Mogo incorporates AI to speed up support for borrowers in Kenya

Mogo, Head of Public Relations, Becky Ngigi

Motorcycle and smartphone financier, Mogo has deployed the use of artificial intelligence to drastically reduce customer waiting times, with the technology now resolving up to 80% of routine calls without human intervention.

Mogo, Head of Public Relations, Becky Ngigi says introduction of an automated phone menu and an AI-powered voice agent has reduced calls reaching its customer service queue from between 70,000 and 80,000 to fewer than 60,000, even as its customer base grew by 100,000.

“As a FinTech company, innovation is essential to how we serve our customers,” said Becky.

The AI tools, which respond to queries in English and Swahili, are designed to help customers resolve common issues faster while allowing call centre staff to focus on more complex cases.

About 1,000 customers use the automated phone menu each day to retrieve PINs needed to unlock their phones, according to the company.

For boda boda riders who rely on motorcycles for their livelihoods, quicker access to payment information and customer support can help minimise disruptions to their businesses.

Financial services providers in Kenya are increasingly adopting the use of AI to automate processes, strengthen risk management and improve customer experience.

A 2025 Central Bank of Kenya survey found that half of the financial institutions had adopted AI. Among those using the technology, 65% applied it to credit risk assessment, 54% to cybersecurity and 43% to customer service.

Becky says Mogo’s voice agent can collect information about a missing M-Pesa payment and forward the case to a human representative with a summary, reducing the need for customers to repeat details. Despite this, customers can request human assistance at any stage.

One thought on “Mogo incorporates AI to speed up support for borrowers in Kenya”

  1. My bank has a similar issue where the automated system misdirects calls frequently. This particular tech integration seems unlikely to handle complex financial queries accurately.

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