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Apr 11, 2020

Enabling Financial Inclusion in Asia

CredoLab's CEO & Co-Founder Peter Barcak speaks with Entrepreneur Asia Pacific on Enabling Financial Inclusion in Asia.

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This article originally appeared on Entrepreneur Asia Pacific.

Historically, credit-lending favoured consumers in developed markets over those in less affluent emerging markets. This lack of ability to obtain a credit loan induced a vicious cycle; a lack of loans means consumers cannot build credit scores, in turn making it challenging to secure a loan. Fortunately, AI-enabled alternative credit scoring is upending this, creating opportunities for online lenders and fostering financial inclusion across the region.  

Research by the World Bank indicates more than a billion Asian consumers lack access to mainstream financial services and other corresponding benefits that come hand-in-hand with being ‘banked’. Saying that,  with 51% of Southeast Asian consumers being mobile-first Internet users, smartphones are transforming this. Mobile Internet use enables the creation of new instruments available to assess consumer creditworthiness, opening up access to debt capital markets.

Smartphones’ Role in Financial Inclusion

Smartphones can play a key role in fostering financial inclusion among the global unbanked population, especially in Southeast Asia, where, as previously mentioned, mobile Internet usage has seen tremendous growth. This was observed when CIMB Bank Philippines expanded its consumer base by signing over 1 million customers in 10 months via its all-digital mobile banking platform, propelling it to become an ASEAN regional market leader.

It is predicted that by 2025, the Internet economy of ASEAN may reach US$200 billion. Already, ASEAN leads in mobile Internet use at 3.6 hours per person daily, ahead of China (3.0 hrs), the USA (2.0 hrs) and the UK (1.8 hrs). In the Philippines, where 77% of the population of 105.7 million as at 2018 is unbanked -- with 67 million Internet users -- CIMB Philippines leveraged anonymized metadata from customers’ mobile phones to underwrite customers for personal loans. This aided the bank in enabling a seamless underwriting process and extended credit to a broader market without impacting the cost of risk.

Smartphone metadata has great promise to advance financial inclusion. Analysts can glean behavioural insights into consumer behaviour, and by using this data, they can then convert consumers into customers. These insights relate to the willingness to pay back a loan, as well as loyalty, behavioural consistency and ethical standards.

An Accenture study estimates that banks who improve accessibility for underbanked stand to generate an estimated $380 billion in annual revenues, there is substantial financial opportunity that financial institutions (FIs) can capitalise on.

Platforms that can enfranchise the under-banked and unbanked generate new opportunities and build brand strength. Customers on such platforms will come to associate the financial brand with the financial instruments and opportunities they can then access, creating a virtuous cycle centered on the financial brand.  

Trust and Cybersecurity

Financial institutions (FIs) and fintechs need to emphasise greater transparency -- and therefore trust -- in their business, alongside security, given the sensitive personal and financial information they store. While transparency is a key element in building trust, it does not automatically build trust, requiring mindful communications that are purposeful and grounded in ethics.

Without being self-serving or violating confidentiality, thoughtful transparency creates an information environment where people can trust they'll be able to access pertinent information to operate with integrity and make informed decisions, as well as enter genuine professional relationships. With the mean cost for a data breach in ASEAN for an organisation amounting to S$3.6 million in funds and 22,500 records per breach being compromised, security is paramount to maintain trust.

Trust -- a crucial differentiator -- is more important as regulators worldwide implement data privacy standards. For businesses, this means secure systems and processes must be underwritten by the intangible of trust.  FIs need to assume a breach will occur and plan to mitigate damage, given that preventing an attack is impossible; consumers interact with their money in diverse ways and hackers will eventually find a way.

If end-users fail to see any benefit and security in a new innovation, then it will not achieve a meaningful outcome. Revenue cannot be traded for trust in the long run, so customers must be able to control the quantity of data accessed; have transparency of how that data is used, and be able to explicitly consent to data access. All this is part of sustaining trust.

Only using secure measures from the start, keeping customers in the loop to minimise indirect costs; minimizing the data accessed and anonymizing it where possible; as well as encrypting it, can only benefit companies. The investment in compliance might be tedious, but the yield in customer trust is compelling.

AI-enabled Credit Scoring

With increased investment in artificial intelligence (AI) -- a PWC study found most financial services decision-makers pursuing AI investments -- the main business advantages arising from AI are its enablement of 24/7 mobile banking and its augmentation of security and fraud detection. Part of a wave of technologies that includes blockchain, robotic process automation (RPA), and cloud computing in financial services, the key is leveraging to pull actionable information from unstructured data.

The advantage of AI-based credit scoring systems over traditional systems is their capacity to unearth hidden relationships between variables that are not always apparent to traditional credit scoring systems, as well as conducting a more nuanced evaluation of data. AI can provide complex, in-depth rules. Meanwhile, traditional credit scoring models employ simple rules, often rejecting borrowers who may otherwise be credit-worthy. Self-learning credit scoring models can continuously improve themselves via machine learning (ML) as new data feeds into the system.

This opens the case for alternative credit scoring, which is critical to serving the unbanked. For consumers, this facilitates access to homeownership and consumer credit opportunities, as well permitting small businesses to access debt capital.

This also establishes a compelling case for digital scorecards’ usability across different verticals, as the symbiotic relations that develop in financial services translates across industries. For instance, it can be deployed by travel booking companies, ride-hailing services, and e-commerce operators. The behavioural insights gleaned from metadata also have sector-agnostic applications.  

Disrupting the high cost of credit assessment and verification is fundamental to facilitating financial inclusion. Financial identities for consumers translate to a larger customer base, with the potential to tie them into various ecosystems and rotate customers between services, as firms like Grab have done.  Expanding from transport services into deliveries, financial services, and retail wealth management in Southeast Asia, services like Grab Finance highlight the potential of alternative credit scoring for driving both business growth and financial inclusion at a macro level throughout the region.