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Data-as-a-Service, A New Frontier for Credit Decisioning

Data-as-a-Service, A New Frontier for Credit Decisioning

Bharath Vellore, General Manager Provenir APAC

It is not a secret that many financial institutions struggle to transition to more advanced credit models. Technologically, many institutions have outdated system capabilities, with limited access to data sources, paired with outdated analytical engines. This has resulted in poorer credit decisioning, as the strong reliance on traditional data, limited access to alternative data, inflexible models and subjective assessment by fallible managers and underwriters, have impeded growth, even before regulatory reviews come into the picture.

Knowledge isn’t just power, it’s also opportunity. With Asia Pacific’s Business Intelligence segment expected to increase at a CAGR of 11.04 percent between 2021 and 2028, financial institutions in Southeast Asia will increasingly depend on data as the go-to solution to accelerate innovation, superior customer experiences, and newfound resilience to navigate an ever-changing credit landscape.

It’s no wonder that Banking and Financial Services form the largest chunk of Asia Pacific’s Big Data spending with a 15.4 percent CAGR between 2019 to 2024. This has resulted in a growing trend of platforms offering Data-as-a-Service (DaaS) to the financial sector, as financial institutions seek to solve business challenges, and capitalise on transactional data to tap into previously obscure markets and financial segments. As such, DaaS has opened the door to improve credit decisioning, and ensure financial inclusivity, through efforts to bank the unbanked in Southeast Asia.

A Marketplace For DaaS

With consumption increasingly shaped by data analytics, DaaS Marketplaces have emerged, acting as platforms to converge and consolidate into a one-stop hub for financial institutions to have easy access to traditional fraud, credit, identity, open banking and alternative data. The availability of data – local, regional and global, brings providers together, and also enables newer cross-border opportunities previously limited to a handful of players.

Simply selecting specific data sources through a data cloud’s single API results in rich, customised datasets that enhance business’ abilities to make data-driven decisions. These marketplaces enable users to connect to new data sources in minutes and test data across decisioning processes immediately; all done without systems integration and tedious maintenance – freeing up internal development resources for more crucial projects.

With the advancement of technology, and future integrations, this whole process can also be automated – enabling the business to offer customised and personalised offerings to every visitor in mere seconds, all according to their needs. This takes credit decisioning to the next level, and means more business segments, in more countries, in less time.

Faster, Simpler, Wider

Having access to such a powerful tool helps companies build a wider portfolio of products and services, and achieve superior customer experiences in a shorter amount of time. Apart from empowering new products and services, such data ecosystems also enable greater accuracy in risk decisioning, a challenge in the industry, especially since only 18 percent of fintechs and financial services organisations believe their credit risk models are highly accurate.

Access to more data from a DaaS Marketplace means that companies do not need to rely on antiquated credit models but are liberated to reach into other segments and markets in a big way. A seamless, frictionless and fully automated decisioning process brings more value to clients, minimises risks and in this age of disruption, enables businesses to disrupt rather than be disrupted.

With the unique combination of universal access to data through the Provenir Marketplace, simplified AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle – offering diverse data for deeper insights, auto-optimised decisions, and a continuous feedback loop for constant improvement.

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