How to Tame Credit Originations Complexity and Data Overload

Exploring the Originations Decision Management Challenges 

For many lenders, the multiple decision factors have been a cause of disjointed originations processes, which elongate the journey – because they involve requests for documents, or a switch to costly and needlessly time-consuming legacy decision-making systems. More friction and breaks in the process mean more applicants are likely to go with a competitor who is able to provide a more seamless journey. The challenge for lenders is to create originations processes with acceptable levels of friction, whilst maintaining robust risk assessments, to effectively comply with regulation and manage levels of delinquency and loss. 

The emergence of new channels through which customers obtain finance represents a further origination technology challenge. But it’s one that can unlock the convenient, seamless experiences on which customers are placing increasing value. Price comparison websites have been a cornerstone within many markets for years, and embedded finance options, such as those where a finance option is selected at the check-out of an e-commerce portal, are growing rapidly. Currently dominated by fintechs, it's an area where the British Retail Consortium expect to see up to 25% year-on-year growth between now and 2028. To maximise their market share, banks need systems that can meet the different requirements of their internal sales teams and multiple third parties. 

Facing the Originations Challenges

With the right technology it is now possible to drive out manual or high-friction interventions and offer seamless, near-instant credit decisions across multiple sales channels, without compromising on risk controls at all. There are three critical assets, which should be used in combination: 

1. Open Architectures

API-enabled architecture is key to providing the flexibility required for connecting a common strategy system with multiple sales interfaces and data sources. When combined with the capability to tailor the response message via the favoured requesting channel, without significant amounts of complex coding, it becomes far easier to sell through multiple channels and close any gaps restricting new business. 

This level of flexibility is key to achieving market share as an already competitive environment becomes more competitive still. Open architectures have allowed the lines between ‘traditional’ lenders, fin-techs and tech-savvy, non-finance organisations, like Apple to become blurred. It’s important for banks to respond through the adoption of their own similarly open and adaptive decision architecture.  

2. Flexible Data Models

API-enabled architectures connecting to new data sources, need to be supported by the ability to make data readily available for use. It’s vital to have a decision system with a flexible data model to facilitate the use of new data, from across the organisation or from third parties, quickly and efficiently. Consider the pace of change within Open Banking, Open Finance and Open Data ecosystems, where new data sources are continually emerging. Open Payroll, where salary data can be shared directly with lenders, provides a recent example of the continued growth of structured data that's available to underpin automation of originations processes. 

The quicker banks can leverage the ever-expanding data universe, the greater the competitive advantage will be, especially when it comes to delivering a first-class customer experience, whilst retaining robust risk controls. 

• Read the blog post FCA’s Consumer Duty Mandates Sharper Use of Technology

• Watch a video on why customer-centric service is critical