How tech talent + AI/ML = A new era of personalized banking

While banks have been focusing on client micro-segments and personalized offerings for decades, these capabilities by themselves are not sufficient to increase consumer engagement and achieve a competitive advantage in today’s age. The banking industry is also facing stiff competition from retailers and tech-savvy enterprises who are putting personalization at the heart of their business models and scaling it to achieve significant performance advantages. To fulfill their crucial role as financial partners and advisors to the modern customer, banks need to deliver a user-centric and solution-based experience to each of their customers. 

Personalization is a must for banks in order to respond to clients' expressed and hidden needs, differentiate their brand, increase revenue, and improve financial inclusion. By gaining a better understanding of their consumers, banks can employ marketing and branding skills that will allow them to create an emotional bond with their clients. Furthermore, banks have recognized the financial benefit of individualization, resulting in significant cost savings. 

In such a scenario, Artificial Intelligence (AI) and Machine Learning (ML) capabilities are seen as vital to drive the second wave of automation in banking by increasing capacity and freeing employees to focus on higher-value projects.

Need for AI in core banking services

For the past few years, AI and ML have been the hottest topics in the financial sector. According to the International Data Corporation (IDC), by 2026, 60 percent of Indian businesses will use artificial intelligence, machine learning, natural language processing, and pattern recognition to augment foresight across the board. This trend is applicable to corporate banking as well.

Like other financial institutions, banks can gain a significant competitive advantage by implementing intelligent AI/ML solutions to deal with the changing industry landscape, better grasp their customers' needs and optimize and refine their market offerings. Here is how this will play out:

• AI/ML in banking can enhance the customer experience via Android/ iOS mobile banking apps. This helps deliver personalized services to the customers. For example, SBI, the largest public sector bank in India, uses an AI-powered chat assistant called the SBI Intelligent Assistant (SIA) that can handle 10000 queries per second. iPal, an AI conversational banking software used by ICICI Bank, can help manage customer queries regarding new products, account balance, fund transfer and so on.
• These technologies can help streamline and automate routine tasks previously performed by humans. This simplifies workflows, optimizes quality and reduces the workload of banking professionals.
• AI is widely recognized for its data collection and data analysis capabilities. It can analyze enormous amounts of data in very little time, increasing efficiencies and driving profitability.
• AI and ML-based systems also assist in risk management and fraud detection via smart banking services like document verification, financial status tracker, etc. They help maintain the privacy of consumers, reduce the risk of fraudulent acts, observe irregular user behavior patterns by scanning transactional data and protect banks from potential breaches. 
• AI/ML-based tools guarantee high-level security by monitoring every transaction and protecting the entire process like a firewall.

However, to provide highly personalized experiences to customers, banks need to combine human talent and skills, underlying technology, and relevant data.

Human talent: Vital ingredient for success in a digital world

The book ‘Human + Machine: Reimagining Work in the Age of AI’ written by Jim Wilson and Paul Daugherty suggests that "The opportunity for skilled individuals to collaborate with intelligent machines will accelerate the shift from the assembly line approach to a more fluid ‘assemblage’ of teams and technology, which will be capable of higher levels of creativity and innovation."

Since banks with better customer service tend to get a larger share of the market, banks need to attract, hire and retain top tech talent to stay competitive and innovate. While AI and ML have raised the specter of job losses in banking and other sectors, the truth is that benefits can accrue only if humans and technology work hand-in-hand to improve productivity.

Here's how humans and machines can collaboratively elevate the banking experience:

Error-free supervision requires human involvement

AI and ML help bring unprecedented advancements in administration, data analysis, algorithmic trading, etc. However, the auditing of such complicated tasks needs human intervention. By checking for unusual results and discrepancies, AI auditors minimize the risks associated with machine-driven decision making in banks.

Managing customer relationships requires a collaborative approach

Digital solutions can automate a process, but human talent needs to step in after a point. For example, an AI-enabled chatbot can handle routine customer queries or guide the customer to the correct department. But some questions are too complex for the software or require an out-of-the-box solution that requires human interaction. This combination of chatbots with skilled talent increases the productivity of the customer service department. 

People are needed to create value from data

As banks become more reliant on data, they run the risk of implementing data-driven solutions without respect for common sense or the human experience. It is self-evident that data is only as valuable as the decisions made by humans. People who examine data, form hypotheses, test conclusions, and finally establish the ultimate direction are the ones who determine whether big data succeeds or fails. 

Human talent + AI/ML = Hyper-Personalization of customer experience

Hyper-personalization in banks is not about offering the next best product; it is about using data and analytics in a smart manner to anticipate customer needs. When combined with human intelligence, technology can help banks move away from mass marketing campaigns and instead create hyper-personalized services that will fulfill the individual needs of customers and increase customer trust and loyalty.

The Hyper-Personalization Engine, or HPE platform, from IDFC FIRST is such an example. This cutting-edge technology allows each client to have a unique and personalized banking experience. The program takes into account a variety of factors, including the user's risk profile, spending and investing history, income group dynamics, and other distinctive traits. This gives IDFC First Bank an advantage in real-time recalibrating portfolios to maximize risk and performance, with appropriate debt-to-equity ratios, cash flow analysis, and timely aggregated investment dashboards. 

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