Approximately 26 million Americans have no credit history with a national credit agency, according to the Consumer Financial Protection Bureau (CFPB). This creates a tremendous barrier to accessing credit.
On December 3rd, an Interagency Statement was issued on the use of Alternative Data in credit underwriting with an emphasis on the consumer protection aspects of using such data. The group of agencies issuing the statement include The Board of Governors of the Federal Reserve System, the Consumer Financial Protection Bureau (CFPB), the Federal Deposit Insurance Corporation (FDIC), the National Credit Union Administration and the Office of the Comptroller of the Currency (OCC). Alternative Data is defined in the statement as “information not typically found in the consumer’s credit files of the nationwide consumer reporting agencies or customarily provided by consumers as part of applications for credit”. Now such data can be utilized for the purpose of assessing credit worthiness.
This is a welcome update to the work that has been on-going over the last few years. Since 2017, the use of alternative data has been a key area of focus for the CFPB. At that time, they issued an RFI to explore the benefits and risks of utilizing alternative data sources. In the time since, the CFPB issued a No-Action Letter to a fintech using this type of data and also published positive results of their due diligence work with this entity on the CFPB blog. Now roll forward to December 2019 and we have a joint statement from 5 agencies stating “The agencies recognize alternative data’s potential to expand access to credit and produce benefits for consumers. To the extent firms are using or contemplating using alternative data, the agencies encourage responsible use of such data.”This represents a major leap forward in the recognition and acceptance that alternative data sources can offer a more complete, robust and timely profile of a potential financial services customer.
Utilizing Alternative Data
Alternative data can include various sources depending on the specific purpose. For a financial services company these may include social/web/app media and related transactional history, account spending and purchasing patterns, call center data, mobile data, ATM history, etc. This data may be sourced internally or externally from third parties. As long as the data is used fairly and equitably, it can provide better insight into the credit worthiness of an individual.
The use of alternative data in financial services is not a new concept. The capital markets industry has been using such data to augment their research and projections surrounding investment activity for some time. By looking at the data in aggregate, correlations are made to help predict and anticipate market activity.
The decision by the governing agencies in the US is now advancing the use of alternative data on a more individual, personal level. This will impact the credit approval or denial process of those 26 million people in an entirely new way. A credit score will still matter, if it exists, but now other characteristics and correlations can be considered for the credit worthiness of the individual to be determined.
How to Access and Store the Data
Now the question becomes how to access this data and how to manage the quantity of data. As mentioned, alternative data comes from a variety of sources. This data is structured and unstructured. It will come in both batch and streaming forms. Financial institutions have already been working hard to get control over their traditional data sources and disparate data repositories to perform analytics. An example of a financial institution doing this successfully is Santander. The addition of alternative data is another component of their data and analytics strategy that financial services companies must address. The ability to combine both batch sources and streaming sources of data and ingest multiple formats to get a comprehensive view of customers is crucial to providing a better experience. Real-time data is already critical to timely decisioning – to provide account recommendations, a timely offer, etc. Alternative data in real-time is the next further advancement to the real-time information. In a competitive environment of traditional and non-traditional lenders, the ability to assess credit worthiness and make an offer quickly will decide who wins a customer. Financial services companies are operating in a fiercely competitive environment enabled by technology advancements. The use of alternative data to offer products and services appropriately matched to prospective customers is a powerful tool in gaining a competitive advantage.
The quantity of alternative data is another challenge when considering the use of it. Sources are growing exponentially – all of our electronic devices are becoming more connected. According to Digital Information World, by 2020 1.7MB of data will be created every second for every person. Therefore, any strategy to include alternative data sources also needs to include a strategy to store the data. Consideration should be given to the value that historical data provides. Trends can be identified based on the more history that is available and this can provide better intelligence as well as inform future activity. However, privacy and security must be managed and maintained carefully. With this new approval to use alternative data also comes the responsibility to use it in a manner that is unbiased and anonymous. The interagency announcement is very clear about the goal to use this data in a beneficial manner that is applied fairly. The data sources provide the ability to gain insight as to the ability of a borrower to repay, but this must be done with a non-discriminatory approach.
At Cloudera, we are already assisting Financial Services companies with how to ingest, store and analyze alternative data sources. Recently, Barclays Bank was awarded a Data Impact Award for their use of data and machine learning models to provide their customers with more relevant financing opportunities. Cloudera provides an enterprise data cloud that enables streaming and batch sources to be consumed and a scalable platform to manage the increasing quantities of alternative data.
Some of our products that assist specifically in such areas include:
Cloudera Data Flow – a scalable, real-time streaming analytics platform that ingests, curates, and analyzes data for key insights and immediate actionable intelligence.
Cloudera Data Warehouse – an auto-scaling, highly concurrent and cost-effective analytics service that ingests high scale data anywhere, from structured, unstructured and edge sources.
We are excited about this interagency announcement and the opportunity it offers financial services companies to provide their customers with products and services that may not have been previously available to them.
For more information about how Cloudera enables Financial Services, visit our website.