Advancements in the use of bank data is changing how financial institutions consider almost every element of their customer onboarding, credit risk, and compliance functions.
With each passing day, the advantages to using bank data become clearer. But for those considering implementing an Open Banking solution, confidence that there are no underlying problems with bank data need addressed. In this article we condense the most oft cited risks versus the rewards of using bank data.
Jump to specific section
Companies, including financial institutions who use bank data throughout their operations can reap substantial benefits. As bank data is not confined to one particular department or function it can be used throughout the banking continuum, adding value at each respective stage.
With high overhead costs, and lack of automation, operations is an area with significant potential for impact. The use of bank data provided through Open Banking is now making this impact apparent.
This is because processes currently are typically inefficient, cumbersome and take an exorbitant amount of resource to execute. Using a large volume of resource, which takes time to execute, makes it an expensive unit to operate.
The reasons for these resource requirements are primarily historical. As we know, fraud analysts, underwriters and compliance professionals frequently need to corroborate the information provided to them against physical documents.
These checks are carried out for several reasons, including compliance, AML and KYC, affordability assessments and checking creditworthiness. The process becomes even more laborious should the applicant be required to go through the exceptions process.
With multiple checks required, different individuals and teams must all participate in clearing the applicant.
Much of the work undertaken by these highly trained and professional individuals involves checking bank statements – sometimes line by line – to check for inaccuracies, possible tampering and fraud, and to try and calculate affordability and creditworthiness.
With customer’s bank data, this process is completely reversed.
Bank data ensures that the data comes direct from the bank, so cannot be altered with or tampered with in any way. This reduces the amount of scrutiny required from fraud analysts.
Products such as DirectID can classify and categorise bank data, offering insights into affordability and creditworthiness. The time required of an underwriter is now decreased.
Reducing the time that these professionals need to spend at the outset of a customer case allows them to focus their attentions on other business priorities.
A complaint that we frequently hear from bank customers of banks, is the amount of time it takes to process a new customer account or credit application.
As well as having to wait an inordinate amount of time, it is common during this waiting time for the bank or financial institution to phone with requests for additional information. This information could encompass bank statements, ID checks or proofs of address or residency.
Indeed, modern banks have multiple touchpoints with prospective customers prior to their request ever being fulfilled. In some instances, this can even involve asking for the same information on more than one occasion.
While the amount of time varies between case and institution, we are aware of cases taking upwards of five months to complete.
In 2020, it is barely necessary to state what a poor experience this is for the customer.
Beyond this, it is in a bank’s interests to shorten the period and make the process as streamlined as possible. If a prospective customer receives a poor service during the application process, there is increased likelihood that they will seek to fulfil their needs elsewhere. Even should they wait patiently for the process to be completed, the customer is unlikely to be an advocate for the service.
Beyond the customer experience, finance houses need to consider their own sales pipeline when taking days, weeks or potentially, even, months to complete onboarding. The faster that a customer can be onboarded and have their account set up, or have their credit application accepted, the faster they can begin to spend money with you, either buying additional products or services, or taking the loan applied for.
Delaying onboarding for any more than is necessary has a detrimental effect on both the customer and the bank. Making the process friction-free and seamless has a positive impact for both.
Bank data can supply the lubricant required to remove all friction from the onboarding / credit risk process, resulting in satisfied customers and banking provider alike.
In the first instance, bank data can speed up the entire onboarding / account opening process, enhancing the customer experience and contributing to a happier customer.
In the second, speeding up the onboarding process, also has the obvious side effect of allowing you to bill customers sooner.
One component of the onboarding or credit risk process that makes it so lengthy, is that the specialists examining the documents need to be entirely sure the person to whom they are offering the loan, or opening the account for, are who they say they are.
They also, moreover, need to ensure that the recipient can afford the repayments on it and it will not push them into financial distress. These checks are imperative and makes the decision-making process critical.
Despite the importance of these questions, and the answers contained therein, obtaining correct and up-to-date information remains challenging.
As we have already alluded to, the analysts and underwriters who seek to understand their potential customers, must resort to going through bank statements line-by-line, trying to classify and categorise transactions to understand a customer’s spending habits. They try and understand an applicant’s salary based on the same statements.
While this is perhaps not an issue for those in Monday to Friday roles, less than 50% of the population are represented this way. Far more common is to see zero-hours contracts, part-time jobs, self-employed, gig economy, retirees and students – none of whom will have a monthly salary from the same employer, for the same amount, every month.
Using bank data then, gives those making credit risk or account opening decisions the answers to questions that are extremely challenging to answer in its absence. Calculating an individual’s income, by way of example, involves matching what is written on the application form with what is on each bank statement.
As well as making savings in time and resource, bank data also affords banking professionals the opportunity to make better, more informed decisions.
We’re conscious that scrutiny on the sector from regulators such as the FCA has only heightened over recent years, and it is therefore imperative that all decisions are made with the most up-to-date and relevant information available. For that to happen, the use of bank data is a must.
In the traditional account opening or credit risk process, fraud analysts, underwriters and credit risk professionals are reliant on the information submitted on the application form combined with CRA data on which to make a decision.
Customer’s credit histories are rarely, however, straightforward.
For this reason, the value of bank data comes into its own. The ability to see income and expenditure, where money is being spent, on debt management, on gambling, credit cards and more; underwriters suddenly now have so much more information on which to base an agreement.
As well as being able to make better, more informed decisions, bank data can also supply insights, which were they not presented directly to the credit risk professionals, would be totally overlooked.
Fear of Missing out and Competitors Stealing an Advantage
As we know, Open Banking, which is principally used for the generation of bank data, was brought into existence in January 2018. Two years in, and new research has shown that Open Banking has been used by over one million UK customers. The volume of regulated body’s using Open Banking has also increased markedly, with the figure now standing at above 200.
This is a long way of stating that Open Banking, and the use of Open Banking is proliferating.
The very first fear that we at DirectID come across regularly is that the competition to those we are speaking to will be suing bank data. And the truth is, that they most likely are. Unstructured bank data, with no insights or support can now be attained from some suppliers at extremely low prices.
Other companies, who place more of an emphasis on receiving visual and actionable insights with their data, use services such as DirectID Insights.
To address this fear, consider why you would want to use bank data, and the operational challenge that it may resolve. Is it affordability assessments? Is it income verification? is it removing the cost and time associated with credit risk decisions? Is it seeking to enhance operational efficiency?
Having clarity on how bank data can support business operations puts end users at a distinct advantage who are receiving unqualified and unstructured data with little consideration for how it is to be used.
We understand that data security is one of the prime considerations for any financial institution. The risk of data breaches taking place are unprecedented compared to any other period in history. Either through malicious actors, security lapses or human errors, the last decade is littered with the fall-out of companies losing their customer’s data. In the finance sector, the implications are even more severe than elsewhere.
Indeed in 2019, 60% of all the data that was leaked came from financial services companies (though they represented just 6% of all the companies hacked).
In mitigating against the risks when using bank data, it is important to understand that Open Banking is inherently secure, and far more secure than its predecessor, screen-scraping. Ensure that any AISP or PISP uses bank level security, layered and protected by tokenised oAuth authentication and strong encryption.
As with all services, there is a cost to using a service provider to grant you access to bank data. The good news is that there are SaaS companies working at different ends of the price point.
As we intimated above, bank data by itself is not hugely expensive and can be acquired relatively cheaply. The challenge begins when you try and analyse and categorise these transactions with no external help.
As we intimated above, services such as DirectID Insights sits further up the expenditure scale, but allows customers to begin working with bank data in less than a few days. Rather than sending unstructured data to customers, DirectID - as well as providing a full set-up and onboarding process replete with regular updates and a dedicated customer support function - also categorises and classifies all the data to our customers specifications. As a result, DirectID can have customers up and running with bank data in mere days.
Loss of business
As we have outlined in myriad other articles, the advantages for banks and other financial institutions in using bank data are hugely significant.
Some of the most ardent supporters of bank data and Open banking have been smaller FinTech’s and Challenger banks. They have been clear in how their use of data can help them meet their business goals, and this, allied with the fact that their technology is built upon modern tech stacks and Open APIs, it has been far easier for them to realise the potential of Open Banking.
That threat from Challenger and digital banks, is real, and potent. The positive news for other financial institutions is that solutions can be implemented today that involve no set-up, zero integration and instant insights – meaning you can be caught up in just days.
The rewards of using bank data have been widely distributed. Savings in time and resource, efficiency gains, better decision making, faster onboarding, actionable insights and more. Indeed, as new products and services are brought to market, we expect more and better advantages for banking customers to be made available.
In our experience, we have found the risks of bank data to be widely anticipated, but have not yet been forthcoming. There was much talk about data security at the outset of Open Banking, but of course, for those that have followed Open Banking’s progress, it is more secure than its predecessor technology and runs on OAuth2 bank level encryption.
It is the other intangible risks to which bank customers should be aware. While you may be considering a solution, customers, unhindered by loyalty to any particular brand, will be searching for the best experience. If they find a competitor who offers a swifter, more efficient service, with bespoke rates that requires negligible back-and-forth between bank and customer, then we know to whom they will turn.
The cost of implementing a solution is another possible reason for some bank executives to hesitate. In our experience we have seen bank data pay for itself many, many times over in an incredibly short space of time. As stated above, bank data by itself is also incredibly cheap. However, without insights, visuals and context to it, it can be heard to find practical insights from it.
Premium services such as DirectID Insights can offer the best of all worlds, offering bank data within a structured, contextual, graphic interface that gives you the answers to the most pressing questions, in mere seconds.