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Creating highly personalized campaigns with anonymized customer database

A robust customer database allows for more efficient and effective campaigns

6

increase in campaign production efficiency

$2M

Credit Bureau expense savings

2

increase in campaigns executed

High expense but low impact

A leading U.S. bank needed an anonymized customer database to help improve their cross-selling and prospecting efforts. The challenge: the Fair Credit Reporting Act (FCRA) limited their access to Credit Bureau data, causing slow processing and execution timeframes at a high cost. The bank was also outgrowing their on-premise database which lacked scale and flexibility.

Epsilon PeopleCloud Customer breathes new life into a stale database

PeopleCloud Customer's three main features helped achieve the bank's goals:

Anonymized customer data

PeopleCloud Customer maintained an FCRA-compliant environment. With built-in identity capabilities, the solution houses consolidated, anonymized and enriched existing client profile with credit data—all of the data necessary to pre-qualify clients for product offers combining Relationship Data/Scores, Credit Bureau Data and dynamic targeting criteria. This means the bank no longer has to rely on the Credit Bureau to segment their data and execute campaigns.

Smart modeling

Credit, analytics, and predictive model development teams could analyze current and historical credit and behavioral performance on clients. Building and validating models with client relationships, performance, credit and 3rd party data could all be done in a compliant way.

Fully scalable infrastructure

PeopleCloud Customer's scalable infrastructure provides increased agility and efficiency today and will ultimately expand to meet increasing client engagement demands. This will enable the bank to prospect for future clients using a variety of data elements (credit risk, proximity to branches, and wallet share).

"By having the full customer view from PeopleCloud Customer, we’re able to understand our client’s capacity for lending. Before it was more of an educated guess. Now we’re able to broaden our approval criteria and open up our lending products to a larger group without taking on additional risk. We can make safe credit decisions."
Senior VP of Analytic Modeling, leading U.S. bank
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