This article delves into the world of digital transformation in banking, focusing on alternative credit scoring, its objectives, AI and regulatory frameworks’ pivotal role in financial inclusion.
December 19, 2023
12 minutes
Shuant Goh
Alternative credit scoring is making waves in the digital transformation in banking. It’s a revolutionary approach reshaping how financial institutions assess creditworthiness, helping credit or lending companies, primarily banks, mitigate losses with a robust assessment of borrowers’ credit risk. Alternative credit scoring is made possible by the remarkable surge in digital consumption and the widespread digitization of financial systems.
As smartphones and internet usage become more widespread, they leave behind valuable digital footprints, paving the way for a groundbreaking approach to credit assessment. The broader digitization, highlighted by the growth of micro-financing through online lending, Buy Now Pay Later (BNPL) platforms, e-wallets, telco services, and messaging apps, is not just altering how financial transactions take place—it's unlocking a wealth of accessible data unprecedented in scale.
This article delves into the world of digital transformation in banking, focusing on alternative credit scoring, its objectives, AI and regulatory frameworks’ pivotal role in financial inclusion.
Traditional credit scoring relies on a limited set of variables, such as credit histories, transactions, and loan repayment, often excluding individuals with no credit history. The coverage becomes even more restrictive in countries with high unbanked or underbanked populations. For instance, over 70% of Southeast Asia’s population is unbanked or underbanked, where top countries contributed to the percentage include Vietnam (79%), the Philippines (78%), and Indonesia (77%) (source: National Geographic).
Alternative credit scoring is a paradigm shift from traditional methods.
It broadens the scope by incorporating diverse data sources beyond income and credit history, namely
Leveraging these unconventional data sources to evaluate an individual’s or business’ creditworthiness, it also provides a security net for fraud risks. By embracing alternative credit scoring, the aim is to empower those excluded from traditional banking systems, providing them access to loans and financial services. It strives to achieve financial inclusion and digitization of the unbanked. This shift allows for a more comprehensive evaluation, ensuring a fair assessment of creditworthiness.
All types of financial institutions, be it banks, peer-to-peer (P2P) lending or any digital platforms with microfinancing capacity, including BNPL, can benefit from a robust credit scoring model. What’s more, it offers better visibility to avoid loan stacking. Here are the advantages of alternative credit scoring that give financial institutions a competitive edge.
Addressing the unbanked issue is at the core of alternative credit scoring. With new alternative data, previously overlooked individuals are now visible in the credit ecosystem. This means:
AI fundamentally transforms the accuracy and efficiency of decision-making—smarter, more accurate, and more efficient. These technologies streamline decision-making, reducing processing times and improving overall effectiveness. Here’s how:
Alternative data contributes to financial inclusion by providing opportunities for individuals with limited or no traditional credit history.
This actively works towards creating a more equitable and accessible financial landscape, ensuring that a broader spectrum of individuals can participate in and benefit from the formal financial system.
There are always two sides to everything. Having explored the myriad advantages of alternative credit scoring, we now focus on the intricate challenges and risk factors accompanying this transformative journey.
As alternative credit scoring relies heavily on diverse data sources, ensuring the privacy and security of this information becomes paramount. Stricter data protection regulations, such as the GDPR in Europe, demand meticulous attention to how personal data is collected, stored, and utilized. Instituting robust encryption measures and secure data storage protocols is a regulatory requirement and crucial for building and maintaining trust with consumers.
Embarking on the journey of alternative credit scoring introduces financial institutions to a complex regulatory landscape—where innovation must harmonize with stringent compliance requirements. The evolving nature of technology often outpaces existing regulations, leading to a delicate balancing act that institutions must master. Regulatory bodies tasked with safeguarding consumer rights and financial stability grapple with the rapid advancements in alternative credit scoring methodologies. The challenge lies not only in updating existing regulations to accommodate these innovations but also in anticipating potential risks and mitigating them proactively.
Often, the regulatory challenges include:
AI and machine learning (ML) in alternative credit scoring bring exciting advancements but also pose ethical challenges. Recognizing and addressing biases in these systems is crucial for trust and fairness.
Here are the key concerns:
Embracing digital transformation in banking presents hurdles, but proactive strategies can turn challenges into opportunities.
Addressing challenges in data quality and diversity is crucial for a comprehensive understanding. Ensuring a holistic view through effective data management enhances the reliability of credit scoring models.
Proactively engaging with regulators ensures the scalability of credit scoring models to align with the latest regulations. This approach helps financial institutions stay ahead, fostering a harmonious relationship with regulatory bodies.
Implementing continuous monitoring, learning, and keeping data collection up to date are pivotal in reducing bias. This proactive stance contributes to the ongoing refinement of credit scoring models, promoting fairness and accuracy.
Choosing a solution provider that offers flexible infrastructure options is key. There is an array of tools at their disposal to tailor their credit scoring approach. Whether opting for a generic score, customized score, joint modeling, or traditional score, flexibility ensures adaptability to evolving needs in the dynamic digital transformation landscape.
Generic Score: Off-the-shelf fraud score, credit score, and telco score
Customize Score: Solution provider's data and scoring for the client to create a combined strategy with the agreed features
Joint Modeling: A combination of solution provider's and client's data to create a credit scoring model with the agreed features
Traditional Score: Solution provider to strategize credit scoring model solely based on client's data with the agreed features
The journey of digital transformation in banking through alternative credit scoring is just the beginning. As financial institutions continue to innovate, collaborate, and address challenges, the future holds a promise of increased financial inclusion and a more resilient, efficient, and equitable banking ecosystem. TrustDecision aims to be part of the equation in helping financial institutions embrace the transformation. With technological innovation that centres around people, together we can transform lives and shape the future of finance.
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TrustDecision empowers businesses with AI-driven decision engine designed for fraud prevention, credit risk decisioning and ensure regulatory compliance. It leverages on machine learning models and big data capabilities to deliver real-time risk insights with accuracy and automate decision-making process to deliver maximum operation efficiency.
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