As a lender with a strong social conscience and in order to give the fairest possible deal to their customers, Places for People Financial Services' interest rates would be lower than the industry average so margins would be relatively tight. It was therefore necessary to have a loan management platform that would introduce considerable automation and intelligence so that staff recruitment could be kept to a minimum. The solution must also have a proven track record and pay close attention to security.
Places for People Financial Services successfully launched on time in early 2016 and have enjoyed solid performance and on-target triple-digit growth rates. By leveraging the system’s features which offer significant automation of credit decisioning and loan processing, they have been able to significantly increase business levels without increasing their head count. This has delivered a sustainable and scalable model that delivers the fairest lending rates to customers who in some cases may have resorted to borrowing from higher rate lenders.
Loans 2 Go, appointed LendingMetrics to support the launch of their online lending platform, offering automated flexible loans to suit the consumers’ needs.
As part of their approach LendingMetrics, provided credit risk advice to assist Loans 2 Go in producing their decision engine and assisted the team so that their understanding of the consumer data grew throughout, attending regular meetings both prior to and during the implementation phase in order to assist Loans 2 Go and to share their industry experience.
LendingMetrics delivered a service which produced a scalable model, allowing Loans 2 Go to successfully launch their online presence and look to increase their lending portfolio using the ADP platform and associated services.
The solution was delivered within budget and on time, due entirely as a result of the collaborative and knowledgeable teams at Loans 2 Go and LendingMetrics. Following training, the Loans 2 Go team are now using the ADP interface to change their credit decisions in real time, champion challenge their rules and analyse the results within ADP, as well as using the Equifax suite of products and BankVision.
Fair For You had their own in house Credit Risk Officer who designed their decision engine, using Call Credit’s core bureau products and also LendingMetrics BankVision product to collect 90 days of bank statement data. Their aim was to design a decision engine that could automat as many decisions as possible, delivering good quality leads into the underwriting team so that agent workflow could be driven by tasks from the ADP, based on the warning rules that have been hit and thus improve productivity.
FFY UK successfully launched and importantly, now have a decisioning model which is highly scalable. ADP was delivered on time and within budget without any upfront fees from LendingMetrics, making the award winning (Credit-Connect ‘Best Credit Risk Solution 2018’) platform a cost-effective solution without compromising on functionality.
Street UK needed someone to support the re-launch and growth of their online lending operation; offering affordable personal loans with a clear transparent model.
Street UK successfully launched, enjoying solid performance and growth and most importantly with a highly scalable decisioning model. The ADP solution was delivered within budget and on time. Following ADP training the Street UK team are now using the ADP interface to autonomously manage their credit decisions in real time, champion/challenge their rules and analyse results in order to inform future rule changes.
LendingMetrics were appointed by Nextcredit to support the growth of their online lending operation by providing a more automated process as well as an underwriting tool. Alongside this, Nextcredit also required credit referencing and anti-money laundering checks, which LendingMetrics provided through their LMX platform.
Since the launch of the ADP and LMX platforms, Nextcredit has enjoyed solid performance and growth but most importantly their decisioning model is now highly scalable.