Power of AI in BFSI: Transforming operations and enhancing customer experiences

Banking, Financial Services and Insurance (BFSI) has always been a hub for innovation and has seen significant change as a result of recent technology advancements. While mobile has permanently altered how banks connect with their clients, automation and analytics have made it possible for banks to provide highly customised offers to consumers. The BFSI industry, however, has seen its share of difficulties as well. The banking, finance, and insurance industries have long been plagued by ineffective management and operations. 
 
Due to a high volume of requests, a lack of agent capacity and erroneous customer support systems, traditional contact centres' customer support is quite subpar by global standards. As a result, businesses have to endure a multi-fold increase in customer dissatisfaction and bounce rates, creating communication gaps between them and their customers. Successful automation projects help businesses uncover issues that can be resolved by technology. No matter how skilled and attentive the workforce is, mistakes will be made, leading to a cascade of wasted time. 
 
According to Rashi Gupta, Chief Data Scientist, Rezo.ai, the application of AI technology in the BFSI sector has shown to be a practical means of preventing systemic failures, implementing fraud detection and prevention strategies and assisting BFSI organisations in lowering operational risks in trying times. 

“Banks and financial institutions are flooded by the abundance of information due to the exponentially increasing volumes of structured and unstructured data,” Gupta said.

Naveen Singh, Manager - Growth Advisory, Aranca, said that the emerging technology, artificial intelligence (AI), has brought evolution across sectors and BFSI is no exception. 

“The utilization of AI in the BFSI sector is currently prominent in the developed world, specifically North America and Europe. Financial institutions prioritize technological advancements and increase investments in AI technologies to improve customer services and increase business revenue. However, emerging economies, particularly in the Asia-Pacific region, are expected to join the race soon as the world becomes more open and digitally connected. To stay competitive and relevant in the market, AI is no longer an option; it has become a compulsion,” Singh added.

BFSI Pain Points

BFSI’s ongoing difficulties include improving customer service and reducing attrition. The battle to keep existing clients and win new ones is another ongoing one. These issues are frequently data-related or more precisely, they involve assisting individuals who are now required to manage data. Automation is a valuable tool for addressing issues like Regulatory compliance, labour, accuracy, maintenance, decision-making complexity, processing and analysing large amounts of data, low collection rates and dealing with a cultural shift toward a technology-first attitude where customers expect 24/7 service and immediate response and care.
 
Gupta further said that the BFSI sector needs a unified and integrated analytics solution for gaining timely, relevant insights that will help them make better strategic and operational decisions. Along with the issues with expansion, banks and other financial organisations also need to follow constantly changing risk management procedures and satisfy expanding statutory reporting obligations which requires a new data-driven strategy that uses cutting-edge algorithms in conjunction with massive amounts of data and integrates real-time operational data with other business data that further enable Descriptive, diagnostic, predictive, and prescriptive analytics.

“Advanced analytics that comes with AI-driven tools may lower attrition among high-value and high-net-worth consumers, which benefits the company's top line. The versatile linguistic ability of AI-driven products makes it an ideal partner to cater to the tailored needs of BFSI based on linguistic, geographical and informational constraints without compromising the efficiency of operations“, Gupta opined.

Poor Penetration and Rural Participation

Low penetration and density rates and poor rural participation are two major problems facing the BFSI sector. More than 60 per cent of the rural population don’t have access to loan schemes as they don’t have a savings account. Most rural populace prefers keeping all their savings at their home as most times they have difficulty accessing a bank branch.

How AI Can Contribute?

Gupta believes that traditional branch-based banks face difficulties in accessing rural pockets due to their reliance on legacy systems and physical infrastructure, making it economically unviable and operationally challenging to set up branches in remote regions. Moreover, rural markets are diverse, with varying regional languages, dialects, accents, and communication styles. It is important to capture the nuances involved in an AI-powered interaction with rural consumers, for example, a word can mean different things or there can be multiple words to convey the same meaning. 

AI-powered tools can provide the BFSI sector with efficient customer relationship management that can aid them in scaling up their business in rural pockets where information asymmetry is highest without having to spend on physical infrastructure. The utilisation of AI presents an opportunity to effectively bridge the communication divide, allowing for tailored interactions in the native languages and dialects of customers. By capturing the nuances inherent in different ways of expression, this functionality guarantees that rural customers feel understood and valued, ultimately fostering greater trust and participation in financial services. 

In the BFSI Sector, customer relationship management is one of the most important tools. Customer relationship management’s initial and most essential step is to be a good listener and communicator. By leveraging the power of AI, BFSI can offer personalized communication that can not only communicate and register customers’ responses in their preferred language and dialect but also capture nuanced expressions, creating a more inclusive and accessible financial landscape for all.