By Louise Potts, Head of Banking Customer Advisory Practice at SAS UK & Ireland
It’s no secret that banks hold a wealth of information on their customers. While many have focused extensive resources on safeguarding this data, this has caused many organisations to overlook how this insight could actually be used for good – specifically when helping to protect vulnerable customers.
The Official Monetary and Financial Institutions Forum’s (OMFIF) latest report, ‘Central banks in the digital age: Bringing data into focus’, has found that banks are not harnessing the power of data, with many central banks bogged down by old and outdated legacy systems.
This needs to change – particularly given the context of the nation’s financial resilience. According to the Financial Conduct Authority (FCA), in May 2022, 12.9 million UK adults had low financial resilience – 1 in 4 (24%) of all UK adults. As the cost of living crisis continues, we can expect a similar bleak picture to unravel throughout the remainder of 2023.
Data insights can have a hugely positive impact here. Those banks able to mine and understand their data will often spot indicators that a customer may be moving towards financial distress, before this situation has spiralled and become unmanageable.
Data for good
Applying data science for social good is not a new phenomenon. SAS has long used data to help solve some of the world’s most challenging issues – in key areas such as education, poverty and health.
In the banking industry, there is immense potential to make the most of data insights when identifying and helping vulnerable customers. Here, early identification could not be more important.
Artificial intelligence (AI) can be used to monitor an individuals’ activity and transactions, throughout the entire credit lifecycle, so that banks can spot signs of impending financial difficulty, such as frequent overdrafts or late bill payments.
This data can then be used for proactive intervention with a vulnerable customer’s specific needs in mind, whether it be simplified account management, alternative low-cost banking options, or resources for those with poor financial literacy.
Putting vulnerable customers first
Traditionally, banks have relied on customers to disclose their financial vulnerability. However, as information from the Vulnerability Registration Service (VRS) illuminates, this often does not occur in reality, or prove the best course of action.
Sudden negative life events such as ill health, bereavement, relationship breakdown or job loss, can leave a person more vulnerable or susceptible to financial harm – while at the same time – people in difficulty may not want to ask for help or know how to.
In the past, it may have been difficult for banks to quickly spot struggling customers, given stretched resources, but as advanced technologies have developed to harness the power of data, this process has become easy to automate. The result is reliable, informed insights – that, crucially, can occur in real time.
The real-life solutions
To be effective, any solution needs to consider together all the key contributors to a person’s finances – including credit cards, instalment loans and mortgages. Has an individual missed a mortgage repayment for the first time? Have they also recently defaulted on a loan?
Owing to innovations in AI and machine learning, this is now possible through complex models which take a wide range of data sources into account beyond the traditional means. Through this, the appropriate help can be given to those who need it.
For example, if a customer logs-in to their bank account online, their activity can be used to trigger a personalised message with advice relevant to their situation, such as loan guidance, or more detailed information about the terms and conditions of their loan.
Equally, data can be utilised to prevent a different department reaching out to a customer at an unsuitable time, prioritising their circumstances with the most useful comms.
Banks also need to consider that it is often vulnerable customers who are most frequently targeted by fraudsters, who exploit a person’s poor financial situation with scams and fraudulent offers to make money. With this in mind, banks can implement sophisticated fraud detection systems, alongside providing the individual with clear guidance on how to protect themselves from scams.
With Consumer Duty regulations coming into force, many banks are already turning their attention to putting their customers’ needs first. Data will not only help banks evidence this, but form their strategy when dealing with vulnerable customers, based on invaluable analytics from a multitude of sources.
