How the BFSI Can Enable Personalization at Scale with Data Science

How the BFSI Can Enable Personalization at Scale with Data Science

BFSI Can Enable Personalization

For a long time, the banking and financial services (BFSI) sector has been accused of lagging in delivering personalized customer experiences (CX). Research suggests that 72% of customers expect personalized services from their banks, but only 14% of banks are delivering them.

A recent Genesys report on the “Challenge of Customer-Centric Banking” outlines that 61% of banking executives talk about the growing expectations around better CX in the banking industry. However, 45% of BFSI companies are struggling to cope with those demands.

In the age of personalization, BFSI companies can no longer afford to lag behind other industries. Let’s discuss some of the major challenges to personalized CX in the BFSI sector – and how data science technology can overcome them.

Why Is It Challenging for BFSI Companies to Deliver Personalized CX?

Each day, banks and financial services companies generate massive volumes of customer data that they can leverage to gain a competitive edge. However, most of this generated data remains unused or inactive. What is stopping them from leveraging this data? Here are a few major challenges:

Legacy Systems

The existence of legacy technology and applications continues to plague the BFSI sector. Deloitte reports that outdated technologies are the primary bottleneck to achieving personalization in the BFSI sector. Additionally, the lack of advanced data analytics capabilities prevents banks from extracting business value from existing data.

Data Silos

The aforementioned Genesys report found that 64% of respondents believe internal silos are also an obstacle to optimizing CX. For instance, data silos prevent efficient data flow across business functions and branches, thus making personalization unviable in the BFSI sector.

Beyond these challenges, banks have ignored customer needs and focused largely on delivering products and services.

How Technology Can Enable Personalized CX in BFSI

Coming back again to the Genesys report, most CX experts believe that investing in new technology that enables personalization is an important step towards realizing enhanced customer experience. In the age of customer-centric banking, advanced data analytics is now essential for delivering data-driven banking services. Valued at $4.93 billion in 2021, the data analytics market in the banking sector is projected to reach $28.11 billion by 2031.

Among the evolving technologies, Artificial Intelligence (AI) is enabling hyper-personalization in the BFSI sector. It is used to predict customer behavior and their changing needs. Similarly, embedded finance enables non-traditional financial companies to check and authenticate savings and current accounts.

BFSI companies are also leveraging Big Data Analytics to transform massive customer data into new user experiences, innovative services, and personalized recommendations. Using data analytics, BFSI firms can easily gain a 360-degree view of their customer’s digital behavior and queries.

AI-powered systems also enable customers to make informed financial or investment decisions (based on their financial goals). Powered by Natural Language Processing (NLP) technology, chatbots are improving CX in the BFSI sector. As “virtual” assistants, AI-based chatbots can now authenticate financial transactions, thus eliminating the need for human intervention. Besides “conversing” like a human agent, intelligent bots can self-learn from customer responses, remember their preferences, and recommend personalized services. What are some of the applications of data science in the BFSI sector? Let’s discuss that next.

Applications of Data Science in BFSI

Data science technologies, including AI, NLP, and Big Data Analytics, are transforming the BFSI sector with multiple applications. Here are some of their business applications:

Making Sense of Customer Data

Owing to daily customer interactions, banks, and financial service companies must collect and store massive amounts of customer data. Beyond meeting their compliance regulations, banks are leveraging customer data using data science technologies to understand more about customers and explore new sales opportunities.

Using data science, banks can also understand customer sentiment from information collected on social media platforms, customer surveys, and external touchpoints.

Fraud Detection

Financial frauds cost BFSI companies billions of dollars each year, besides the loss of brand reputation. Using AI and machine learning models, banks can detect any irregularity in financial transactions that could suggest a major fraud. Data science technologies are effective at monitoring users’ activity to spot any anomalies or major deviations from the usual pattern.

Anti-Money Laundering

Banks are strengthening their fight against financial crimes, including money laundering. Using advanced machine learning technology, banks can now continuously monitor major transactions across the entire value chain. For instance, ML models can leverage granular data to build and improve sophisticated algorithms.

Insurance Claim Analysis

Among its top use cases in the insurance sector, data science can significantly reduce the time for processing insurance claims. Based on the complexity level, insurance companies can categorize claims and assign a score. Also, using predictive analytics, insurance companies can identify high-cost claims. Data analytics is useful to automatically examine past claims and notify the claims, approver.

How Ellicium Can Help BFSI Companies with Data Science

At Ellicium, we provide end-to-end service in data science to help BFSI companies extract maximum business value from their data. Here are some of our specialized services in data science:

Here is a customer success story elucidating how Ellicium enabled a U.S.-based financial institution to implement an anti-money laundering system using machine learning.

Wrapping Up

To summarize, data science technologies like AI, Big Data Analytics, and NLP can help BFSI companies improve personalization in their CX initiatives. At Ellicium Solutions, our expertise in Big Data, Analytics, and Artificial Intelligence is enabling our BFSI customers to scale up their personalized offerings. Looking to start your data transformation journey immediately? Contact us today!