Data quality for finance and insurance
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How bad data affects finance and insurance?
Financial
Unreliable address data
No foolproof method exists to verify address information and geocode latitude and longitude values.
Disparate siloed datasets
Impossible to find the correct view of data as insurers tend to pull data from multiple sources and vendors.
Risky financial data
Financial institutions incur significant long-term losses by basing risk assessments on false information.
Obsolete IT infrastructure
Considerable financial data is still based on outdated legacy mainframe systems that create data conversion challenges.
Slow data digitization
Finance and insurance businesses experience slow and gradual data digitization as compared to other industries.
Inconsistent data standards
Lack of common and standardized data structures, models, and definitions create duplicate records.
Solution
DataMatch Enterprise – Manage financial risk with confidence
Customer Stories
See what financial institutions are saying...
Business Benefits
What’s in it for you?
Detect financial fraud
Detect identity theft and suspicious transaction activity with minimal false positives through accurate matching of unique identifiers and detection of duplicate records.
Ensure regulatory compliance
Avoid costly litigation and penalties by implementing standard rules for inconsistent records as well as custom patterns for proprietary data.
Minimize transaction risks
Anticipate transaction risks such as likelihood of default and other warning signals by removing siloed datasets.
Speed up customer onboarding
Eliminate frictions to accelerate the customer journey process with a single, consolidated view of data across multiple touchpoints.
Reconcile conflicting entities
Resolve similar customers arising from name variations, data entry errors, and inconsistent data standards with fuzzy matching and standardization features.
Reduce returned mails
Verify customer addresses and geocode to yield latitude, longitude, and ZIP+4 values to improve mailing accuracy and reduce packaging costs.
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
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