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Data Pre-processing

Ensuring Dynamic Reconciliation Data Pre-processing

If an excellent data extraction logics can determine a successful account settlement, than Ascent AutoRecon© is the right solution.  It eliminates manual data gathering and minimizes blind spots in data.

In today’s fast changing business environment getting data is most critical activity for any organization. Moreover, inaccurate and wrong data will undermine the decision making and ultimately harm the business performance.

Ascent reconciliation solution is developed by highly experienced people, who possess domain / functional knowledge, hence the rule sets are high yielding. Considering the dynamic banking environment, we can fine tune the rules to achieve percentage.

AutoRecon©Software offers an integrated, enterprise scale, robust platform for Data Stewards/Custodians to perform full breath of data management services including Data Profiling, Standardization, Correction, Enrichment, Transformation, De-duplication, Encryption, Masking and Integrated Exception Management.

data-preprocessing

Additionally, Ascent Data Management  supports seamless data source integration, automatic data extraction, cleansing, match & merge, cluster analytics, archival management from virtually any cluster of enterprise system.

While other solutions in the market have dependency on existing jobs, AutoRecon© can be scheduled for complex matching.

Functionalities

AutoRecon© validates the incoming data for consistency, accuracy and logical data checks (Date of Transaction, Time of Transaction, Card No., Sequence No, Terminal ID etc). These logics can be scheduled as per requirement to make the extraction faster.

Ascent reconciliation engine can fetch the transactional data virtually from any banking system like:

  • Core Banking Systems
  • Network Switches
  • POS Device Network
  • ATM Machines
  • e-Payment Applications
  • Visa / Master / NFS Networks

It reconciles them after performing the required data cleansing activity such as, Validations, Data Transformation, Transaction Enrichment and Data Encryption\Masking.

All the transactions, which encounter issues during data cleansing activity, are kept separately so that they can be reconciled after the issues have been resolved.

transactional-data-from-banking-system

Some of the pre-processing jobs are scheduled at specific time, after completing STP, to generate exception reports.

Complex rule based matching – using multiple data sources AutoRecon© is scheduled for complex matching:

  • In case of many to many, we use grouping criteria and match records as bulk
  • Netting of one set of data with another is used to achieve a good percentage
  • Reference Matching
  • Fuzzy Matching

Finally, duality of AutoRecon©, in terms of matching, is excellent because it detects duplicate transactions very efficiently.