The impact of AI and advanced analytics on labor costs

Across all industries, businesses continue spending money on unnecessary labor costs, particularly on the heels of the COVID-19 pandemic. Significant staffing shortages over the last couple of years have raised the cost of labor. According to some estimates, private-sector labor costs in the United States will increase by 4.4 percent in 2021. That figure is double – at about 8 percent – in the leisure and hospitality sector.

The industry has found that it can deploy artificial intelligence and advanced analytics to manage costs, including using bots to replace expensive human labor. We are seeing a new wave of advanced automation capable of performing 10 to 25 percent of work across bank functions, allowing employees to focus on higher-value tasks.

The challenge for banks is finding the best way to get started. Some have seen significant downsides to scaling automated services, lacking the resources and capabilities to monitor the technology and ensure it performs effectively. But others have seen tremendous success stories.

HDFC Bank Limited is an Indian banking and financial services company headquartered in Mumbai, Maharashtra. Given the organization’s explosive growth, it had trouble finding the time and resources needed to scale the contact center and meet customer expectations. So, like many other major banks worldwide experiencing exponential growth, it was looking for a self-service solution that could address customers’ questions instantly.

Senseforth has been working with HDFC Bank since 2017 when they collaborated to launch a chatbot known as “EVA” (Electronic Virtual Assistant). Progress has been gradual, with the addition of various features and the extension of this virtual assistant to address popular user issues.

The Senseforth solution

• EVA (Electronic Virtual Assistant)

The initial Senseforth strategy

• Knowledge gathering: The company shortlisted frequently asked questions and had responses prepared.
• Scenarios: EVA is prepared to handle numerous scenarios involving customers’ common requests for their banking needs.
• User feedback: The application gathers data on its performance based on user feedback to learn and improve.
• Analytics: EVA’s responses improve through the analysis of conversational data.
• Additions: EVA became better prepared to handle common consumer scenarios and learned responses to those over time.

The Senseforth impact

• This chatbot addressed over 2.7 million customer queries in six months and became India’s largest banking chatbot.

What we provided

Empowering customer service: The technology behind EVA’s 85% accuracy rate EVA was built with an accuracy level of over 85 percent by using Senseforth’s comprehensive conversational artificial intelligence platform, which is deeply integrated with its patented natural language processing engine.

This technology helps computers understand human language. With it, the bot can understand English and Hindi, is trained to understand and respond to around 8,000 customer scenarios, can address frequently asked questions, and can execute transactional requests related to accounts, credit cards, loans, and other products.

The immediate impact

Millions of conversations and reduced overall support costs

The ongoing impact

● Millions of questions addressed

● Implementation and training time reduced from over 70% while maintaining high levels of accuracy.