The incorporation of Machine Learning (ML) and Artificial Intelligence (AI) in banking has rapidly increased in the past few years. Banking and other financial services are keenly adopting AI and other advanced data-science technologies to enhance and facilitate customer engagement, detect fraud or criminal activities, and comply with regulatory banking requirements.
Advanced machine learning algorithms and AI in digital banking assist banks with the detection of financial crime fraud and money laundering. Banks have embraced the automating processes, intelligent automation practices, and use of AI banking bots that use NLP (Natural Language Processing) to classify texts and identify documents, and more.
So, the pandemic or COVID-19 has not stopped banks from adopting these technologies, and rather it has boosted banks’ adoption of AI even more. The enhanced digitization has generated new data processing requirements. But it is also crucial to understand that the pandemic has weakened the AI’s business case. The machine learning models that relied on historical data are no longer used, as there is a vast difference between the pre-COVID and the present data.
Therefore, it would be interesting to see if the COVID-19 pandemic speeds up AI adoption or instead impedes its use in the banking sector.
Impact of COVID-19 on AI in the banking industry
It has been observed that bank’s attraction towards adopting data science and machine learning has sped up during and since the pandemic crisis. According to a Bank of England’s Summer 2020 survey, almost half of the banks polled said that the COVID-19 pandemic has made data science and machine learning even more necessary for the future of banking.
And over a third of the banks reported an increase in planned use cases and expected growth in certain business areas that directly got impacted by the pandemic, such as customer engagement.
Machine learning, data science, and AI in banking are part of a major digitalization that seems to be accelerating more due to the pandemic. American banks and credit unions experienced anywhere between a 20 to 40% increase in online and mobile banking while a 10 to 20% hike was observed in online and mobile banking across Europe following the first wave of the COVID-19 pandemic. And throughout 2020, digital banking has continued to increase steadily.
But even though half of the banks find AI more essential for their future banking operations, a significant proportion of banks are still not interested in the application of AI in banking. Less than a quarter proportion of banks are planning to increase the resourcing and funding for banking applications. In addition, around 12% of banks are planning to reduce funding for their future applications. The evidence towards this fact is that many banks hired fewer AI talents in the year 2020, compared to previous years.
A negative impact of COVID-19 on AI in banking
COVID-19 has impacted banks’ budgets and revenue in the past year. The net revenue income for banks has substantially dropped down during the pandemic. Mostly, this fall is down to provisions. Moreover, apart from tight budgets, the crisis has also affected bank’s business models’ performance (both non-machine learning and machine learning), which explains their reluctance towards incorporating newer or advanced business models and investing in new projects.
Because of the unpredictable nature and severity of the pandemic crisis and recent events, it is no doubt that the bank’s machine learning performance models suffered tremendously. Since there is no past data to train machine learning, banks find it of no better use. Thus, data science applications and banking machine learning have encountered several risks in the past, affecting and negatively impacting over a third of banks in England, Europe.
So what is the future of AI in banking in the post-COVID world?
COVID will have a lasting impact in many technological and financial sectors for the coming few years. But despite the pandemic, banks’ and businesses’ interest in AI has been resilient and does not seem to diminish in demand and adoption. In fact, Google’s searches on AI have spiked in the initial months of 2020.
Many banks might seem to increase their profits through cost-containment strategies and AI technologies such as AI chatbots in banking in the post-pandemic world. There is also a possibility of banks seeking to retrain their machine learning models to achieve better results and perform better under sustained unstable situations.
With the advent of new post-COVID models, some old pre-COVID trends will remain persistently. Mobile and digital banking will continue to provide useful data to banks, making machine learning and AI capabilities more affordable.
Moreover, regulatory clarity could also enhance a bank’s AI adoption.
COVID-19 has affected the bank’s net revenue and capability to adopt expensive AI technologies, but the pressure to AI automation and cut costs overpowers the negative impact, making it much necessary to adopt AI in digital banking. AI helps banks to reduce expenditure, boost revenue, and provide enhanced user and customer experience. Despite certain bank budget limitations, they are looking forward to increasing their AI capacity and enhancing their overall performance and growth. Interface.ai provides intelligent AI solutions and recommendations to banks to help increase their revenue and boost customer engagement. Visit our website at interface.ai to check out and learn more about our products and services.
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