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Enabling a Global Bank to simplify its Reconciliation and Reporting​

Leading Global Bank’s Shared Services Center

India

Situation
  • Cost team spending considerable time on downloading, processing and producing  data heavy month close files manually​​
  • Current tools provide limited insights and lack functionality to provide transaction level drill down ​​
  • Numerous ad-hoc requests being received and catered to during month end​​
  • Delivery of critical cost MI is dependent on manually intensive and iterative front to back reconciliation process which takes 15+ days​
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Solution
  • Nanobi’s LiquiData Platform automated and simplified the acquisition of structured and unstructured data across multiple applications​​
  • Insights generated using statistical techniques and sent to users who can then drill down & provide commentary​​
  • A two step Reconciliation process using Deterministic and Probabilistic which is layered on ML algorithms like Text, Pattern Detection, Phonetics and Edit Distance techniques to improve the matched records​

​The 3 Use Cases with different user groups within the bank working on

  • Insights on Cost Reporting​​

  • Cost Allocation and Reconciliation of Costs​​

  • Reconciliation of Trade, Nostro, Accounting​

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10+% 

Overall Efficiency at a Global Level and reduction of costs in Year 1

30% 

Reduction in TAT time for month end reconciliation process to complete and No. of FTEs​

40% 

Increase in Auto reconciliation ​​of trades

Results​
  • Expected improvement in efficiency to be about 10% globally​​
  • 40% increase in Auto-reconciliation of trade using ML/AI algorithm​​
  • Reducing the turn around time of reconciliation process from 15+ days to 6 days and reduction in number of FTEs by 30%​​
  • Self serve functionality expected to eliminate manual effort on month close files​​
  • Provide business and finance with the ability to create flexible dashboards and analytics ​
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