As per the globally-renowned market research firm IDC, banks globally, spent about $4 billion on the use of AI in its functioning, in 2018. The recently launched PwC’s report, namely – ‘Sizing the Prize‘ has also caught similar trends in the use of AI by the banking sector, worldwide. As per its published report, Artificial Intelligence will help the global economy rise to a whopping $15.7 trillion by 2030.
PwC research has forecasted global GDP growth of 14% in 2030, compared to the present GDP growth figures, as a result of potential increase in AI-enforcement across industries.
The report has indicated that China & North America will be the biggest beneficiaries of the application of AI in their respective trade & commerce activities. China is expected to receive a boost in its GDP by 26% by 2030, while North America, by 14%. The industry sectors to get the maximum revenue-boost with optimal exploitation of AI in their business processes will be healthcare, financial services, and retail.
How Is AI Going to Transform the Banking Machinery?
We are currently witnessing the transformational phase in the investment banking industry, wherein AI is being introduced in every process concerned with the said sector. A plethora of processes in investment banking that are currently leveraging AI, range from deal sourcing, automating implementation in debt and equity markets, risk modeling, to the use of AI in the middle & back-office processes of banking.
Applications of AI in the Banking Domain
AI has led to slicing off the costs in banking operations to a considerable extent in the recent past and is continuing to do so at an unprecedented rate, with each day passing by. The three primary business functions in investment banking that are benefitting heavily in terms of cost-savings include front office(conversational banking), back-office (underwriting), and middle office (fraud prevention).
A few of the most evident applications of AI in banking, at present, comprise:
- Banking, as an industry sector, is implementing AI on the front-end to make the customer identification and authentication process seamless, imitate live employees through voice assistants and chatbots, further developing customer relations robust, and offering personalized recommendations and insights.
- Banking professionals at major investment banks are leveraging AI to identify and detect frauds in digital payments, and to better the processes for AML (anti-money laundering) and KYC (Know Your Customer).
- AI tech provides banks with a distinct competitive advantage, by helping them make data-driven, smart business decisions.
AI in Banking to Enhance Customer Relationship Management
Retail banking, currently, is benefitting immensely from the use of AI in bettering customer relationship management. Retail banks rely heavily on attracting and retaining their customers over a long period of time, as the relationship between the two is mostly transactional, involving capital deposit & payments. However, retail banks do store a lot of your transactional details while you pay for a product or service online.
Investment banks too, hold a considerable chunk of financial information of their respective clients, and basis that, offers investment advice. But, with AI and data analytics coming into play, now, investment banks can easily automate the process of financial and risk-analysis, to offer the aptest advice to its institutional clients.
Retail banks, on the other hand, source your personal info by saving and storing your transactional history, and later, applying AI to analyze it, thereby carving out personalized financial and consumer products for you.
AI Chatbots in Banking That Help Offer Personalized Customer Assistance
Since the introduction of AI-powered chatbots, weaving a robust bond with customers has become extremely convenient. Chatbots work on an AI-backed tech functionality, called NLP (Natural Language Processing), in which customers can ask and interact with the AI-powered software that answers customer’s questions by recognizing and interpreting human’s voice.
It eventually leads to enhanced customer satisfaction and a better repute for the company offering such kind of support. Moreover, firms do benefit from a significant cost-cutting in the form of replacing call centers with interactive chatbots.
Potential Capital Savings Involving AI Usage in Investment Banking
Consolidated cost savings for investment banks with the use of AI apps is forecasted at USD 447 billion by 2023, with majority savings to be made in front & middle office accountancy. The mentioned data has been sourced from the ‘Autonomous Next’ research conducted by globally-renowned market research firm Business Insider Intelligence.
This is the age of digitization wherein data plays a vital role in strengthening any industry, whatsoever, and the same is the case with investment banking. As AI is powered by data, therefore, to make it useful, you need quality data from within the organizational databases.
In case of retail and investment banks, the scope of AI-application is huge, and as per the ongoing growing trends of AI-deployment in banking, it is expected in a few years time that AI will command a position as critical in banking, as what internet commands in the age of digitization.