Finance Vertical Webpage

Monte Carlo for Financial Services

Make your data quality as stringent as your industry regulations.

Integrate data quality monitoring tools into your existing stack with Monte Carlo
Affirm
Checkout.com
Credit Karma
Payjoy
Sofi

Leading data teams in financial services choose Monte Carlo

Learn how Clearcover, an automotive insurance leader, increased data quality coverage by 70 percent with Monte Carlo.

Benefits

  • 70%

    increase in data quality coverage

  • 50%

    faster resolution times

“We no longer had to tailor specific tests to every particular data asset. All we really had to do was sign up, add the security implementation to give Monte Carlo the access that it needed, and we were able to start getting alerted on issues. Monte Carlo gave us that right out of the box.”

Braun Reyes

Senior Manager of Data Engineering

Data Stack

  • Rising data volumes stemming from business applications and departments

  • Lack of domain knowledge into department-specific data sources

  • Complexity associated with their growing data stack implementations

  • Reduced implementation times with out of the box coverage for new datasets

  • Automated data lineage creation to isolate and remediate incidents

  • Custom field health thresholds to meet internal SLAs

Benefits

  • 70%

    increase in data quality coverage

  • 50%

    faster resolution times

  • Rising data volumes stemming from business applications and departments

  • Lack of domain knowledge into department-specific data sources

  • Complexity associated with their growing data stack implementations

  • Reduced implementation times with out of the box coverage for new datasets

  • Automated data lineage creation to isolate and remediate incidents

  • Custom field health thresholds to meet internal SLAs

Data Stack

“We no longer had to tailor specific tests to every particular data asset. All we really had to do was sign up, add the security implementation to give Monte Carlo the access that it needed, and we were able to start getting alerted on issues. Monte Carlo gave us that right out of the box.”

Braun Reyes

Senior Manager of Data Engineering

Use cases for financial technologies

Achieve data integrity

Make sure that third-party data is tagged and classified appropriately.

Scale proactive incident resolution

When it comes to your customers’ finances, one inaccurate field can have detrimental effects. Invest in a data quality solution that alerts you before incidents occur.

Increase customer engagement

Leverage application data to improve the user experience at each stage of the customer journey.

Monte Carlo is a very good way for us to understand our data quality at scale.

Trish Pham, Head of Analytics
Hear their story

Use cases for financial services & insurance

Make accurate decisions

Ensure your consumers are ingesting reliable data to drive financial decision making.

Remove the risk from risk management

You have models to understand where risks are in your portfolio, but you need to know where risks exist in your data, too.

Maintain SOX and more

Ensure your service is industry-compliant with accurate data to avoid costly fines and reputational damage.

Now, we can start having those proactive conversations to prevent downtime before stakeholders are affected, versus finding out after the fact that something was broken and then rushing to get it fixed.

Braun Reyes, Senior Manager of Data Engineering
Read their story

Learn more about our product

Detect

Detect

Out-of-the-box coverage across all your data tables, opt-in monitors for key assets, and monitors-as-code.

See how
Resolve

Resolve

Don’t just sound the alarm when data incidents occur. Empower your data teams to resolve incidents in minutes, not days.

See how
Prevent

Prevent

Rich insights enable your team to proactively ensure data quality, and make better infrastructure investment decisions.

See how

Use data observability to lead the financial services industry

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