About the Client
The client is a prominent advisory organization offering services across transaction advisory, financial due diligence, investment assessments, and risk-focused consulting. The firm works closely with private companies, investors, and professional advisors to manage complex situations effectively. Known for its ethical approach and collaborative way of working, the client focuses on delivering clear insights and reliable guidance while always keeping client goals at the center of its work.
Business Challenge Faced by the Client
The client’s loan approval and due diligence process is highly time-intensive due to its heavy reliance on manual effort and fragmented data sources. Critical information required for background checks is spread across Salesforce and a large volume of unstructured SharePoint documents. These documents exist in multiple formats, including Excel, PDFs, Word files, and email files. As a result, the client must manually search, interpret, and consolidate information for each borrower, significantly increasing processing time.
Additionally, the lack of a centralized view and advanced analytics in BFSI limits the client’s ability to quickly identify relevant insights. The absence of automation and centralized data access limits visibility and slows decision-making. This fragmented and unstructured data landscape increases operational effort and delays loan approval decisions, making the entire process inefficient.
Kasmo’s Solution
To address the challenges of manual processes, scattered data, and limited analytical capabilities, Kasmo implemented a Snowflake solution. By data integration, combined with automated data pipelines and analytics in BFSI, we enabled faster insights.
Unified Data Ingestion into Snowflake
We designed a unified data foundation by ingesting both structured and unstructured data into Snowflake. Structured data was extracted from Salesforce by pulling all relevant non-zero objects and applying required transformations and validations during load. For unstructured data stored in SharePoint, our team built custom ingestion pipelines to handle complex Excel files containing 80–90 sheets per file, along with PDFs, Word documents, and email files. This ensured all data was centralized, cleansed, and analytics-ready.
Structured Data Analysis with Snowflake Cortex Analyst
On top of the Salesforce datasets in Snowflake, Kasmo implemented Snowflake Cortex Analyst to enable intelligent analysis of structured data. This allowed users to query large, multi-table CRM datasets efficiently and receive responses. Cortex Analyst reduced dependency on complex SQL queries and accelerated insight generation.
Unstructured Data Analysis using Cortex Search
Kasmo enabled Snowflake Cortex Search on extracted SharePoint document tables to unlock insights from unstructured content. This provides semantic search capabilities across workpapers, reports, checklists, and email communications. Users could easily get relevant information without manually scanning documents, improving productivity and allowing intelligent analytics.
Analytics in BFSI with Snowflake Intelligence
Kasmo enabled Snowflake Intelligence by combining agents for both structured and unstructured data. This layer enabled natural language querying and context-aware responses across all data sources. Users could ask business questions in plain language and receive insights that span documents, supporting faster, more informed loan approval and risk assessment decisions.
Key Results Achieved
~95% Accuracy in Insights
Achieved high accuracy and consistent results across structured and unstructured data, building trust in AI-driven and agentic analytics.
Reduction in Manual Effort
Automated data ingestion, document processing, and intelligent search eliminated extensive manual file reviews, enabling teams to focus on higher-value analysis.
Faster Decision-Making and Time Savings
Agentic analytics powered by Snowflake Intelligence accelerated insight generation and reduced analytics time.
Context-Aware Analytics
Enabled natural language querying and cross-data insights across Salesforce and SharePoint sources, delivering a scalable analytics experience.
