In 2020, when the world was devasted by the deadliest pandemic of all the centuries, we saw a rise in the adoption rate of digital banking services. As per the Mckinsey report, a 20 to 50 per cent rise in adoption was recorded. The expectation is, customers will continue cutting on their branch visits, and they will demand more advanced services similar to the ones they experience from other customer-internet companies. AI being an integral part of daily life, it becomes necessary to be AI-First to remain relevant to the changing market conditions.
Why AI in banking?
A humongous amount of data is lying unused in the banking structure, and the banks deploy AI to realise the new opportunities from the unused “vast troves of data”. In an environment of “low-interest rates”, it becomes imperative for the bank to integrate advanced technologies. More broadly speaking, if we can list various reasons that lead banks to adopt AI, there are endless reasons. To stay relevant, to stay unique, to compete and compel the ever-changing, tech-savvy customers, banks need to deploy the latest technologies at scale.
How AI is changing the banking process?
When we think of AI in banking, there are three areas where it has been deployed at scale: conversational banking, underwriting, and detecting fraud.
In conversational banking, banks leverage AI to engage with customers with chatbots and Robo advisors to recommend products that will be totally personalised. To deepen the customer relationships, AI is deployed at scale in the front office and structure.
Also, it helps in enhancing customer interaction and experience: e.g., chatbots, voice banking, Robo-advice, customer service improvement, biometric authentication and authorisation, customer segmentation (e.g., by the customised website to ensure that the most relevant offer is presented), targeted customer offers.
Enhancing the efficiency of banking processes on building smart contracts: e.g., process automation/optimisation, reporting, predictive maintenance in IT, complaints management, document classification, automated data extraction, KYC (Know-Your-Customer) document processing, credit scoring, etc.
Detection of Fraud
AI is also leveraged to detect and prevent fraud. It enhances the security and risk control: e.g., enhanced risk control, compliance monitoring, any kind of anomaly detection, AML (Anti-Money Laundering) detection and monitoring, system capacity limit prediction, support of data quality assurance, fraud prevention, payment transaction monitoring, cyber risk prevention.
In the banking industry, adoption of AI is necessary but there are incumbents that bank faces. To remain market-relevant, banks need to be fast, agile and flexible to compete with their nearest competitors- fintech. Again at the same time, they need to maintain security, transparency, regulation and compel the new age digital customers with an engaging experience.
According to global consultancy Mckinsey, “Disruptive AI technologies can dramatically improve banks’ ability to achieve four key outcomes: higher profits, at-scale personalisation, distinctive omnichannel experiences, and rapid innovation cycles”.
The Future is here
The Future of AI will look more promising when they will cater to the next-gen customers with their highly intelligent recommendation engine that will automate regular decision-making tasks, recommend the right product/service and many more. The future AI bank will also attain customers with their personalisation touch. It will analyse the past behaviour, the present condition and recommend a product based on these data. Again, we will see more consistent experience across various offline and online channels. In this article, we have given an overview of how our future banking might look like. To have a deeper understanding and insight into how open banking can revolutionise the banking industry when it is powered by AI, take a look at our latest ebook. To download, click here.