Risk Monitoring and “Active PSD2” Use Cases
PSD2 isn’t a threat, it’s a golden opportunity.
The Goose that laid the golden eggs, if you will.
And those golden eggs are the new business models and revenue streams it’s creating.
Indeed, there has been a lot of chatter regarding “Active PSD2” use cases.
Active PSD2 use cases exemplify how banks can leverage the payments directive to offer new and improved products such as account aggregation, cash management, etc.
And PSD2 might also be able to make the average credit risk officer’s life easier.
How? The newfound access to recent transactional data as a basis for making credit decisions.
But let’s leave the new credit applications for the end and for now focus on slashing default and prepayment risks of the current loan portfolios. Essentially, this means using PSD2 to monitor existing loans efficiently while preserving the all-important customer experience.
Behavioural Credit Risk Management Use Case
Let’s say Bank Of The Future (BOTF) is monitoring a portfolio of 100,000 consumer loans.
For obvious reasons, BOTF cannot request access to every single client’s aggregated transactional data… especially not monthly.
This would be uneconomical, unprofessional… and certain to piss off its clients.
It’s more realistic and efficient to use an early warning system.
BOTF uses its early warning tool, which neatly singles out and highlights the 500 loans that have a high probability of defaulting and 100 loans that have a high probability of prepaying in the next 6 months.
BOTF then analyses the recent transactional data to draw firm and actionable conclusions.
For example, the bank discovered that only 100 clients were actually showing default patterns while the other 400 displayed risk-averse behaviour. And only 20 clients have recently experienced a significant, one-off inflow that might encourage the clients to prepay the loan.
BOTF promptly reaches out to these 120 clients to help them decide what their next steps should be, without having to disturb all 600 of them.
Bank Of The Future is satisfied that it honed in on the customers that had a high default and prepayment probability because it resulted in cost-efficient monitoring.
It didn’t have to request access to account and categorisation services on a whim, it knew where to focus and whom to request access to.
Now that the bank has monitored and mitigated its existing credit risk, it can move onto finding new credit opportunities.
Loan Origination Use Case
Alternative credit scoring isn’t a thing of the future anymore. The usual framework for calculating a person’s credit score is no longer enough.
Especially for the new generations, whose credit files are usually too thin to calculate a decent credit score.
That’s the catch – Without credit histories, it’s difficult to give them credit.
But now, they don’t need credit histories.
Their new power to grant access also gives them the chance to request credit by offering up another type of information – transactions.
Transactional data can give deep insight into a customer’s behaviour, which may or may not have changed recently, and can provide information that aids in ALM and KYC.
BOTF has recently taken interest in Gen Z and would like a way to reach them without partaking in risky practices.
So, BOTF uses its ecosystem of innovators to create an app that will let these Gen Zers apply for different types of loans and mortgages.
Rather quickly, it receives an application from twenty-three-year-old Tina, who has never taken out credit in her life.
After accessing Tina’s transactional data, BOTF notes that she does not have many expenses. She does not engage in any risky behaviour such as online gambling or withdrawing money in the dead of night.
By identifying her earned income among the transactions, BOTF also calculates her disposable income and sees that her cash flow has not experienced any significant or recent change.
Satisfied, BOTF accepts her application. The bank will then proceed to monitor her, along with the rest of the loans in the portfolio, using tools made to process the number of data banks deal with today.
As you can see, PSD2 (or Open Banking in the UK) might have been the boost banks needed to improve their risk management processes.
However, as I noted when I went to Edinburgh’s Credit Scoring and Credit Control Conference at the end of 2019, there is still much work to be done in normalisation and categorisation.
In CantabPI’s case study of how PSD2 has the power to transform lending, three challenges are highlighted:
- Variables – PSD2 data sets differ from the ones used in credit scoring. This means that we still must create the variables used to make credit decisions.
- Data standardization – Although Open Banking in the UK and the NextGenPSD2 API framework in Berlin Group aim to standardize PSD2 data, there is much to be done to standardize across the EU.
- Noise – The irregularity of current account data makes it hard to single out specific information of interest.
In this article where I list the main takeaways of the credit scoring conference, I also highlight that experts suggest not to push open banking credit scoring to all customers.
Post-PSD2 credit scoring and risk management, just as with all innovations, need to be done one step at a time.
It is time to start seeing PSD2 for what it is – a way forward.
But one shouldn’t jump headfirst.
Dip a toe in, test the waters, then draw your own conclusion on whether leveraging PSD2 will benefit your organisation.