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Data Management in Financial Services | New Era Technology

Written by New Era Technology | May 27, 2020 4:00:00 AM

Data management in banking poses unique challenges. You’re dealing with vast amounts of sensitive information, rigid regulations, and security issues, all of which can complicate the process of actually managing and using the data you collect.

Given our long experience with data management in financial services, we jumped at the chance to help a regional bank streamline their data strategies. After helping them transform their operations through an enterprise data management program, the client saw a staggering 1,054% ROI over three years.

Challenge

A regional bank’s need to prevent and reduce credit losses from defaulted commercial loans was symptomatic of a greater challenge. The bank needed a data management program that could help it more effectively manage different aspects of the business.

Read on to learn how a new finance data strategy helped our client triumph over the core challenges of 1) meeting stringent regulatory demands for more robust reporting and 2) dealing with issues surrounding its data and data access.

A Common Challenge in Banking

Each year, banks approve billions of dollars in commercial loans. Throughout the approval process, documents are signed and covenants are created to ensure that funds will be repaid. Funds not repaid within the outlined term can result in higher capital requirements on the institution and, ultimately, credit losses for the bank.

Most often, the only indicator that a loan has gone bad is when payments become delinquent, which is too late. Our client wanted to analyze such scenarios well in advance to prevent payment default. And that’s what led to the need for an improved bank data management program.

Solution

Our team’s assessment revealed that this bank’s ability to quickly uncover and manage credit loss was constrained by a lack of consistent, quality data, and by static reporting and manual processes. In addition to regulation issues, other issues to resolve included:

  • Incomplete and inconsistent data
  • A desire to have more time to analyze data before monthly, quarterly, and yearly reporting
  • An inability to see the “story” behind the data
  • An inability to interact with the data through visualization tools

Summary of Deliverables

  • An Enterprise Data Management framework that included culture, people, process, and technology change management
  • The enablement of a new data leader, i.e., a chief data officer
  • Numerous executive dashboards:
    • Status dashboards – accrual, AQR status, charge-off and recovery, delinquency, and others
    • Trend dashboards – commercial portfolio, retail and mortgage portfolio, charge offs, large dollar exposure, etc.
    • Operational dashboards – delinquencies and maturities
    • Alert dashboards – accruals, loan structure alerts, AQR alerts, etc.