Have you ever imagined – living a life without electricity? Ability to generate and use electricity changed the world completely. Today most devices around us run on electricity or electronic circuits. Does AI hold the similar potential of bringing human-like intuitive capabilities into services business specially financial services? If data is considered new oil, then AI must equal electricity. Over the past two decades, banks have invested billions of dollars in creating a tech infrastructure to capture and collect quality data. These data-driven enterprises are now transforming themselves into AI-powered enterprise by integrating advanced analytics in the value chain. Realising this potential, Banks and financial services companies are rapidly adopting Artificial Intelligence to redefine how they operate and conduct their business.
Need of AI in the banking sector
Many banks have struggled to handle an enormous amount of data and generate valuable insights to serve customers better, improve internal processes’ functioning, or optimise risk-return metrics. Artificial Intelligence provides that much-needed ability to analyse data at scale and derive conclusions comparable to a human mind, intelligent and contextual.
Firstly, this gives companies phenomenal power; with the help of AI, they understand a customer better, delivering a more personalised and faster banking experience. To make this happen, banks need to think creatively while embedding AI to balance customer convenience, privacy and security. The use of chatbots and mobile applications integrated with AI that provide a robust infrastructure for customer convenience is becoming a minimum feature in the banking experience. Bank’s have done remarkable innovation in adopting AI in front office client-facing functions and automating internal processes.
Most banks lack to adopt and leverage AI effectively in risk and regulatory compliance. Banks operate in a dynamic regulatory landscape. According to industry estimates, banks have seen over a 500 per cent increase in regulatory compliance post the global financial crisis of 2008. Additionally, global banks spend around a whopping $ 270 billion on risk and regulatory compliance activities annually, out of which a massive $128 billion is spent on technology. Considering the challenges banks face due to the new regulatory environment, banks can leverage AI to achieve better transparency, improve accountability, higher responsiveness and audibility of various regulatory submissions and risk disclosures.
Using AI in risk management can significantly help banks in better credit risk management by comparing their existing champion credit risk models with challenger ML models, using advanced sentiment analysis to capture credit sentiments, and using natural language generation to write credit memos to produce intelligent alerts for credit managers. The other big area is fraud management. As per the RBI’s 2019 report, banking frauds have risen by over 73.8%, despite the government’s continuous effort to curb them. In such a scenario, AI plays a crucial role in early fraud detection and helps the banks adopt the right set of practices to mitigate the risks. Additionally, banks leverage AI technology to monitor payment networks in real-time, analyse data and assess transaction risks. Apart from this, banks are tapping into this intelligent technology’s power to detect money laundering and monitor cyber threats.
Future of banks powered by AIs
Banks have already reached a long way in using AI-integrated technologies. The number of banks adopting AI is continuing to rise considering AI’s capabilities to handle traditional and time-consuming tasks, prone to mistakes. According to HIS Markit’s report, global spending on Artificial Intelligence is predicted to touch $ 41.1 billion in 2018 and reach $ 300 billion by 2030.
Also Read: How automation brings in an optimistic shift in the BFSI sector
Challenges to be worked upon
With the widespread adoption of AI, it has become evident that the technology has reached the point of affordability and accessibility in the banking and finance sector. However, there is still a considerable need to create a responsible and accountable culture for AI adoption. The ethical use of AI and model boas are fast becoming extensive areas for the regulatory focus. Banks implementing AI in their internal and external processes need to comply with the regulatory standards to ensure they comply with the ethical standards and prevent any AI induced Dias in their banking processes. The recent Apple credit card incident has created a big concern for customers and regulators because the credit scoring AI algorithm seeming had “gender bias”, leading to discrimination against female applicants. Banks are learning that AI’s unresponsible and unethical use can result in serious reputational risks and regulatory fines.
What’s next?
It isn’t easy to visualise the world in 2050 without electric cars, and an automobile is the next frontier that electricity is transforming. Similarly, it is impossible to imagine a bank not using AI in 2050. The use of AI in banking is no longer a choice, and it has become imperative for banks to adopt AI to survive. The AI-first bank will have the same advantage as Tesla has with legacy automakers. Traditional banks will need to work at the same speed, at which big automakers are modernising their engineering teams and factories to design and produce electric cars to survive and stay in business. While they do so, Tesla has all the fun of taking away market share!
If you are building a future bank, build a self driving Tesla, an AI-powered self-service bank is the bank of future. All humans will be its customer but no human to drive it.
Views expressed in this article are the personal opinion of Alok Tiwari, Co-Founder & Alok Tiwari, Co-Founder & CEO, CogNext.
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