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Streamlining access to the banking system

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Streamlining access to the banking system 1

With customers’ expectations continuing to rise amidst stay-at-home orders, banks and other financial institutions are competing with one another to provide the best digital products and services.

It’s fair to say that with digital interactions, speed is everything. This is particularly true when it comes to opening a new bank account. The Digital Banking Report 2020 revealed that abandonment rates increase significantly as the time to complete an application increases. If the process takes over ten minutes for opening an account online, or five minutes for a mobile process, the abandonment rate is as high as 40%.

If your process is confusing and requires a lot of work for customers, you will lose their loyalty. Another 2020 study by Gartner highlighted that 96% of customers who put a ‘considerable effort’ into an interaction become more disloyal. That’s why you must ensure that the procedure is smooth and simple from start to finish, whether on a desktop or mobile.

We sat down with Ezbob’s Chief Risk Officer (CRO) John Christiansen to find out more about the problem that banks face when it comes to account opening, and how it can be solved by data and analytics in the age of Open Banking.

Why are the banks now under more pressure to improve their account opening processes?

People are demanding the same frictionless experience and seamless customer journey that they get from big tech companies, with similarly simple service. For example, with Amazon you can buy a product in three clicks: one to select the product, one to purchase it, and one to review the purchase. The likes of Just Eat have followed suit, and you can order and pay for your meal in just a couple of clicks.

The longer a process takes, the more likely a consumer is to abandon it whether or not they go elsewhere. This is particularly a problem for traditional banks – we have seen 80, 90-question application forms that result in eye-wateringly high rates of abandonment. The onboarding process at incumbent banks is typically significantly longer and more complicated than for newer challenger banks, sometimes by a factor of four or five times the amount of clicks.

What steps can they take to resolve this issue?

The first step is to recognise the problem and treat it as a priority. Money is the ultimate commodity, so it’s natural that people expect an optimum customer experience in financial services. Now that artificial intelligence (AI) and machine learning are maturing, their main use in this industry should be to optimise the customer journey. 

Historically, banks have looked to increase access by lowering risk controls, but there is a view today that they can have the same, or better, risk controls while at the same time asking fewer questions. 

This is achieved by combining the latest technology with the abundance of data available in both documents that the customer will likely have about their person (for example, a full driving licence, which ~75% of UK adults have), other data sources and Open Banking to accurately prefill information at onboarding stage, meeting the requirements of customer due diligence, and completing the process quicker with only exceptions requiring manual intervention. 

Banks and other financial institutions should carefully review the questions they are asking and consider what really is essential – let automation do more of the heavy lifting. 

How can they use data more intelligently?

Simply put, lenders should look to gather data from external sources to reduce the number of, and potential for confusion in, the questions that they ask. Banks are increasingly turning to cloud banking software, often partnering with agile fintechs to help them focus on solving this problem. 

One of our clients, for example, started with more than 80 questions, before internally undertaking an exercise which reduced it, to nearly 50 but still not enough people were completing the application. 

After a three-hour exercise reviewing the questions that they were asking, we were able to reduce it to eleven and went on to build an onboarding platform for them. We pulled together multiple data sources that allowed their end customers to be served at the highest speed possible, whilst not sacrificing anything in the way of accuracy and without the necessity of speaking to anyone from the bank.

John Christiansen

John Christiansen

Lenders have intelligently generated a flow of the collection of data items and step-by-step decision making to create an optimal journey – meaning that there is minimum input from the applicant and gathering data from third parties means that the number of touchpoints is vastly reduced. For example, some lenders are choosing to generate decisions based on the following flow: 

  1. Applicant data
  2. Regulatory requirements
  3. Credit decision: binary 
  4. Credit decision: product
  5. Credit decision: pricing
  6. Lending amount 

This allows for the time from 1-6 to be reduced to minutes, not days. 

How exactly do advanced technologies, such as AI, leverage the open data available thanks to PSD2 to increase the speed of opening a bank account? 

The latest onboarding systems make use of AI, machine learning and analytics to automate much of the process, increasing speed and efficiency.

Open Banking provides accurate, real-time financial data based on an applicant’s financial performance and behaviour. The user grants their permission for the system to access this wealth of data (in the case of Open Banking, for a limited time), and then gathers information from multiple sources (including non-traditional ones such as Amazon activity), extracts and categorises the data. 

Experimentation continues within the ezbob ecosystem at the same time, using techniques such as elastic net and XGBoost in order to arrive at the most predictive model, where examining high volume data instances including marketing and transactional data. 

In addition, the best systems can cut out a host of questions by using AI techniques to absorb an applicant’s identification documents and a selfie, with the algorithm gathering the data from the document. Therefore, the applicant isn’t asked for their name, address or date of birth – they’re merely asked to confirm what has been captured from the document.

What is Ezbob doing in this space?  

Ezbob provides cloud-based SME lending and account opening solutions that enable financial institutions to accelerate customer acquisition and automate their operations. The company is a pioneer in using advanced AI-powered analytics and Open Banking data to streamline the end-user application process, resulting in increased sales and significantly reduced operating costs. Its clients include some of the largest European banks including NatWest’s Esme Loans, Metro Bank, Intesa Sanpaolo, and Santander. The company was founded in 2011 and is headquartered in London, UK, with a development office in Tel Aviv, Israel.

What’s next when it comes to simplifying and democratising access to financial services?

Banks and other financial institutions need to understand a 360° degree view of the customer to lend or provide services in a responsible manner, especially given the economic impact of COVID-19. Open Banking gives them the keys; they can access all the data needed to provide this holistic view and thus improve customer service.

We expect to see the industry move beyond bank accounts and lending to use external data including Open Banking to inform a wider range of products, from HP, PCPs and asset finance through to residential mortgages and – eventually – portfolio-level lending across multiple, similar, assets. 

I’ve worked in the past on the concept of the ‘four-minute mortgage’ with a lender, and I do believe that advances in technology can make this a reality. AI and machine learning can predict elements like the changing value of a property over time, an applicant’s changing income, and even lifespan to inform a quicker lending decision. It will become possible to move from the first page of a website to formal offer in minutes. 

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