In an exclusive interview, Dheeraj K Janbandhu, Senior Vice President of IT and Business Group, Indian Bank, speaks about his organisation’s groundbreaking digital transformation journey. Indian Bank has been at the forefront of integrating innovative technologies to enhance customer experience and operational efficiency. Janbandhu highlights the pivotal initiatives that have propelled the bank’s digital strategy, from the successful implementation of Project WAVE to collaborations with fintech companies and the adoption of advanced cybersecurity measures. The interaction also focuses on how Indian Bank is leveraging AI and machine learning to improve fraud detection, credit scoring, and personalised customer experiences, and how blockchain technology is reshaping secure transactions and transparent operations. He also discusses the bank’s efforts to support customers in adopting digital banking services, ensuring that no one is left behind in this digital revolution.
How does Indian Bank’s digital transformation strategy enhance customer experience and operational efficiency?
Indian Bank decided to embark on a digital transformation journey as early as 2022. Various teams under different portfolios and action work have been proposed to accomplish this task. The Task Force Project was formed and named “WAVE” – a World of Advanced Virtual Experience for employees and customers. Project WAVE has the following aspirations under various parameters: Revenue Enhancement, Cost Reduction, Productivity Increase, Customer Satisfaction, and People Engagement. During this task force, various journeys have been undertaken for the customer segments like Retail, Agri, and MSME, shortly called the RAM sector.
The customer-initiated journey like “PAPL” – Pre-Approved Personal Loans – has been introduced, which became a hit product among bank customers. As per eligibility and terms and conditions, the customer can apply for and receive account credit in just three clicks through PAPL. The maximum amount is INR 5 Lacs, a complete STP journey initiated by the customer through the mobile app or Internet banking. In addition, customer experience has also been enhanced in agri and MSME journeys where customers can initiate and complete processes, such as MSME renewals, online.
For operational efficiency, key initiatives taken are embedded finance, account aggregator, chatbot I-Help, cloud migration, and generative AI. Due to these digital initiatives for customers, the bank has achieved 14X growth in the year 2023-24 to INR 81,200 cr compared to INR 5,600 cr in the year 2022-23 in digital business.
How is Indian Bank collaborating with fintech companies to integrate innovative technologies and stay competitive in the digital landscape?
Indian Bank collaborates with fintech companies to build systems on its legacy infrastructure, which would otherwise take years to develop. This collaboration offers a wide variety of services and products quickly. Technologies brought in by fintechs, such as blockchain, artificial intelligence, and data analytics, have significantly impacted financial services, including deposits, lending, remittances, credits (B2B and P2P), underwriting, insurance, and cryptocurrencies.
The bank sees fintech partnerships as collaborations or joint ventures, working together to develop more products and services or entering into revenue-share agreements. These partnerships benefit both parties by integrating cost-effective solutions into existing infrastructure, making financial services more affordable and attractive.
Indian Bank has drafted and approved a Fintech Collaboration and Implementation Policy for engaging with Fintech companies. This allows the bank to integrate data analytics tools to process and analyse large amounts of financial and customer data, improving product and service offerings. Fintech innovation enhances customer retention through convenience and speed, offering personalised experiences through AI and big data services. By partnering with fintechs, the bank aims to unlock new revenue streams, optimise supply chains, and foster a more agile and resilient organisational structure.
What advanced cybersecurity measures has the Indian Bank implemented to protect customer data and secure digital transactions?
Cybersecurity is essential for protecting your data and systems in this digital age. Cyber threats and attacks have become increasingly common and sophisticated, making it essential to take the necessary security measures to protect yourself. As cyber threats become more sophisticated and commonplace, it is essential to ensure that your data and systems are secure. Cybersecurity is critical not only to protect your confidential data but also to protect the reputation of your organisation. A data breach or cyber attack can have serious consequences, such as financial losses, legal repercussions, and damage to your reputation.
To protect the data, the basic way of protecting data is through encryption. The bank employs the principle of encrypting data at Rest and in Transit: encrypt all sensitive data, both during transmission and when stored. Manage encryption keys properly: use a secure system to generate, store, and handle keys. Rotate keys regularly and don’t store them with the data they encrypt.
Cybersecurity is the practice of protecting networks, systems, and programs from digital attacks. These attacks are usually aimed at accessing, changing, or destroying sensitive information, extorting money from users, or interrupting normal business processes. Cybersecurity is essential for any system that stores, processes or transmits confidential data, such as financial information, personal records, or intellectual property.
To protect customers’ data and systems from cyber threats, the bank is taking the necessary security measures. These measures include:
- Firewall and antivirus protection
- Password management
- Encryption
- Other data protection methods like Data Loss Prevention (DLP), Security Awareness Training, and Cyber Security Incident Response (CSIR).
- Network and Vulnerability Management: Deploying a network discovery and vulnerability management solution that identifies, prioritises, and provides real-time insights.
- Digital forensics: Implementing an integrated digital forensics solution that automates evidence collection, accelerates investigations, simplifies workflows, and reduces response times.
- Onboarding, training, and deployment service: Guided onboarding, deployment, and training advisory service with a structured methodology to ensure quick setup and sustained success with the enterprise solution.
Data security and compliance are two sides of the same coin, hence deploying proper and applicable compliance regulations such as GDPR, SOX, PCI, HIPAA, etc. The bank is undertaking foundational security measures for digital payments and transactions as follows:
- Encryption
- Tokenization
- Secure payment gateways
In addition to the above, the bank is deploying advanced authentication methods for secure online transactions:
- Two-Factor Authentication (2FA): 2FA adds an extra layer of security by requiring users to provide two different authentication factors to verify their identity. This method significantly reduces the risk of unauthorised access.
- Biometric verification: Biometric verification methods, including fingerprints, facial recognition, and voice authentication, offer a higher level of security than traditional passwords by leveraging unique biological characteristics.
- Customer trust and transparency: Communicating security measures effectively to customers can significantly enhance trust.
- Emerging technology and future trends: Offering sophisticated tools to identify and prevent fraudulent activities. Keeping abreast of these technologies and trends is essential for future-proofing payment security measures
How are AI and machine learning being utilised in Indian banks to improve services such as fraud detection, credit scoring, and personalised customer experiences?
Fraud detection is a vital and very important area in the financial and banking sector. Machine learning systems can detect fraud by using various algorithms to sift through massive volumes of data. The bank is implementing these systems and algorithms to monitor transactions, keep an eye on client behavior, and log information to extra compliance and regulatory systems to help minimise overall risk regarding regulatory compliance.
The bank uses AI services and AI technology to flag identity theft by analysing vast amounts of data in real-time and recognising patterns. This proactive approach enables banks to identify and prevent fraudulent transactions before they occur. The bank is in an advanced stage of implementing AI and machine learning tools to help identify fraudulent activities, track loopholes in their systems, minimise risks, and improve the overall security of online finance.
One of the most common applications of AI the bank is using in customer service is chatbots and voice assistants. These software programs can interact with customers through text or speech, using natural language processing (NLP) and machine learning (ML) to understand their queries and provide relevant responses. AI is used in banking to enhance efficiency, security, and customer experiences. It automates routine tasks like data entry and fraud detection, reducing operational costs. AI-driven chatbots provide 24/7 customer support.
The bank is harnessing AI tools and techniques to elevate the mobile banking experience and net banking experience of the customers. Through this, the bank can offer the following features to the customers:
- Personalised banking services
- Enhanced security features
- Improved customer support
- Efficient transaction processing
- Advanced analytics for better decision-making
With advancements in AI, the bank believes that AI can drastically change customer service in banking if implemented properly. These improvements can be achieved using the following models or methods:
- Chatbots and voice assistants: These software programs can interact with customers through text or speech, using natural language processing (NLP) and machine learning (ML) to understand their queries and provide relevant responses. Chatbots and voice assistants can handle simple and repetitive tasks, such as checking balances, transferring funds, booking appointments, and answering FAQs, without human intervention. This can reduce waiting times, operational costs, and human errors while increasing customer satisfaction and convenience.
- Sentiment analysis and feedback: Sentiment analysis is the process of using NLP and ML to identify and extract the emotions, opinions, and attitudes of customers from their texts, speech, or facial expressions. Feedback is the process of collecting and analysing customer ratings, reviews, comments, or suggestions. By combining sentiment analysis and feedback, banks can gain insights into how customers feel about their products, services, or interactions, and what they need or expect from them. This can help banks improve their customer service quality, tailor their offerings, and increase customer loyalty and retention.
- Fraud detection and prevention: AI can improve customer service in banking by enhancing fraud detection and prevention. Fraud is a serious threat to the banking industry, as it can cause financial losses, reputational damage, and legal issues. AI can help banks detect and prevent fraud by using ML and data analytics to identify patterns, anomalies, and behaviors that indicate fraudulent activities, such as identity theft, money laundering, or phishing. AI can also use biometric authentication, such as face recognition, fingerprint scanning, or voice verification, to verify the identity of customers and prevent unauthorized access. This can improve customer service security, trust, and compliance.
- Personalised recommendations and advice: AI can improve customer service in banking by providing personalised recommendations and advice. AI can use ML and data mining to analyse customer data, such as demographics, preferences, behaviors, and transactions, to create customer profiles and segments. Based on these profiles and segments, AI can offer personalised recommendations and advice to customers, such as products, services, offers, or tips that suit their needs, goals, or interests. This can improve customer service relevance, value, and engagement.
- Robotic Process Automation and workflow optimisation: AI can improve customer service in banking by using Robotic Process Automation (RPA) and workflow optimisation. RPA is the use of software robots or bots to automate repetitive and rule-based tasks, such as data entry, verification, or reconciliation, that normally require human intervention. Workflow optimisation is the use of AI to streamline and improve the efficiency and effectiveness of business processes, such as customer service, sales, or marketing. By using RPA and workflow optimisation, banks can reduce manual work, errors, and delays while increasing productivity, accuracy, and speed.
AI ethics and challenges must also be addressed as the bank continues to integrate AI technologies to ensure responsible and fair use of AI in customer service and other banking operations
What role does blockchain technology play in your bank’s digital transformation efforts, particularly in areas like secure transactions and transparent operations?
Blockchain uses cryptography and Public Key Infrastructure (PKI). Every transaction on the blockchain is secured with cryptographic principles, ensuring data integrity and authentication. Public Key Infrastructure (PKI) grants users a public key to receive assets and a private key to safeguard them. Blockchain uses a distributed ledger that records transactions and data identically in multiple locations. All network participants with permission access see the same information at the same time, providing full transparency.
As blockchain technology is one of the techniques where all transactions are traceable and non-repudiable, it reduces the possibility of financial misdeeds. Banks will be relying on these systems. However, use cases and practical business applications in the real financial sectors are still limited, and the adoption and implementation rates are on the lower side. After evaluating which business verticals and processes are most suitable, the bank will decide to implement this in various applications.
What initiatives are in place to encourage and support customers in adopting digital banking services, especially among those less familiar with technology?
Adopting digital banking services, especially by customers who are less familiar with the latest technology, is a challenge for every bank. Taking note of this, the bank is taking various steps to enable and empower such customers. The technology initiative helps to quantify the active element of web-active end users. The idea of this initiative includes three facets: active technology adoption, active technology assimilation, and active technology dissemination.
Technology alignment workshop: Organisations need to ensure their technology initiatives meet business needs. In an alignment workshop, participants explore their business goals and strategies and the planned technology initiatives and look at which initiatives achieve which goals and strategies. During various customer meets, participants are informed about the technology products and their use and need to operate for the benefit of the customers. Many customers may not be well-versed with the technology apps, and they need to be educated about them and how to operate them. Regular seminars and workshops are organized at the branch and zonal office levels to promote education among such users.