AI/ML - ValueLabs

End-To-End Case Study

Geo location

US-Midwest

Platform

Web, Mobile

Service

Intelligent Automation,

AI&ML

Challenges

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.

Inefficient onboarding

Time-taking procedure

Manual operation

Implementation backlog

Provide a more efficient system for millions of consumer and business clients onboarded every year
Create a configuration automation process and automatically validate data according to the client’s business rules
Increase the quality of implementations while decreasing deficits
Convert client requirements into the XML and DB-script client configuration files

Our Solution

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.

Solution Impact

Entity details extracted

From the client configuration worksheets and generated proprietary

XML schemes uploaded

Into the configuration portal for setting up the FI, reducing the customer onboarding time

Automatic data validation

Enabled in the portal and saved it into the system, leading to quality configurations and reducing defects

Our Approach

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.

Data, BI-Analytics and Intelligent Automation – Redefining the global banking and fin-tech industry

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Creating as-is configuration automation for streamlined operations

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:

Developed a process for autoconfiguration using the client’s XML and DB-script configuration files
Extracted the requirements from the configuration worksheets and put them in a structured format such as JSON
Developed a rules engine to convert the structured requirements into the client’s proprietary XML files
Developed the basic financial institution instance setup details into DB SQL scripts
Loaded the client’s XML files and SQL scripts into the configuration portal
Verified the financial institution client instance

Creating as-is configuration automation for streamlined operations

Set up a requirement-gathering web portal

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:

Developed a requirement portal to collect quality requirements and enable autoconfiguration
Designed data templates that support the client’s complex business logic for both nested and dependent requirements
Created a responsive web portal driven by data templates
Built and added in-line error validations to check the data quality entry
Integrated with the rules engine to enable autoconfiguration

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.

Set up a requirement-gathering web portal

Business Impact

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.