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Banking Case Studies Decision Support General Consulting Underwriting Strategies

Adjustment of initial line assignments and authorization strategies helps client achieve growth & loss targets

line assignments authroization strategies

Challenge:

A PAG client in the US credit card market was not achieving its Year 1 growth and loss-rate projections on a new credit card product.  Balances were growing in the lower half of the credit spectrum and activation on higher FICO balances was not happening at a rate to offset the lower credit balance growth.

PAG Solution:

PAG reviewed the Client’s underwriting approach to see if adjustments could be made to the existing account management strategies to stimulate balance growth in the proper areas.  PAG found the Client was being too conservative with its initial line assignments and authorization strategies.  Average credit lines for 680+ FICO customers were only $1,800 while the Client was blocking nearly 20% of transactions at the point of sale. These higher-end customers simply weren’t using the card: They weren’t being assigned sufficient credit lines to meet their shopping needs and using the card was a hassle.

PAG used refreshed Vantage scores along with other data attributes to quickly build credit lines in a revamped Credit Line Increase (CLI) strategy so those higher-end credit customers could see significant credit limit increase to meet their shopping needs. PAG also rebuilt the authorization strategy to fit the demographics of the Client’s portfolio, resulting in fewer stoppages at the POS without a significant increase in transactional fraud.  PAG also designed Reissue strategies so the Client could continue to pursue the right credit growth when the initial batch of cards expired.

Client Benefits:
  1. PAG was able to increase balance growth in customers with an initial line of $2,000 or greater by 40% while lowering overall Year 1 delinquencies on the portfolio by more than 10%
  2. PAG complemented the enhanced CLI program by loosening the authorization strategies, enabling higher-credit customers to feel more comfortable using their cards. The resulting model and analysis increased transactions per month on active users by more than 20% with a minimal increase in fraud losses to only five basis points.
  3. PAG worked with the Client’s marketing team to deliver digital and direct mail messages to inactive customers by promoting its reward platform and mobile application. The results were a 22% increase in first-time use of the card in the next nine months.
  4. The Client exceeded its Year 1 growth targets and has since seen no substantial risk in fraud or credit losses. Growth continues to trend in the right direction.
  5. The Client has re-engaged PAG to have a PAG SME on its risk council. That person is helping guide account-management strategies while making sure learnings are being shared with the underwriting team to ensure wins are seen in the initial book of business for future portfolio bookings.
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Banking Case Studies Data Warehousing Underwriting Strategies

Fintech kicks off card program after PAG merges four data streams into a relational database

fintech credit card relational database

Challenge:

One of PAG’s clients – a medium-sized fintech with a long history of customer loyalty – wanted to enter the U.S. card market to leverage its strong customer relationships. The client also had good data history on their customers through its non-card products, but it was in multiple legacy systems and the data was not designed to be migrated from one system to another. The Client also did not have an internal data warehouse to store all of its data nor did it have internal Risk expertise to merge data and build the strategies and reporting packages it needed to monitor a credit card portfolio.

PAG Solution:

PAG was asked to evaluate the fintech’s data streams and infrastructure and determine how it could take advantage of its rich data history.  PAG identified four major system feeds that contained valuable data and had customer-identifying data to unify that data.  PAG used its GOBLIN enterprise data platform to automate the four data streams into one relational database.

PAG merged the data sets into a series of unique tables that are now available each day for querying.  PAG then built an initial underwriting strategy, merging the Client’s existing relationship data with PAG’s 30M-record bureau data set. That allowed us to build detailed performance and profitability models. After getting approval on the underwriting strategy from the Client and its sponsor bank, PAG built a robust set of monitoring reports and automated their delivery through GOBLIN so the Client now starts each day reviewing the performance of its new card portfolio and making decisions to run its business more effectively.

Client Benefits:
  1. PAG merged all four data streams into a relational database that is ready for querying each day by the Client or PAG by 4 a.m.
  2. PAG helped architect the data environment on the new cards being booked so their data from a third-party provider is also streamed into GOBLIN and available for querying and merging back to the original relational data streams.
  3. The underwriting model PAG built passed a regulatory audit and has exceeded Year 1 growth targets by 5% while coming in 10% lower on Year 1 loss targets.
  4. PAG supported interviews of Risk personnel for the Client, which now has a small team that is creating monthly dashboards and executive presentations for senior management.
  5. PAG was recently rehired to build new Credit Line Increase, Authorizations, and Card Reissue strategies in conjunction with the Client’s new Risk Team.
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Data Warehousing

Beating Back the Beast: Cybersecurity in the Financial World

You read all the IT reports, you follow their recommendations, and you pay attention when they inform you of risks and problems. Many of your associates or those you know do the same. Yet somehow, you still hear about breaches in businesses everywhere, including your personal network.

The reality of the current climate is that it’s not IF but WHEN with data breaches. Data breaches are an evolving, everlasting problem for all businesses. Targets for data breaches can extend from the “mom and pop” corner stores to every Fortune 500 company. While you are growing your business, hackers are growing theirs. Equifax or not, your data has a big price tag.

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