How Moneyview uses Ema: 10xing Customer Support at a Large Fintech Company

Moneyview is a popular digital lending and savings platform based in India, with more than 45 million app downloads and $1.4B in loans disbursed. A financial services unicorn, Moneyview offers personal finance management tools and instant personal loan services to enhance financial inclusion and accessibility for a diverse customer base across India.

As Moneyview rapidly grew, so did the queue of customer support queries from its diverse customer base across India:

• Multilingual support, and bot distrust: a large segment of customers required support in non-English local languages. The lack of multilingual chatbots — combined with users' inherent distrust of bots — made automating support extremely challenging, despite the repetitive nature of the queries.
• Cyclical volume spikes at the most delicate moment: query volumes surge around monthly loan repayment deadlines in the first week of each month — payment failures, extension requests, payment confirmations. These are anxious moments for customers concerned about their repayment status, who expect quick responses. Hiring more agents wasn't viable: the extra hires would sit idle for the rest of the month.
• The internal automation attempt fell short: Moneyview built non-generative ML models to predict ticket categories and subcategories linguistically — but these had limited utility, with low accuracy even for that narrow categorization task.

While looking for a more reliable and accurate way to improve customer experience, Moneyview decided to pilot Ema's Customer Support Assistant AI Employee.

Witnessing Ema's integration into our customer support has been nothing short of revolutionary. Ema's Customer Support AI Employee not only assists our support specialists to expedite response time to customer tickets but also ensures accuracy and appropriateness in tone, a critical factor given our diverse customer base. In a landscape where simplicity and clarity are paramount, Ema shines by delivering fast and precise answers using straightforward language, accommodating our non-native English-speaking customers seamlessly.

Venkatraman Narayan

Head of Customer Experience, Moneyview

Ema adapted to Moneyview's unique context with remarkable speed, an AI Employee automating customer support with the appropriate tone, in multiple languages:

• Learning from the same sources as human agents: Moneyview provided Ema with the knowledge base its agents trained on and relied upon, along with millions of past tickets to derive insights from.
• Categorize, then resolve: Ema predicts the right categorization and then generates a quality response, succeeding where the earlier internal models couldn't even categorize accurately.
• Truly multilingual: Ema understands Hindi and Hinglish queries alongside English, in the straightforward language Moneyview's non-native English-speaking customers need.
• A colleague, not a bolt-on: Ema integrated directly with Moneyview's Freshdesk instance with the same access rights as her human colleagues, assisting support agents by suggesting responses to reach resolution quickly.

With over 70% of tickets being answered automatically by Ema in the first few weeks of the pilot, it was obvious that Ema's AI Employees were perfectly suited to the task:

• 70%+ of all tickets resolved automatically with accurate, well-toned responses
• Calm at the most stressful moments: instant, accurate answers to repayment-deadline questions improve customer experience and build a more trusted brand, driving higher retention over time
• Seasonality, solved sustainably: high automation rates absorb the monthly volume spikes without idle headcount, greatly reducing operational costs