Guest post by Simon Forster, Senior Market Consulting Partner – Financial Services at Experian
The COVID crisis has had a profound impact on the credit market with many lenders withdrawing products or tightening risk policy on those that remain. Now that lockdown restrictions are easing and demand for credit returns, there is a real opportunity for product diversification and disruption within the Financial Services sector.
Those organisations that make better use of data from both existing and new sources will find themselves best placed to take advantage of these opportunities. Access to and use of data on its own won’t be enough however, it is the insight that is derived and the way in which it is utilised within lender strategies which will make the most significant difference.
During and immediately after the lockdown period, the credit quality of the application traffic we are seeing flowing through the Experian bureau has improved. I believe this is being driven by a combination of pent up demand and self-selection. As volumes begin to recover across all sectors, we very much expect to see this anomaly corrected and the $64k question is whether the products which were withdrawn from the market will return?
Traditional scoring models using bureau data continue to rank for risk but whilst past performance will always be indicative of future behaviour, it doesn’t necessarily consider the impact the pandemic has had on the applicant’s financial circumstances.
We know that large numbers of people are overstretched financially, with debt on the rise and loan defaults increasing: 1.6M people are in persistent debt; 25.6M people are showing a characteristic of financial vulnerability; and 9M are using credit cards to fund everyday living expenses. Offset against this and, despite the introduction of payment holidays, we’ve observed a pay-down of £7.4 billion of consumer credit in the first month of lockdown alone and at the same time we’ve seen savings balances increase across the board.
Through advances in data collection and analysis, we are now able to identify such patterns to provide a more granular insight into behavioural spending, which in turn will drive more informed decisions to provide a more effective indicator of an applicant’s ability to re-pay, whilst considering the traditional credit and affordability risks based upon the patterns observed.
By adding payment behaviour trends, lenders will be able to differentiate between two applicants, who may look the same based upon the static view, and create new segments to which more personalised decisions can be applied which are truly representative of the applicant’s circumstances; by doing so, lenders can expect to reduce bad debt and drive profitability.
The inclusion of alternative data elements (such as Rental) within the scores and attributes will provide additional perspectives to those who may have traditionally been classed as a ‘thin file’ applicants. The incorporation of alternative data will widen the pool of people that can be considered for the products and services on offer. Importantly, the use of ‘trended’ behavioural data will help optimise the journey, as fewer applications will require manual review, and by removing friction, it can be reasonably assumed conversion will increase.
In parallel to the economic and financial impacts, the COVID crisis has driven a series of lifestyle and shopping changes, one of the most significant being the increasing adoption of digital sales channels and the associated finance options that come with them. Customer expectations of personalised offers and streamlined customer journeys are higher than they have ever been and in the world of instant gratification, it is imperative that accounts can be opened in real-time and offers are made with conditions these can be fulfilled seamlessly. Examples of this could be;
Provision of the option for a customer to follow an open banking journey to enable accurate data backed affordability assessment instantly. Identity verification via ‘selfie’ validation against a driving licence or a bank statement to validate residence; instead of providing paper ‘proofs’
It might even be these steps are brought forward to the start of the journey, to enable pre-population of the application form, thus simplifying customer journey even further.
To deliver the flexibility that is required to support these interactions an intelligent, data orchestration, decision and workflow engine needs to exist to ensure the right services are called at the right time with the decision at each stage of the journey defining next action.
For instance, customers are willing to spend time setting up security questions as they know this will facilitate the viewing of account information in the future. Still, they aren’t willing to spend time providing information they perceive you to have already or should know. The average loan application takes nine minutes to complete, and pre-population could reduce this by half and at the same time increase accuracy.
Such levels of automation can often be facilitated by standardised designs (typically delivered through the cloud on software as a service basis) that take data, apply rules and models, overlay optimisation constraints and policy limitations to determine terms, pricing and a final decision; all of which can be evidenced through the full audit history provided These solutions also provide access to future capabilities such as machine learning with minimal incremental investment, to ensure lenders always have access to the newest data, insight and capabilities to optimise their business process, whilst minimising operational cost.
Transforming data into information and insight is essential to understanding customers and approaching them with the appropriate treatments. With the right automated systems in place, new models can be easily built through highly intuitive desktop tools, and rapid deployment to the run time environment provides the flexibility required to dynamically react to the ever-changing needs of the market-place.
Automation enables responsible lending using timely, accurate data in a consistent and auditable way. Supporting lenders in ensuring that they meet their FCA obligations and treat their customers in personalised yet structured way.
“Automation is the future – helped by the development of cloud-based access which allows you to bring together all your applications and decisioning needs into a single place. As a result, you can make more sense of your data and unify your business processes, be more accurate, more efficient and armed with an ability to act on previously unseen insight.”
Experian is a member of BIIA