2024 BFSI Industry Outlook: The Top Tech Trends Driving Business Growth

Introduction

The Indian BFSI sector is on a growth trajectory with a 31% YoY growth. However, a McKinsey report states that financial institutions face challenges such as changing industry regulations, intense competition, and increased operational expenses. With the shifting market dynamics, companies are adopting disruptive technologies like AI, ML and blockchain to tackle these challenges.

• Digital transformation in BFSI increases customer conversion and retention rate by 3-5 times, allowing enterprises to tailor engagement strategies. 
• Data analytics help businesses understand customer behaviour for loan servicing and reduce collection costs by 15%. 
• To achieve growth/expansion goals efficiently, digital technologies allow network leaders to strategically manage loads by gathering insights. 

This blog discusses the top 5 tech trends in the BFSI sector that leaders are adopting to overcome the challenges, facilitate business revolution and drive business growth. 

5 Key Trends and Expectations from Tech Leaders in 2024

1. Hybrid & Multi-Cloud Adoption

According to an IDC report, 80% of corporate banks in India will migrate their operations to the cloud in 2024. Nutanix’s third annual Enterprise Cloud Index report also predicted 39% growth in hybrid cloud adoption in the Indian BFSI sector by 2026. 

The BFSI sector generates over 2.5 quintillion data bytes each day. Managing and processing such vast amounts of data is one of the biggest challenges for businesses. However, with cloud deployment, businesses can process requests quickly, thus improving customer experience. Moreover, cloud solutions offer better data security than on-premise solutions. Since data privacy regulations are becoming more stringent, enterprises need these to adhere to data security compliances.

Cloud solutions allow quick and easy integration of various platforms for seamless data configuration and analysis, thus ensuring business scalability. Businesses also use cloud computing to monitor transactions in real-time and prevent fraudulent activities.

However, many businesses are unable to maximise cloud advantages because of poor network connectivity and lack of visibility. Therefore, the adoption of SD-WAN, an agile network solution, is increasing. It provides better visibility, control and bandwidth for efficient use of cloud-based applications. 

2. Leveraging Big Data & Analytics

Mr Mahesh Kumar Jain, Deputy Governor of the Reserve Bank of India, explained at the “Cyber Security Exercise for Banking Sector” event that digitalisation helps banks leverage structured data to assess customers’ risk profiles. However, big data analytics enable organisations to get deeper insights into customer trends and preferences by analysing semi-structured and unstructured data. 

The need for big data analytics in the Indian banking sector is based on 4 V’s:

• Volume: 48.60 billion real-time transactions took place in India in 2021, the highest in the world. Tracking such high volumes of data generated from these transactions is possible with big data analytics tools. 
• Velocity: As transaction velocity increases exponentially, big data analytics platforms emerge as a solution to handle the velocity of data streams effectively, enabling BFSI organizations to analyze transactions in real-time.
• Variety: The BFSI sector has large volumes of semi-structured and unstructured data that are difficult to analyse. Collecting and processing different data formats from various locations, such as customer support portals and sales dashboards, requires big data analytics. 
• Veracity: The BFSI sector requires accurate data collection and processing. In 2016, Harvard Business Review reported that “dirty” data, characterized by inaccuracies or inconsistencies, cost the US economy $3 trillion annually. These figures have skyrocketed with the booming Indian economy and the increase in user data volume.

Big data analytics plays a critical role in enhancing the finance and banking experience. It provides insights into the entire customer journey, enabling businesses to find hidden customer interaction points and improve onboarding, payment, and deposit processes. It also boosts innovation, operational efficiency, and risk management.

3. Changing Network Strategy & Virtual Network Services business needs

Building resilience is the top priority for BFSI institutions because of intense competition. This involves improving operational efficiency, catering to rapidly changing customer demands, innovating new solutions, and focusing on cybersecurity.

Backhauling traffic from different branches or ATMs using the traditional WAN network does not support real-time request processing, leading to latency. Therefore, financial institutions are unable to expand their branches to different locations or operate remotely.

Hence, enterprises are replacing traditional networks with SD-WAN for seamless interconnectivity across different applications and devices. It increases data processing bandwidth and provides better security due to end-to-end encryption.

4. Increasing adoption of Artificial Intelligence (AI) and Generative AI

According to the “The AIdea of India” 2023 report, 78% of C-suite executives in financial services are either already leveraging Generative AI (GenAI) for one or more purposes or are planning to use it in the next 12 months. The two main focus areas are—enhancing customer experience and cost reduction. 

Organisations are also deploying specialised teams to leverage GenAI for business growth. While 83% of the respondents want to collaborate with external partners, 67% of them want to build an in-house team. 

The report also suggests using GenAI as a virtual assistant for banking institutions. 

The following are some of the most popular use cases for AI and GenAI for banking, financial and insurance institutions:

• Fraud Detection and Prevention: AI and ML algorithms analyse real-time transactions and payment methods. They detect suspicious activities and alert banks and financial institutions. 
• Personalized Customer Experiences: A PwC Report on the use of AI in the Indian banking sector states that 83% of organisations improve their customer service by using AI through hyper-personalisation. It anticipates customer behaviour and needs and helps businesses understand preferred products and services and channels of communication. 57% of them have gained a competitive advantage and improved operational efficiency by automating tasks with AI.
• Automated Customer Service Chatbots: Enterprises use AI-powered chatbots for better and faster customer interactions. Chatbots help customers independently solve basic queries and process requests, reducing banking costs and increasing operational efficiency. 
• Generative AI for Risk Management: Businesses use GenAI to create customer-risk ratings and reports. It helps assess customers’ risk profiles and reduces loan defaults. GenAI can also provide market forecasts for better investment strategies. 
• Compliance Automation: AI models are trained to analyse vast datasets and automate compliance tasks like Know Your Customer (KYC) verification and Anti-Money Laundering (AML). Moreover, GenAI can be trained as an expert to offer insights on industry compliances and frame internal policies.

5. Underscore the rising concern of cyber threats in the BFSI sector

“Cybersecurity is a strategic necessity for the banking sector and not merely an operational issue”, says Mahesh Kulkarni, the Managing Director of Barclays India. 

The India Cybersecurity Domestic Market 2023 Report by the Data Security Council of India states that enterprises have increased their data security budget over the last few years. Here are some technologies and strategies organisations they are investing in:

• Zero-Trust Architecture: Traditional security models require verification from external users, but internal users can easily access the network. Zero-trust architecture is a network security model that requires external and internal agents to verify their identity to access the network, preventing unauthorised access and fraud risk.
• SOC/Next-Gen SOC: The Security Operations Center (SOC) is a centralised team that monitors, detects, and prevents cybersecurity breaches. Businesses use SD-WAN for SOC to get better visibility of operations across the network and promptly identify potential breaches.
• Security Audits and Assessments: This involves periodic network and hardware assessments of an enterprise to identify cybersecurity vulnerabilities.
• CNAPP: The Cloud Native Application Protection Platform (CNAPP) is a consolidated tool or platform that provides workload protection and data security.
• SD-WAN Network Security: SD-WAN is an advanced network infrastructure that allows seamless and secure collaboration and data transfer across different applications used in remote locations.
• Privacy by Design: It is a cybersecurity framework that focuses on implementing robust privacy policies and technologies in the initial stages of application development.

The Final Word

BFSI organisations leverage AI, ML, blockchain, and cloud technologies to grow their businesses. However, these technologies pose data privacy and security risks, making customers and organisations vulnerable. 

Therefore, banking and financial enterprises are switching from traditional networks to SD-WAN. This evolved network infrastructure enables organisations to achieve digital transformation goals and data security. 

An SD-WAN solution facilitates seamless data flow through load balancing and application prioritization. With 58% of businesses intending to deploy it within the next two years, SD-WAN’s speed and cost-effectiveness make it the clear choice for organizations aiming to stay competitive. 

With its SD-WAN, Airtel offers BFSI enterprises agility while reducing overall WAN costs, enabling them to transition to a future-ready SASE architecture. 

Scale your business today by exploring Airtel’s SD-WAN solution.