Published: Wednesday June 06, 2018
A blog post by Albert van Wyk, Business Development Director, Australia & New Zealand at GBG
Businesses are facing growing pressures to onboard more customers faster, and this is making them increasingly susceptible to risk.
The recent months of the Banking Royal Commission in Australia have been a revelation. In 2017, the Australian government began an inquiry into misconduct within the banking and financial services industry.
Through six gruelling months of public questioning and testimonies from senior executives at businesses taken to trial, we’ve learned how the pressures placed on bank employees to achieve revenue goals have created cultural aberrations that have led to very unfortunate outcomes
It is clear that the need for immediate gratification, increased competition and a great customer experience with the shortest time to “yes’’ has led us down this path. And regulators are more scrupulous, with astronomical fines for non-compliant businesses now commonplace in the daily news cycle.
I’ve had many conversations with leaders in financial crime and fraud prevention over the last few years, and have often heard “we don’t have an application fraud problem…” or “that’s not our concern…”.
Yet, without fail, those same organisations would carry significant losses through first payment defaults, writing it off as sub-optimal credit decisioning and trying to reinforce their collections processes.
So why does a blind eye get turned at the point of customer onboarding?
Today we stand at the inflection point where the need for swift customer onboarding is met with advanced analytical capability.
How can businesses say yes to new customers quickly, without the added risk? Here are my three top tips:
- Automate many of the processes involved in deep data investigations
Back office checks and fraud investigators no longer have the luxury of time to delve into the grey to find those unique corner cases that ultimately lead to bad debts where there is no intention to repay. Using technology that quickly and accurately link data attributes, and display the correlations, allows more time for decision making and streamlined operations.
- Measure and report on those areas of most importance
If we measure Average Handling Time (AHT) as the key metric, we will install a culture where quick is better and quality is second. The preferred approach would be to measure quality and provide investigators with the tools to reduce AHT.
- Trust and leverage the expertise in the team
In a world where Artificial Intelligence and Machine Learning are key buzz words and large investments are being made into it, it is commonly forgotten that one of the most important needle movers are the team right in front of you.
Instead of trying to find or create that model that is 100% predictive, leverage the actions of the investigators by dynamically using their inputs to adjust weights and implement rule changes. This approach quite often yields greater results that can then inform the future models.
At GBG, we’ve listened and understood the needs of our clients and enhanced our anti-fraud solution for applications - GBG Instinct, to help investigators see connections, react to changing threats faster and help their business to say yes to more good customers faster.
To find out more, please email me at Albert.vanWyk@gbgplc.com.