If 2017 was the year of hot topics: Blockchain, Artificial Intelligence, Mobile Payments, and 2018 fed into that hype, 2019 is the year of “Show Me the Money”. Within the domain of artificial intelligence (AI) media reports and sales pitches envision a future of machine automation that improves speed and efficiency compared to the status quo. However, with any assertion there are shades of grade and an evolution of progress, not the revolution of “disruption”. Advancement of AI is contingent on industry adoption and innovative companies while there is no better match between overlooked Asian and European AI FinTech Firms and the Financial Services and Insurance Industry.
The reality is financial institutions have been eagerly exploring AI technologies to improve business decisions, risk management, and customer service. [1] A survey taken in 2017 among 424 senior executives from world leading financial institutions and FinTech firms, found that 75% of these organizations planed on implementing or exploring some form of AI technology to analyze large data sets within a year. [2] Much of the work done with companies’ large amount of data is analyzed with machine learning- a subset of artificial intelligence. This involves algorithms that process data to detect patterns in order to make predictions and recommendations based on a firm’s needs. [3] As companies collect more and more data, these AI and machine learning technologies seem to further integrate themselves into many firms’ everyday practices and business models. FinTech has become more user friendly and hands-on thanks to machine learning and AI technology. AI technology allows for financial service firms to work a significantly faster and smarter, making it a game changer.
China and several other Southeast Asian regions are proving to be a dominate force in AI growth. China was the second largest investor [4] ($2.6 billion USD) in AI last year, and it continues to be a leader in the AI and FinTech sectors. AI alone is getting a portion of Hong Kong’s $50 billion 2019 budget. As professor of finance at the Hong Kong University of Science and Technology, Chan Kakeung, explained [5], “China is leading and will continue to dominate in the future.” Hong Kong’s Orient company uses AI technology to provide real time credit scoring, digital lending and other tailored services fora number of fast-growing economies in Southeast Asia. In Beijing, Face++ uses AI technologies for an authentication service involving facial recognition to help with financial fraud detection. [6]
The Chinese FinTech ecosystem is thriving, including that involving AI technologies, for several reasons. China has fully embraced FinTech efforts and innovations. It is such a large economy that players are able to continue to use this technology and roll out new innovations faster than competitors around the world. [7] Along with this, regulation has been much more accommodating for FinTech and AI development in China and surrounding nations compared to its European counterparts. In general, the financial sector has a high level of regulation which means adoption of technology like AI can take longer due to compliance concerns. This regulation is in place to address risk and fraud concerns. However, in China, regulation restrictions are viewed more favorably compared to other leading nations - therefore, encouraging innovation and this fast-growing segment.
AI innovations in FinTech are making their mark not only in Southeast Asian markets but around the world. With AI offering financial service firms with the opportunity to reach greater efficiency and data analysis capabilities, other Asian and European nations have also been supportive of AI FinTech growth. Dayli Financial Group of South Korea was founded in 2015 and is now one of Asia’s leading FinTech companies. It offers AI technology that provides enterprise-level analytics for financial firms. Dayli claims their technology offers “finance to enrich everyday life” and is continuing to grow through several partnerships expanding not only their business, but their technological capabilities, with their venture into blockchain. Onfido is a London-based firm that uses AI-powered identity verification to help websites and companies verify user identities using a photo-based identity document, a selfie and artificial intelligence algorithms. Onfido’s system is used by many finance companies who face the problem of onboarding new clients and users when processes involve time consuming and onerous checks.
Not only is AI helping companies, it is also becoming more user-friendly and widely available to other individuals using FinTech. For example, Indonesia’s Datanest partners with FinTech businesses by building a platform that uses AI and machine learning to help its users compare and apply for loans. AI is also improving cybersecurity for many companies. The UK-based cyber security focused firm, Darktrace, uses AI technology that detects and fights against emerging cyber-threats across different enterprises, including those in the financial service industry. From cybersecurity to analytics to personal banking, AI has found a way to function in many business models in the financial service industry.
Even though AI has caused financial services to evolve greatly in terms of affordances and performance, not everyone is embracing AI and machine learning technology. Several critiques have arisen involving AI in regard to FinTech. In McKinsey’s report, they point out that AI has led to a “meaning evolution” of financial technology and services. Despite the “buzz” surrounding AI Apps in FinTech, there really has not been any great leaps forward for FinTech. For instance, many traditional methods are still being used as a so-called “base” for these technologies. AI has helped improve these basic methods- however, there isn’t necessarily any new processes involved. It seems as if AI is increasingly improving existing performances of FinTech- it is not providing any completely new, cutting edge concepts. Chat Bots involving AI in FinTech are also getting a lot of attention around the industry. Even though they have helped companies, replacing human power with computing power is not a new concept. As one of the earliest entry points into AI, they should not be used to predict or indicative of what the future of AI in FinTech will look like.
Other experts have important concerns of AI development involve transparency, and the potential for biases in the technology. [8] If the creators behind this technology are not open about how it was created or how it works, this is concerning due to the opportunity for bias to be embedded in the technology. As humans, we naturally hold biases. If we are not transparent about how this technology is being created and implemented, the biases of the developers may translate into the technology or the outputs of it. Let’s say a company is using technology that is inherently biased toward a certain group of people or region, this could drastically affect the patterns, predictions or analysis that the AI enables.
Along with this idea of transparency and technology bias is the concern over data quality. If the input data is biased, largely inaccurate or misrepresentative, this would also impact the quality of the output this technology may provide. That is why many are concerned about the proliferation and quick adoption of AI and machine learning in general and in FinTech specifically. It is difficult to retroactively detect problems in the data or the technology processing it, that is why it is important for firms to value transparency when adopting these new innovations.
Despite the concerns and critiques involving AI and FinTech having gained some recognition, these technologies are continuing to expand and evolve. Companies around the world are embracing this technology and altering their business models around it. The future of FinTech will be reliant on gathering and analyzing large amounts of data. AI and machine learning technologies are likely to be at the forefront by helping provide important insights and recommendations to companies and individual users. The question is whether AI is worth the effort and the risk is it truly pushing us forward to new and improved technology or just adaptations of what we are already familiar with?
Imagine Capital Group seeks to partner with FinTech innovators, we want to be a part of this growth in AI and beyond.
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[1] https://www.oliverwyman.com/our-expertise/insights/2017/dec/managing-next-generation-artificial-intelligence-in-banking.html
[2] https://static1.squarespace.com/static/567c3510a12f44019c963eb0/t/5afe1ef070a6ad7131d66732/1526603508488/AI+in+Finance+-+The+Road+Ahead++-+FPM+Dravis+.pdf
[3] https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai
[4] https://www.scmp.com/tech/innovation/article/2117298/china-fast-learner-when-it-comes-artificial-intelligence-powered
[5] https://www.scmp.com/tech/innovation/article/2117298/china-fast-learner-when-it-comes-artificial-intelligence-powered
[6] http://fintechnews.hk/7759/ai/fintech-asia-ai-artificial-intelligence-to-watch/
[7] https://www.mckinsey.com/industries/financial-services/our-insights/synergy-and-disruption-ten-trends-shaping-fintech
[8] https://static1.squarespace.com/static/567c3510a12f44019c963eb0/t/5afe1ef070a6ad7131d66732/1526603508488/AI+in+Finance+-+The+Road+Ahead++-+FPM+Dravis+.pdf