How AI and ML is transforming the fin tech landscape
Sri Shivananda, SVP and CTO PayPal
Artificial intelligence and its applications have made a significant impact on nearly every industry. Defined as a technique enabling machines to mimic human behaviour, brands are using AI to automate processes at an increasing rate. We see this at many points of brand interaction - site suggestions on our search engine, lane assistance in passenger vehicles, and app troubleshooting, to name a few.
AI isn’t a new phenomenon. It has been around for almost 50 years, learning constantly, almost on a daily basis. As we evolve and become more efficient, and artificial intelligence learns to better emulate human intelligence, businesses benefit from increased process and operational efficiencies. As just one example, analysis by PWC[i] predicts that AI could contribute up to $15.7 trillion to the global economy as soon as 2030. Of this, $6.6 trillion will likely come from increased productivity; $9.1 trillion, from consumption side effects.
There is a rising consciousness globally around how AI can provide optimum results while working in tandem with humans. This essentially means that humans and AI augment each other’s unique capabilities; such as the innately human qualities of leadership, emotion, compassion, teamwork, creativity, and the speed, scalability, and quantitative capabilities of AI.[ii] India has the world’s second largest customer base and as such can reap significant benefits, wherein humans and machines can enhance each other’s complementary strengths. The potential for AI in India is vast and a recent report by Accenture says that AI has the potential to add $957 billion[iii], or 15% of India’s current gross value, by 2035.
There is a cascade of the use cases of AI across industries. The fintech industry, in particular can benefit greatly by integrating AI into its processes and functions. It has the potential to lower costs, increase productivity, and contribute to the customer-facing practices of fintech companies across the globe. As AI weaves itself further into the fintech discourse, we have witnessed the emergence of some key trends.
Firstly, AI and Machine Learning (ML) is being utilised by fintech organisations to gauge risk and assess fraud cases. Here, analytical tools are used to collect evidence and data is analysed, wherein AI tools learn and map out user behaviour and seek patterns that can be used to identify potential fraud attempts. Over time, AI systems can learn and adapt to wean out undiscovered cases and refine fraud and risk detection capabilities to better protect consumers.
Secondly, AI is increasingly being used in customer relationship management. According to Gartner, by 2020 consumers will manage 85 percent of their relationships with the enterprise without interacting with a human.[iv] Fintech firms are also making use of customer-facing systems such as chatbots or voice systems capable of providing human-like interaction with consumers to effectively resolve issues at a fraction of the cost, no matter the time of day. In turn, users can make payments and transactions directly using chatbots, without the need of human intervention or downloading apps. Consumers are increasingly looking for swift and personalised experiences, which can be delivered by AI-based virtual assistants. These assistants can even give data-backed financial suggestions by leveraging their mining and analysis capabilities.
AI can be used by fintech firms for more personalised campaigns, by leveraging anonymized, non-identifiable user behaviour data to tailor relevant campaigns and offers. AI can also help with customer retention and loyalty, as it can take a customer’s information into account to make sure that businesses are offering the most suitable products at the right time. This gives the companies the opportunity to improve their services and offerings, thereby aiding customer loyalty.
Lastly, AI has immense potential in making credit decisioning seamless, faster and more efficient. In addition to AI’s robust applications in risk management, fintech companies offering credit services are using AI to quickly assess the creditworthiness of a customer. It enables companies to promptly ascertain whether they should be able to provide credit to that customer again, or what credit solutions might fit them best.
It is clear that AI is enabling a metamorphosis of organisations across verticals and is taking on increasingly complex tasks. While this bodes well for the industry as a whole, it is critical to view AI as not only artificial intelligence, but augmented intelligence. AI and ML can increase the capabilities of the current workforce but has to work in tandem with people for optimum results. The future of AI has to be mapped with the human capital in mind. Collaborative intelligence of machine and humans far outweigh either of them in isolation. As AI matures and evolves, the workforce will need to keep pace in terms of skills and capabilities.
There is a need for more education and for businesses and governments to play a role in using AI ethically. Future use cases will emerge as AI adopts and evolves further. We have already crossed the AI Rubicon, and the future lies in the symbiosis of machine and human intelligence.
[i] PWC’s Global Artificial Intelligence Study (2017)
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