Today, consumers and households are faced with mounting economic pressures, as they continue to struggle through the unpredictable financial shifts of the past eighteen months. The
FCA’s Financial Lives survey found that the number of people struggling to meet bills and credit repayments had gone up by a staggering 3.1m at the beginning of 2023 (10.9m, compared to 7.8m in May 2022). For many, the rising cost of living has meant an
increased reliance on loans in order to pay bills or make mortgage repayments on time. For a lot of people, however, especially those working in the gig economy, access to financial lifelines is often restricted due to the lack of sufficient data required
to approve loan applications.
When it comes to making an informed decision on a loan application, banks and lenders need access to accurate and up-to-date financial data such as employment and income verification, utility bills, or HMRC tax notifications. One issue many customers face
during this application process is that traditional approaches to lending tend to exclude those with little or no credit history, or with untraditional income sources. If, for example, you are a young applicant, self-employed, work on short-term contracts,
or are a freelance worker, traditional bank loans and other lending products can be denied, as credit and affordability checks are run on insufficient, inaccurate, or outdated information.
This is where we’re seeing the power of open banking and transaction AI truly come to the fore. The continued evolution in both categories has proven to unlock vast opportunities when it comes to how banks leverage customer data. Financial institutions can
now access a far greater array of information and analyse it in real-time, to provide customised financial products and services that can better meet the needs of individuals.
Data in the digital economy
As it stands, the limited data usually available via traditional credit assessment models excludes significant portions of the population. With such restrictions, the financial services sector is inadvertently adding to the increasing masses of vulnerable
consumers who are unfairly underserved.
However, with the adoption of open banking and financial services AI on the rise, we can see how consumer-consented data can and is becoming a more sustainable, and fairer, basis for credit decisioning.
Empowering lenders and banks to capture a more complete picture of a customer’s affordability context not only makes the decision-making process more efficient, but it leads to higher precision offering consumers the right lending solutions. Additionally,
it enables financial institutions to develop new, innovative products and services that cater to the needs of underserved populations. What’s more, analysis of transaction data using AI technology removes the possibility of human error or bias in the credit
decisioning process, bringing enhanced transparency and objectivity to lending through data-driven assessments.
Personalised finance = economic empowerment
Whilst the opportunities in empowering greater lending capabilities are clear, it’s also worth noting that the possibilities go much further than just supercharging affordability.
The individual needs of consumers in today’s globalised economy are constantly shifting. Individuals have a diverse array of financial situations, goals, and challenges, and a one-size-fits-all approach just isn’t effective. So much commercial potential
goes unexplored and unmined.
AI and ML bring ever-growing capabilities to comprehend and analyse financial data, so financial institutions are increasingly able to integrate deep financial insight into their workflows. This unlocks the Holy Grail of meaningful mass personalisation at
last, enabling them to grow engagement and generate more opportunities to match consumers with the right financial products. This includes the ability to offer clear insights, recommendations, and guidance tailored to an individual’s specific circumstances,
looking at factors such as income, expenses, debts and savings goals as well as trends and habits.
Overcoming the fear of open banking and data privacy
Whilst I don’t see any slowdown in momentum in the adoption of both open banking and open data, a proportion of consumers are still apprehensive about the privacy of their data. Back in 2021, early data showed
three in five consumers thought open banking was a dangerous use of data sharing, while more than two in five pointed to data sharing as their biggest concern regarding the banking practice.
We have undoubtedly come a long way since then, as this fear, that’s keeping people locked out of tools that could substantially boost their financial well-being, is steadily dissipating. Customer-permissioned data, accessed via open banking capabilities,
provides the bridge that enables personalised financial services whilst protecting data privacy. Open banking is rigorously governed by regulatory frameworks and standards like Open Banking, PSD2, PSD3, and the GDPR, which establish clear guidelines for data
protection, privacy, and security practices that financial institutions must commit to, and comply with.
Levelling the playing field for financial inclusion
We’ve already seen open banking begin to unlock financial opportunities and resilience for end users, consumers and businesses alike. With the proven, and growing force of AI bringing more order and making sense of these vast quantities of customer-permissioned
data, we can generate tremendous value for banks and lenders, and make real strides forward for financial inclusion.