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Banks and Mortgage Providers Are Using Big Data to Transform the Lending Process.

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High quality data from a variety of sources allows the financial sector to make faster, more informed decisions.

by Sid Probstein, Chief Technology Officer

Thanks to the exponential growth of user-friendly big data applications, coupled with the falling costs of access to these tools, the financial services industry is undergoing a radical transformation.
It’s beginning to change the way banks evaluate risk and judge the real value of a potential customer - and act accordingly!

That’s good news for all aspects of the industry, but it’s especially good news for smaller financial institutions that can make use of business agility and turnaround speed to compete for new business at a lower cost. It provides a new opportunity to cater for a rising generation of homeowners who have been ‘mobile first’ for most of their adult lives.

‘Big Data’ refers to the massive and diverse streams of data generated in the digital economy that can be gathered, processed and used to make valuable insights. From transaction analysis to geolocation, social media, spending habits, predictive analytics and more, the pervasive use of mobile devices and online transactions has produced a complex, more nuanced portrait of consumers.

A win-win situation for companies and consumers.

There are many benefits to higher quality underwriting, not only for banking and mortgage providers, but also for people who come forward looking for loans without any reasonable expectations of meeting the payments. Intelligent storage and ability to rapidly find and link disparate data is vital in unlocking this value.

AI Foundry is passionate about capturing data in all its forms and storing it for easy access.

Big data can help provide quality loans to people who have no credit history, particularly amongst the Latino community in America. “Sometimes the best thing you can do is tell someone that you can’t make a loan now because they don’t have the resources to pay us back,” says Oportun’s chief executive officer, Raul Vazquez. But in order to do that, you need to have the right information to draw upon.

In servicing people with very little credit history, big data is an invaluable tool in building a portrait of someone’s credit-worthiness. ‘Mobile records, DTH recharges, online spending, click behavior and social media presence’ are valuable sources of alternative data.

In the digital age, many consumers with limited financial records still manage to accumulate reams of unstructured data which can be evaluated to build an informed portrait.

These models succeed, according to HortonWorks “because they use a much broader base of data types - including factors such as a prospective customer’s geolocation and transaction history - and are able to correlate things like comparable people who behave in a particular manner.”

There has already been a measurable improvement in the quality of loans delivered, due to “on-demand access to granular data on active loans, accrued equity, and the ability to generate quicker and more accurate appraisals”.

These developments are delivering real change and better results in the banking industry and are driving innovation in all sectors of the industry.

Image Source: Shutterstock

How else is data being used in the industry?

  • Telematics is being used to keep track of a customer’s driving habits and send data back to the carrier in real-time.
  • Jumo, a South African startup, taps into cell phone data to lend to unbanked ‘thin file’ customers.
  • Small business funder Kabbage uses shipping patterns to evaluate a customer’s credit risk.
  • Biometric authentication - such as voice, facial features and fingerprints on sophisticated mobile devices - is being used to facilitate the opening of new accounts.
  • Upstart Loan Dave Gerarad

Strike a balance between Human and Tech integration.

While the integration of technology with these fundamental services is invaluable, it’s very important that we don’t overlook all the advantages of keeping the human element alive in decision-making.

Leaving AI and Big Data completely in control of the decision-making process would mean that many human factors would not be considered, as they are somehow intangible and character-driven. Yet we know that people are more than what they simply appear to be on-screen. AI cannot fully evaluate a person’s character, nor the opportunity they may ultimately represent. So a healthy balance is needed between human insight and unbiased data processing, in order to achieve truly great results.

One of the biggest advantages of embracing data analytics is the speed at which decisions can be reached. The faster a company is able to gain insights from its data, the better they are able to serve their customers.

Real-time insights are possible with sophisticated modern data storage, indexing and analytic techniques. Combined with easy-to-use dashboards allow companies to present and analyze data, these approaches facilitate speedy decision-making.

Predictive Analysis.

Big data is not only useful for analyzing existing data, but it’s also proving invaluable in predicting future outcomes and suggesting a course of action based on patterns already present in historical data.

For example, high-value customer segments can easily be identified in order to facilitate optimized targeting and improved customer acquisition; customer buying habits can be identified with a view to offering suitable banking products and services; personalized tips and suggestions can be sent to clients based on their recent activities.

Using this data responsibly to develop stronger products and to help clients make better financial decisions should be the ultimate goal when embracing big data in the financial services sector.

AI Foundry is committed to transforming the ways organizations use their digital data. We work with the financial services industry to extract insight and value from data, and improve the quality of business and service that you can deliver.

Get in touch to find out more about what we can do for you.

Sources:

https://blog.aspiresys.com/digital/big-data-analytics/the-future-of-underwriting-with-big-data/

https://www.fastcompany.com/40436683/this-online-lender-uses-data-analytics-to-serve-borrowers-who-lack-credit-scores

https://hortonworks.com/article/big-data-analytics-and-better-modeling-are-changing-the-mortgage-industry/

https://www.newgenapps.com/blog/10-ways-predictive-analytics-help-the-banking-sector