating a more equitable and just society, we must leverage the power of AI to ensure that all students have access to quality education, regardless of their background or circumstances.

Bruno Michieli

Bruno Michieli is the Founding Partner of CS Capital, an alternative investment firm, based in Hong Kong, focused on providing solution-driven capital to lower-middle market enterprises and emerging companies.