Overview
Consolidated Analytics needed to scale due diligence without scaling manual data gathering.
Consolidated Analytics provides due diligence and credit assessment services to banks and financial institutions across India. Their business involves reviewing loan applications - gathering income data, credit histories, property valuations, legal documentation, and other ad-hoc records from multiple sources - before producing structured credit recommendations for banking clients who use these to inform loan approval decisions.
The Business Landscape
Before working with BlueLobster, every loan application at Consolidated Analytics required an analyst to manually gather data from a range of disconnected systems. This included internal banking modules, third-party credit bureaus, property registries, and applicant-submitted documents - each accessed separately, each in a different format, each requiring the analyst to copy information from one place to another. The data gathering stage of each application consumed several hours of analyst time before the actual assessment work had even begun. As application volumes grew, the team was increasingly occupied with data compilation rather than the credit analysis that was their actual value to clients.
The Challenges
The problem had three layers. Speed: each application was slow because of the manual data gathering required at the start. Consistency: different analysts gathered data in slightly different ways, which meant outputs varied depending on who was processing the application. Auditability: because the data gathering steps were manual and undocumented, it was difficult to trace exactly where an input had come from or verify it independently - a growing concern for the banking clients who relied on the outputs for regulatory compliance.
The Solution
BlueLobster mapped every data source used in the due diligence process - identifying every system, API, and document type involved, and assessing how each connected to the others. We then built an enterprise platform that connects simultaneously to multiple internal banking modules and third-party data sources, automatically gathering and structuring all the data required for each loan type. The platform produces a pre-populated assessment file for each application, building a complete and auditable process flow from initial document ingestion to structured credit recommendation. The data gathering that previously took hours now happens automatically - analysts receive a compiled, verified data package and focus their time on analysis and decision-making.
The Results
Loan processing time reduced from days to hours per application. The same analyst team now handles a significantly higher application volume without additional headcount. The consistent process flow improved audit compliance and reduced the inconsistencies in submitted recommendations that had previously required back-and-forth with banking clients. Output quality improved measurably. The business has the infrastructure to scale its client base without the operational bottleneck that had been limiting it.
What's in it for you?
If decisions in your business depend on data that still has to be gathered manually, a Discovery Session is the right starting point.
If your business relies on manual data gathering from multiple systems before decisions can be made, the automation opportunity is significant. A Discovery Session helps us map exactly where the time is being lost and what a connected solution would look like for your specific data sources.
3 days. A clear AI plan. No cost to you.
