Client is a large financial institution that operates globally and offers a wide range of financial products and services. The bank’s MM trade processing department was facing several challenges in terms of efficiency and accuracy. The manual processes involved in handling MM trades were time-consuming, prone to errors, and did not meet the growing demands of the bank’s clients.
To address these challenges, Client decided to implement a Robotic Process Automation (RPA) solution to automate its MM trade processing operations. The bank worked with a leading RPA vendor to design and implement the solution.
Global trade financing is at the core of the partnership between banks and businesses. Although there aren’t many profit margins in this line of work, there are plenty of volumes: by 2026, trade flows are expected to total US$24 trillion.
Banks have recognised trade financing as a crucial pillar of their long-term business strategy in light of this growth trajectory. Market expansion on its own, meanwhile, does not guarantee success. In order to be successful, banks must establish themselves as industry pioneers in trade finance digitisation.
Because financial institutions can only be competitive enough to benefit from market expansion through optimum digitisation, automated processing, and thorough audit capabilities in a multi-step, multi-part processing ecosystem like trade finance.
Trade Capture
RPA Vendor provided components
- Automating the Workflow Processes and approvals
- Vendor Setup and Maintenance
- Data entry of the payment preparation
- Automating processing of payments and bulk payment journal entries to sub system
Trade Processing
RPA Vendor provided components
- Order Processing
- Credit Approval & Customer Master File Maintenance
- Cash Receipt Processing & sending late notices via email
Trade Settlement
Opportunities to Reuse
- Wealth Management
- Shared service
- Banking Operations
- Operation Risk
- Regulatory Control
- Fraud operations
- Branch Operations
- Finance and Accounting
- Production Operations
- Investment Management
Trade Processing
Opportunities to Customise
- Fixed Assets
- Bank Posting
- Reconciliation
- Reporting
- GL clearance
- Consolidation
- Ledger Management
- Cash Application
- Collections
- PnL reporting
- Book closure
- Financial Statements
Data Entry & Data Extraction – Trade Capture and Processing
End to End Trade Capture Process to be Automated, which involves Data Extraction, Field Validation, Data Validation and Perform Automated Data Entry to complete the Trade Capture and Processing Transactions.
Business Processes impacted
- Trade Capture
- Trade Enrichment
Objectives
- Identify the Various “ Input Sources “ – Fax , Email , Posts, Chat , Socio & Mobile etc.
- Define the Data Extraction Fields – Must Have & Good to Have Information
- Identify Source application functionalities
- Design data Extraction engine with cognitive capabilities
- Pre Validation Rules ingested in the data entry engine
Stages of Transformation
- Data Consolidation
- Process study to identify the various sources of data
- Reducing data dimensions and redundancy by combining sources
- Creating a single live database
- Cognitive Data Entry
- Rule Base Data Entry for transactions which involve complex data field validation , followed by data entry
- Reporting Transformation
- Integrating live database with real time analytics with a BI solution
- Creating organization wide rollout plan for automated report delivery
Results
- Achieving an accuracy of ~ 100 % on straight-through data processing resulting in mobilization of H/C to more tactical deliverables
- Cognitive Engine capable of interacting with multiple systems with no system changes required
- Direct Transfer of Trade Statements and Summary as per the Rule based distribution
- Scalable model where adding new reports/metrics are quick and easy
- Automation Achieved for the following :
- Establishing Cash Value Defaults
- Trade Confirmation Defaults
- Custodian Standards & Defaults
- Settlement Instructions
- Transactional Reporting
Suggested Delivery Model: Data Entry & Data Extraction – Trade Capture and Processing
Proposed Delivery Model – Agile Based
Automation creation involves Planning and placing automation on Catalogues by involving Automation Business Leads, Process experts, RPA analysts, Automation Business Leads and Automation leads. This involves workshops and planning meetings.
Automation Implementation: Within a duration of 4-6 weeks, our team access data, Designs and implements along with daily scrum by involving multiple decision makers such as the Automation Lead, RPA Analysts, Automation Architect and Engineers, we make it production ready. This involves daily quick calls, sprint reviews and retrospective meetings.
Service Delivery: Here we manage changes, Monitor Robots, Pass vital knowledge to the team, set up digital governance and showcase projected benefits by involving Business leads and support analysts and engineers. This involves feedback calls.
