Grab’s Path to Profitability Paved by Operating Leverage and AI

In a dynamic operating environment, the path to profitability requires focus and discipline.

It also frequently requires cutting costs and finding new efficiencies by using technology.

Singaporean super app Grab reported earnings results Wednesday (May 15), announcing a record adjusted core profit and raising its annual forecast. On a call with analysts, the company cited its “relentless” efforts to cut costs, as well as the impact of artificial intelligence in optimizing its operations.

“We continue to exercise stringent discipline as we drive greater operating leverage in the business,” Grab Chief Financial Officer Peter Oey told investors on the call.

Grab’s first-quarter 2024 revenue grew 24% year over year to $653 million, which the company attributed to growth across all segments. Grab’s adjusted core profit hit a record high of $62 million.

The company updated its full-year 2024 adjusted core profit guidance from a range of $180 million to $200 million to a range of $250 million to $270 million.

Referencing the company’s updated guidance, Oey explained it is being supported “by a combination of costs in our business and how we are continuing to optimize those cost structures.”

“The second part of the cost side is we’re just seeing greater discipline when it comes to operating expenses,” the CFO added.

It is a strategy that PYMNTS has heard repeatedly from other finance chiefs during the “Day in the Life of a CFO” series. Now is the time for smart cost management and smart capital allocation. While growth is still a top focus, profitable growth matters more.

Read also: Grab Users Boost Digital Bank Adoption as Delivery, Ride-Hailing Businesses Recover

Harnessing the Power of Digital Solutions and AI

Grab executives are also betting that new initiatives, including digital banking, will increase the company’s earnings going forward.

“We’re executing on our FinTech strategy … where we said we would focus on ecosystem payments and ecosystem lending where we really knew our customers deeply in a data science sense and that is paying off,” Grab Chief Operating Officer Alex Hungate told investors on the call. “You can see that in the results this quarter.”

“We’re getting a lower cost of payments relative to what we would get from third-party providers and our deep, credit modeling skills using data science where we now actually ingest something like 185 variables in our data models, many of them highly unconventional relative to what a bank could access, and that allows us to grow our book at this kind of rate but maintain an NPL of only 2%,” Hungate added.

“Based on an advantage we have on data in credit underwriting, and frankly, an advantage we have on collections and user acquisition cost,” he said. “That’s a business that we’re confident that we can scale profitably.”

Alternative data sources offer a broader view of an organization’s financial health and can help lenders make more accurate and predictive credit decisions by providing additional insights into their financial behavior, payment patterns and risk factors.

See also: 12 Payments Experts Share How AI Changed Everything in 2023

The company’s executives also stressed to investors that the rollout of an AI translation solution has resulted in cost savings from no longer having to outsource translation services to external vendors.

“By leveraging these in-house models, we reduced translation processing times from 100 days with a vendor to just five days for onboarding any new language regionally,” company executives said on the call. “This allows us to expand language support and meet the needs of diverse travelers as the segment continues to grow.”

“GenAI has been critical in augmenting our ability to solve problems, not just for our users and partners, but also in improving and driving efficiencies among all our teammates,” Grab CEO Anthony Tan said during the call. “It is one of the key reasons we see why we are confident about how we can continuously optimize cost levels in our regional corporate costs.”