RBI backs AI use for customer grievance resolution

Sanjay Malhotra, the newly appointed Governor of the Reserve Bank of India (RBI), has announced plans to incorporate technology, including artificial intelligence (AI), to improve customer grievance redressal processes and make them globally competitive. Integrating AI throughout the process, from complaint submission to resolution, makes the system more streamlined, efficient, and data-driven. This approach is expected to not only shorten processing times and address recurring issues but is likely to also ensure fairer outcomes by reducing human biases.

However, the RBI chief cautioned that as the Indian banking sector adopts AI for grievance redressal or other functions, financial institutions must prioritize ethical standards. AI systems must include human oversight, bias mitigation strategies, and strong data privacy measures to guarantee transparency and consistent results.

“We are entering an exciting era where technology, particularly artificial intelligence (AI), can drive remarkable improvements in speed, accuracy, and fairness of complaint resolution,” Malhotra said at the annual conference of the RBI Ombudsmen.

The Reserve Bank has been organizing this conference on or around World Consumer Rights Day, which was celebrated on March 15, intending to raise global awareness about consumer rights and needs. Malhotra said that the RBI organizes this conference to reflect on the central bank’s achievements in consumer services and deliberate on improving services and reducing grievances.

“It is time that the banking industry explores and pioneers the integration of technology—including AI—to strengthen the grievance resolution mechanisms and make it best in class across the globe,” he added.

“AI can help categorize incoming complaints by urgency, complexity, or subject area, ensuring minimal delay in reaching the right people or the right team. AI can also help in optimising complaint routing. Further, it can assist in decision-making and reducing processing time.”

Additionally, AI can identify systemic issues by analyzing structured and unstructured data, such as emails, chat logs, and call transcripts. This analysis helps recognize areas where training is needed. By leveraging data from millions of consumer interactions—such as branch visits, call center logs, mobile apps, and social media—AI can provide a comprehensive view of these interactions, making it easier to spot recurring issues.

According to the RBI chief, through data analytics, sentiment analysis, and predictive modeling, AI can sift through vast amounts of data to detect trends, like sudden increases in ATM failures or billing errors, and provide early alerts to relevant teams.

Finally, in a country as linguistically diverse as India, Malhotra stated that AI-powered chatbots and voice recognition technologies can bridge language gaps by functioning in local languages. The deployment of conversational AI in chatbots, voicebots, and advanced IVR systems can handle routine inquiries around the clock, allowing human agents to focus on more complex cases that require empathy and problem-solving skills.

The warnings

While AI presents unparalleled opportunities, Malhotra pointed out that the financial industry needs to be cognizant of the challenges and risks that its adoption poses.

“There are concerns on data privacy, algorithmic bias and complexity in AI-driven models. As we embrace AI in grievance redressal or any other process, we must also remain mindful of ethical considerations. Human oversight, bias mitigation and data privacy must be integrated into the AI systems to ensure transparent and consistent outcomes,” the RBI governor warned.

In December, the RBI announced its plans to set up a committee to develop a framework for the ethical enablement of AI for the finance sector. In January this year, the RBI announced the composition and scope of work for the expert committee. The committee, comprising experts from diverse fields, is tasked to recommend an adaptable and robust AI framework for the financial sector.

The RBI has also introduced an artificial intelligence/machine learning (AI/ML)-based model, MuleHunter.AI, developed by the Reserve Bank Innovation Hub (RBIH), to tackle digital fraud. The AI model is also expected to help banks deal with the issue of mule bank accounts, a typical tactic fraudsters use to funnel the proceeds of their fraudulent activities.

‘To invest in training of staff’

While technology in all its forms is a powerful tool, Malhotra stressed that it cannot replace integrity, empathy, and human judgment. In a world increasingly influenced by data, algorithms, and automation, it’s easy to overlook the human aspect.

“Every transaction represents not just a number in a ledger, but the hard-earned savings of a family, the dreams of a small entrepreneur, or the lifelong savings of a senior citizen. It is, therefore, critical that RBI-regulated entities continue to invest in human resources dedicated for customer service and grievance redressal,” Malhotra pointed out.

“It is essential to invest in training of staff, especially in behavioural aspects of customer service. Moreover, the staff needs to be empowered to take decisions based on their judgement to redress consumer grievances, enhance customer satisfaction and win consumer trust,” he added.

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