Our client has a globally diverse reach, catering to both businesses and consumers, and plays a part in millions of financial transactions annually. As the analysis of contractual information was manual and hence time-consuming, the primary hurdle was to automate the analysis and give an AI/ML solution to accurately visualize all key metrics of the contracts.
The global financial services provider was spending an unusual amount of time on new end-client onboarding. It created a backlog for client implementation. We went through their existing reports and completed an initial phase document with their current reporting process and the business requirements. We utilized the best of data visualization, AI/ML, and intelligent automation solutions for our client’s benefit.
From the client configuration worksheets and generated proprietary
Into the configuration portal for setting up the FI, reducing the customer onboarding time
Enabled in the portal and saved it into the system, leading to quality configurations and reducing defects
We developed an autoconfiguration process using the client’s XML and DB-script configuration files and set a rules engine to convert requirements. We then extracted requirements from the configuration worksheets and converted structured formats into the client’s proprietary XML files. Our experts created a requirement portal and designed data templates to support in-line error validations.
We created as-is configuration intelligent automation to deal with slow and inefficient new employee onboarding. Then we extracted the client’s configuration worksheet requirements and put them in a structured format such as JSON. Next, we converted the client’s configuration files into XML and DB-script. We then used these files to set up the financial institution instance.
To arrive at the solution, we:
To elevate our solution for the Fintech client, we followed up the configuration automation with a web portal to gather the client requirements. We converted the collected data into the client XML and DB-script client configuration files. We used those files to set up the financial institution instance.
Here are the steps we took:
Data fed into the requirement portal is automatically validated based on the client’s business rules and is configured behind the scenes. To improve quality configurations and reduce defects, the rules only allow users to save valid data in the system.
As a result of our meticulous customer experience design solution, we identified the areas of the automation process that could help reduce the onboarding timeline. In the process, we infused artificial intelligence and machine learning to bring forth innovation for our client, who now enjoy the latest technology and enablers.
Improved the customer onboarding timeline
Increased the quality of implementations
Reduced production defects
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