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Facebook Patent a Sign of Changing Times for Lending

January 1, 2016 | tshapiro

A flurry of reports followed the recent revelation that a Facebook patent could be used to help lenders determine credit risk based on members of an applicant’s network.

Many people find the thought bizarre and uncomfortable. In fact, data from social media being used at all is a step too far for many. Yet, the potential for lenders to make use of this data source highlights the extent to which lending is changing.

In the connected age we live in, huge amounts of data is generated on and by individuals all the time. Harnessing relevant bits of this data can bring about an evolution in credit and lending processes. Before long, individuals may not need to source and gather historical data in support of a loan application.

Insights

Among the latest generation of finance-seekers are many that struggle to secure credit because they lack a credit history. Lenders trying to source information to help them assess a risk level may not find what they need among traditional sources. In this situation, social media can provide valuable insights.

The latest generation of finance-seekers practically exists online, engaging readily with digital channels, increasingly to the exclusion of others. They may be only just beginning to create a credit footprint, but their activity on social media adds up to a rich source of data. The information credit and lending risk assessors need may already be out there; it’s just a case of knowing which bits to tap into, and how to do that.

It isn’t really surprising that ‘new’ data should enter risk decisioning processes. The tools traditionally used for the assessment of creditworthiness are well established and have been heavily relied upon. Since they were put in place the digital age has added to the data available and changed the way it is shared.

Social media data can provide an insight into lifestyle, habits, career history, aspirations. It’s data with an interesting characteristic – it’s less about credit history and financial position, and more about behaviour. Back in the day, local branch bank managers assessed loan applications based on their knowledge of applicants and what people prepared to vouch for them said. Now, behavioural indicators can play a part with a modern-day twist – behaviour turned into bits and bytes is assessed by algorithms and data analytics. Smart technology provides the new and efficient ways to automatically access this real-time data, analyse it and generate insights that lenders can use to make faster, informed decisions.

Shake-up

It’s one of the changes happening to the way loans are decided and progressed. Systems and processes are also getting a shake-up.

Despite living in a digital world, many lending assessments still rely on paper-based, manual processes. The re-keying of information as applications move from one department to another in a financial institution is not unusual, but is increasingly unsustainable.

In a competitive market, lenders are looking to gain an edge with appealing products and services and excellent customer service.

They are looking to consolidate and improve the accessibility of information across business functions to aid end-to-end straight through processing; to reduce multiple information requests for the same data and data re-keying during the same application.

They are looking for solutions to automate the 100 plus tasks involved in establishing a new lending relationship, freeing up staff to focus on the customer, rather than the process. Back-office processes need to stand up to customer expectations set by their experience of the front-end channel, which is increasingly online and designed to be quick and simple.

It should be said that risk decisioning as part of credit and lending processes isn’t the only use of the technology covered by the Facebook patent; it isn’t even the primary one. The main parameters of the technology deal with authentication and content filtering. Whether or not it will be used for loan assessments in the way it is suggested it could be, remains to be seen. Either way, the progression of data use and automated analytics to speed up risk decisioning in credit and lending will continue.