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What are the challenges with financial data?

Financial services continues to be a rapidly changing industry, which produces mountains of data on its customers, their spending habits and financial information.

What is the problem

Compounding that data, firms have marketing and website data, mobile application data, debit and credit card spending information, and banks deal with an immense amount of customer data.

  • Did you know that mobile banking apps are one of the three most used apps in the United States? *
  • And, there will be 4.3 million ATMs installed across the globe by 2020.** On average there are 30 – 40 daily transactions per ATM.*** That’s over 172 billion ATM transactions daily.
  • Also, fraud is also on the rise. In fact, the problem is estimated to be $70B this year alone. *

What is hiding in all the data a Financial Institution has?

Imagine all of the important patterns, trends and changes that are hiding in the data that banks and financial institutions have to make sense of in order to obtain a competitive advantage.

  • How are customers leveraging new mobile banking applications? Are those applications working (or not)?
  • What are the trends impacting their best-performing customers? And, how do they retain and create more of these customers?
  • How can banks fine-tune their marketing to capture clients that would be a great fit for their services?
  • Are there early indications of card fraud emerging across your merchants or products?

Even with a team of full-time data scientists, financial institutions are fighting a big battle to analyze and quickly take action on all this data.

“As a credit card issuer, we need to find and stomp out systemic fraud quickly. We leverage AI and Outlier’s Automated Business Analysis platform to help us shut down systemic fraud sooner, saving days or even weeks. In the past few months, Outlier found a few instances that have saved us over $900k.”

Project Manager, Fraud Analysis Team
A Leading Credit Card Issuer

What if Financial Services could easily and automatically:

  • Identify challenges and opportunities in online, mobile and in-store banking to track consumer behavior.
  • Ensure they have no data quality challenges before making data-based decisions.
  • Track shifts in banking transactions to discover early patterns of systemic fraud.

Outlier helps solve this problem with Automated Business Analysis

Outlier, an Automated Business Analysis platform, analyzes customer and business data every day so that you know where to focus your time and resources.

  1. Without any configuration, Outlier delivers unexpected changes and root causes in your business data, in the form of a curated set of insights, specific to your job function.
  2. Outlier’s insights transform your marketing, finance and fraud strategy to keep you ahead of the competition.
  3. Outlier integrates seamlessly across cloud-based platforms and SQL databases in a matter of minutes.

Financial Services Example Story

Automated Business Analysis works for Financial Services:

  • Marketing teams within Financial Institutions need to track their marketing programs that target new card acquisition strategies and customer loyalty efforts. With Outlier, these firms can quickly identify trends with customer acquisition that they can capitalize to deliver more qualified leads and reduce the sales cycle.
  • Outlier’s automated platform is capable of identifying early patterns of systemic card fraud even if it only impacts a small percentage of overall transactions. This helps teams proactively investigate and squash organized crime before it spreads, potentially saving millions.
* 2018 Citi Mobile Banking Survey
**Statista
***ATM Depot
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