Onboarding in financial services involves a lot of paperwork. Anti-money-laundering regulations mean that every prospective new customer has to present a range of documents verifying their identity and address even before they reach the credit check stage. To complete the application, they may well have to produce passports, driving licences, utility bills, bank statements and payslips.
Aside from the sheer amount of manual labour involved in checking and cross-referencing these electronic documents, some highly valuable data is going to waste. Each one of these documents contains information that has the potential to be a major asset; useful insights can be drawn from details such as age, region, income range and spending habits. What’s more, its value can often be increased by linking it to existing information about the same customer.
The reality, however, is that most financial services companies are storing these documents as “flat” image files, which occupy storage space and are accessed rarely. In this format, none of the information they hold can be analysed, effectively rendering them useless. As stated by IDC in a recent report, “Data, in the absence of meaning and context, is worthless and costly.”
Extracting the value from an everyday document
This needs not be the case. Ephesoft’s technology can identify and extract the unstructured data from a two-dimensional image of a document – and turn it into something useful. We can extract the relevant information from a digital image no matter what the format. Our software learns to identify specific fields on different types of documents, such as the account number on a bank statement, or the name and address on a utility bill and can be trained to recognise all of the documentation required for a particular product, whether that’s a mortgage application, a loan or a new bank account.
Once we’ve identified a document and the important fields within it, we can add meaning to the information by putting it in context. At its most basic level, for example, the name and address on a utility bill can be cross-checked against the name on the application form, but far more is possible. When a document comes in to support a mortgage application, for example, it should be possible to link it not only to a customer’s account details, but also potentially to an individual’s credit record, to the history of the house being purchased, or even the insurance details of the property.
Levelling the playing field
AI-based technology is opening up a wealth of new marketing opportunities. For years, the likes of Facebook and Google have been gathering data from their customers and using this to target them more accurately. In retail, customers take it for granted that the brand offering a new pair of shoes or a tracksuit for the dog will already know that they like brogues and own a Labrador. It’s time for financial services to achieve a similar level of customer understanding. At present some lenders struggle even to recognise a mortgage applicant as an existing customer, let alone to predict their needs.
Our AI-based data extraction technology goes far further than the practical issues of efficiency and time-saving. Yes, processing time can be slashed, customer service improved and compliance made more effective, but in the long term, it’s the improved understanding of the customer that will help you grow your financial services business. There’s a flotilla of fintech startups, including rapidly growing brands such as Revolut and Monzo, that are armed with an appreciation of the importance of customer data, so the established banks and insurance companies need to move fast.
The good news is that it’s possible to simultaneously solve a problem and create an opportunity. You can cut your administrative costs, improve your customer service and make compliance simpler – whilst building the data structure that will in turn build your business.
Ready for the next step? Contact us for more information our request an individual demo or a free trial.
