In the first week of August, Grab Financial Group announced a slew of new financial service products including a micro-investment scheme and a buy-now-pay-later program tied to spending through its platform. Grab, popularly known as a Singapore based ride-hailing platform, expanding into financial products seems more like a reach than an expansion. But the role it hopes to play in Southeast Asia’s (SEA) increasingly digital market makes a lot more sense when you realise that 70% of SEA’s digitally native population (of 650 million) remains underbanked. This subset of the population doesn’t have direct and easy access to financial institutions, largely due to a lack of financial profiling, but is tethered to digital consumer ecosystems like Grab.
The economic value that remains untapped then becomes a lucrative pool for anyone willing to bridge the underbanked population with financial products and services. For big financial institutions, the incentive is skewed by the risk, where the cost of taking on credit risk in consumer finance outweighs its potential return – here the traditional route is an uphill battle. This unique situation gives rise to an alternative path to banking the underbanked in SEA.
Platforms with multiple touchpoints across the spectrum of consumer behaviour, like Grab, are well placed to become data moats for the financial profiling of these consumers. Grab and Gojek (Indonesian ride-hailing platform) are unexpectedly solving for this information asymmetry and leading the way towards actualising the financial profiling of SEA’s consumers. The platforms have already begun work on adjacencies focusing on fintech products for drivers, merchants and consumers.
Grab, building an ecosystem for financial profiling
To understand Grab’s positioning as a financial service provider, we need to contextualise it within the broader consumer application market. What type of consumer tech is best placed to effectively mine data around its customer’s financial profiles?
Broadly speaking, there are three types of applications that have a pervasive enough reach to attempt this:
- Messaging and social media applications (Line, WeChat, Whatsapp etc)
- Ecommerce platforms (Lazada, Carousel, AliExpress etc.)
- On-demand utility services (Grab, Gojek, Deliveroo, FoodPanda etc.)
What makes any one of these a better candidate than the other, is the optimal combination of two key factors.
- Frequency: How frequently users engage the platform
- Consumption Behaviour: whether engagement with the platform results in some kind of consumer behaviour e.g. purchase or trade of goods/services
If we abstract the factors, we can think of the frequency of use as the number of data points and consumption behaviour as data classification or category. A messaging or social application, while being one of the most frequently used (high number of data points) revolves around social activity – here the data classification required for financial profiling is not present. On the other hand, e-commerce platforms where activity revolves around consumption (relevant data classification) the frequency is not as significant – the number of data points is limited to the user’s discrete consumption habits. When we look at on-demand utility services, hailing a ride or ordering a meal/groceries, is both pervasive in the number of data points available and apt for the type of data required to financially profile a user.
While ordering a cab or a meal aren’t the strongest or most frequent data points for this purpose, it achieves the necessary minimum for the next iteration of profiling – the introduction of easy to implement financial services. Grab’s touchpoints with consumers are pervasive and consumer-focused enough to do just this. Grab has iteratively built out adjacencies that as interdependent services have helped to build out the financial profiles of drivers, merchants and consumers.
- Stage 1: On-demand utility service
- Stage 2: Driver and merchant services
- Payment system
- Food delivery
- Insurance for drivers
- Financing for drivers and merchants
- Stage 3: Consumer services
- Health insurance
- Pay-later program
Gojek is also on a similar trajectory, however, as the platform services more underbanked regions in SEA the focus is still heavily in Stage 2, with signs of development in Stage 3 consumer-focused services. The most recent indicator of Stage 3 development is Gojek allowing consumer investment in Gold through their platform. However, Gojek’s focus on stage 2, for now, should not be discounted as slow-moving, rather, it is pivotal. The capture of merchant market share will allow Gojek, as gatekeepers to merchants and therefore consumers, to be more competitive against other fintech players. The iterative touchpoints into consumers lives is highly dependent on the robustness of the consolidation in stage 2.
Even as Uber pares back its service to its core ride-hailing platform in the face of the pandemic’s impact, Gojek and Grab are continuing to build out their adjacencies in fintech supported by a significant inflow of capital from the likes of Facebook and Softbank. Most recently Grab secured more than $700 million from Japan’s largest bank, Mitsubishi UFJ Financial Group and $200 million from a private equity firm from South Korea. Gojek has most recently been funded by Facebook and Paypal investments, while the exact amounts were not disclosed, regulatory filings show that Facebook and Paypal own 2.4% and 0.6% respectively of Gojek’s GoPay Fintech arm.
The power of Grab and Gojek lie in creating interdependent ecosystems for the building out of financial profiles rather than discreet services for revenue. An immense amount of value in being the funnel for the underbanked economic potential is available in SEA. The funnel here is defined by the ability to create new demand for financial products as opposed to competing with existing market share within the financial sector of SEA. The parallels to draw from are ecosystems built by Alibaba and Alipay which has manifested itself into Ant Financial Group aiming for an IPO valuation of $200 billion.
Down the Rabbit Hole
1. The transience of users in ride-hailing platforms
“Uber’s revenue generation is directly tied to the cost borne by the consumer, the user is not attached to any unique capital created by Uber.”
“…Where the platform isn’t able to control user acquisition through the provision of unique capital, the user base becomes transient in nature, significantly diluting the incremental value each user brings to the network. A driver on Uber can as easily be a driver on Lyft, and a rider on Uber can easily choose to ride with Lyft instead.”
“Having established that the user base built by Uber is transient, the problem that Uber needs to solve for is creating user stickiness. This attempt then hinges on their ability to create as many touchpoints with their users as possible, increasing the aggregate number of engagements within the ecosystem … This is why Uber (and many other ride-hailing companies) turned to adjacent value propositions like food delivery and fintech.”
“Perhaps ride-hailing can never achieve the asymmetric profitability other big tech ventures enjoy through aggressive user acquisition. Without strong adjacencies that ensure the user capital is consolidated within the Uber ecosystem, transience will always plague ride-hailing as a proposition. Even with the introduction of adjacencies, it is more likely that the adjacencies become profitable enough to sustain a loss-making ride-hailing business rather than vice versa.”
Source: Uber’s strategic decisions plagued by the shadow of its tech valuation – 4th Quadrant
2. How Neobanks utilise behavioural economics
The management of finances whether it is budgeting or investing creates a degree of decision inertia in the average consumer that is not as observable in other facets of life. Behavioural economics principles like “nudging, social proof or loss aversion” can be utilised by fintech providers to create profitable behavioural flows in consumers that can overcome personal finance related decision inertia. The Ross Republic in particular succinctly explores how the concept of “mental accounting” is utilised by fintech start-ups to make their products stickier.
“Mental accounting describes the tendency to categorise income and assets into non-transferable buckets, such as a monthly rent or groceries bucket….[however] money is fungible, i.e. interchangeable and with no pre-set restriction about what it can be spent on…”
Fintech startups are utilising our inherent behaviour to mentally account our income into non-fungible buckets to create intuitive user interfaces.
“Revolut automatically categorize transactions and displays the amount spent and left in their analytics tab in the app. After a user spent money on groceries, a push notification will tell how much money is left for groceries expenses until the end of the month. Hence, users don’t even need to calculate their individual spending anymore and can check their separate ‘mental accounts’ conveniently in the app.”
While the Ross Republic explores the positive behavioural flows from mental accounting to savings and spending behaviour, mental accounting is a narrow perspective on finances that can lead to negative decision making.
“The next level might be that banks even prevent their users from making the mistake that monthly gains or losses are perceived from a narrow mental accounting viewpoint. Bad financial decisions … can be avoided by connecting available money spent or saved in one account in terms of total gains or losses.”
Overall with digital-only platforms, Neobanks can become a hotbed for testing the integration of behavioural economics with personal finance management. This experimentation and outcomes will likely prove to be interesting to both consumers and traditional banks.
Source: How Neobanks utilise behavioural economics – Ross Republic