Data-as-a-Service: a new frontier for credit decision-making
The fintech industry in the Philippines has steadily grown due to technological advancements and improved internet penetration in the country. Studies indicate that Internet users in the Philippines grew by 2.1 million between 2021 and 2022. With these developments, it is only natural for businesses, especially financial institutions, to adapt to new models – those who use traditional and alternative data for a more precise and accurate. inclusive risk assessment. This could reduce reliance on traditional, rigid models and subjective valuation by fallible managers and underwriters.
Bharath Vellore, Managing Director, Asia-Pacific, Provenir spoke to The Manila Times about how Data-as-a-Service cloud software could help the banking and finance industry gain a better understanding of credit risk to that financial institutions can better serve the unbanked sector of society.
The Manila Times (TMT): Please introduce Provenir.
Bharath Vellore (BHV): Provenir is a global leader in artificial intelligence (AI)-based risk management software. We enable fintech and financial institutions to make smarter risk decisions faster. Our AI-powered business intelligence platform uniquely combines universal access to data, simplified AI, and sophisticated business intelligence technology. This provides a cohesive risk ecosystem to enable smarter decisions throughout the customer lifecycle, and Provenir is available globally.
TMT: What is Data-as-a-Service (DaaS) and how can Provenir Marketplace and Data Cloud power organizations?
BHV: Like all other cloud services, Data-as-a-Service is cloud software that allows organizations to access specific types of data when they need it. Instead of being stuck in disparate systems across the organization, DaaS allows data to be used across the organization. Data integrity, cost savings, automatic updates, and maintenance are just a few of the benefits offered by DaaS.
Provenir Marketplace is a single hub and access to traditional fraud, credit, identity, open banking and alternative data. This data, from the convergence of many providers around the world, is offered in an easy-to-use cloud solution. By simply selecting specific data sources, users can create rich, personalized datasets that best meet business needs.
TMT: What is alternative data in credit risk scoring and how is it similar or different from standard/common credit risk scoring currently used by financial institutions (FIs)?
BHV: In the Philippines, for example, the Credit Information Corp. (CIC) is responsible for the country’s centralized registry of credit data from insurance companies, telecom operators and banks. The CIC combines information from bank accounts, credit cards, and loans, as well as a customer’s demographics. These indicators, when combined, show an individual’s overall creditworthiness and the risks to lenders. In the Philippines, traditional data is lacking, especially since the Bangko Sentral ng Pilipinas (BSP) found that around 53% of Filipinos are unbanked.
Unlike traditional data used in standard credit risk scoring, alternative data provides financial institutions with additional context and factors that help improve credit scoring accuracy. With alternative data present in credit scoring, financial institutions would be in a better position to assess loan applications and applicant credit scores and also enable the business to explore new opportunities and create new products and services for untapped markets.
TMT: How will alternative data promote financial inclusion, especially by attracting the unbanked to banks and FIs? Does its adoption necessarily require the FI to be on its own digital transformation journey?
BHV: Alternative data allows financial institutions to assess the creditworthiness of unbanked individuals and enables the company to offer financial products and services without requiring additional documentation or ancillary financial data. With 78% of unbanked Filipinos using e-wallets, the potential and ability to tap into the unbanked segment is huge for financial institutions.
As the world moves towards a new digital era, financial institutions must embrace digitalization and harness powerful new tools to build a broader portfolio of products and services, and at the same time, deliver superior customer experiences in a timely manner. shorter. Digitization is important, especially since only 18% of fintech and financial services companies believe their existing credit risk model is very accurate.
TMT: How can an AI-powered decision-making platform help reduce fraud?
BHV: AI-Powered Risk Decision-Making Platform Delivers Remarkable Benefits, Including 7% Accuracy Improvement, While Automation of Model Development and Deployment Reduces Time by 90% and the effort invested. Our survey with Pulse revealed that 65% of decision makers recognize the role of alternative data in improving fraud detection.
Together, AI and alternative data accessible as DaaS means more time saved, reduced costs, and faster, more accurate decision-making that enables faster time to market and adaptability to changing business. market and consumer forces.