Futureproofing Buy Now, Pay Later Offerings with AI, Machine Learning and Low-Code/No-Code Approaches

  • Veejay Jadhaw, CTO at Provenir

  • 31.08.2021 02:15 pm
  • #BNPL #KYC #ID

As the Buy Now, Pay Later (BNPL) space expands rapidly, organizations need to infuse their go-to-market strategies with advanced technology to make these programs sustainable – to manage risk and respond quickly to market needs, and to be agile to shift as needed to adapt and keep pace with the evolving regulatory environment.

Technology decisions made now will have a direct and tangible impact on the future adaptability, growth and longevity of your BNPL offering. 

Here are eight key technology requirements to consider: 

  1. Harnessing alternative data beyond traditional credit checks

Basic, soft pull credit checks often don’t report the most recent activity; this can make decisions riskier and less accurate. Looking to data outside of the traditional credit score, such as alternative data such as behavioral scores, telco information, transactional data and open banking, can offer BNPL providers real-time insights into affordability and risk. 

  1. Digital onboarding for merchants and customers

According to recent research, unless a financial institution can open a new account or complete a new loan application in less than five minutes, the potential for the consumer to abandon the account opening increases to as much as 60 percent or more. 

Automation in digital onboarding can significantly minimize customer effort. Ideally, automation augments customer data with the additional information needed to perform robust compliance checks, identity verification and risk decisioning all in real-time. 

  1. Flexible compliance processes to address evolving regulations

Building agile processes in areas such as Know Your Customer (KYC) and affordability requirements can ensure your BNPL offerings remain fully compliant. Solutions that leverage no-code, drag and drop user interfaces can empower risk teams to update processes, add in new data sources and make changes on-the-fly. 

  1. Integrated fraud detection

Fully integrated fraud processes, such as robust Anti-Money Laundering and KYC tools, digital footprint tracking, transaction monitoring, simple integration or advanced fraud tools can thwart those looking to exploit system weaknesses. This is important, as catching fraud early in the process prevents bad debt being passed down the credit lifecycle.

  1. Performance monitoring via analytics 

Real-time visual performance dashboards offer data analytics visualization to identify insights that empower innovation. The ability to use performance and decisioning data to train and retrain models in real time also plays a key role in accelerating product innovation.

  1. Support for rapid time-to-market and BNBL business model diversification

It’s important for technology to support your BNBL business model today as well as your future strategy plans and diversification into new sectors. Technology elements that enable BNPL providers to pivot and enter new markets quickly include simplified data integration, low-code/no-code approaches, rapid model deployment and even prebuilt reusable decisioning templates.

  1. Support for the full customer lifecycle 

Look for technology that is extensible to support all aspects of the customer lifecycle, from onboarding to fraud management and ongoing credit line management to collections. When all customer and decisioning data is consumable by that ecosystem, it eliminates data silos that prevent the business from fully identifying risk and empowers rapid iteration and innovation as well as greater operational efficiency and cost savings. 

  1. AI/Machine Learning for Rapid Risk Modelling

Machine learning – or ML Ops capabilities – can help BNPL providers retrain risk models in real time, for significant improvements in decisioning performance. Faced with data science talent shortages, many BNPL providers are finding significant value in prebuilt or custom-built models to accelerate the time-to-market and make strategic shifts in risk strategy.

AI, machine learning and low-code/no-code technology approaches offer BNPL providers tremendous advantages in architecting their BNPL offerings for speed, agility and sustainability. Careful forethought and purpose-built technology can address these eight key considerations for competitive advantage. 


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