Improving FinTech Sales Through AI-Powered Deal Analysis​

Improving FinTech Sales Through AI-Powered Deal Analysis​

Success Stories

Improving FinTech Sales Through AI-Powered Deal Analysis

60%

Faster decision making

20%

Increase in deal win rates

40 mins

Analysis time, down from 6-8 hours

Summary

A fintech company struggled with time-consuming manual transcript analysis for lost deals. Our AI solution reduced analysis time from 2-3 hours to 40 minutes, providing precise insights and enabling faster, more efficient decision-making.

About The Client

The client is a leading provider of subscription billing and revenue management solutions, serving over 4,500 subscription-based businesses worldwide. They specialise in automating revenue operations, including billing, invoicing, payments, and revenue recognition, to help businesses manage and grow their recurring revenue streams. Their platform caters to various industries, such as SaaS, e-commerce, e-learning, and media, enabling companies to streamline subscription management and enhance operational efficiency.

The Challenge

The client faced significant hurdles in their deal analysis process, which impacted their efficiency and decision-making capabilities. The key challenges were:

  1. Time-Consuming Deal Analysis: Analysing lost deals involved manually reviewing video call transcripts, which took an average of 2-3 hours per deal. This lengthy process delayed decision-making and drained valuable resources.
  2. Limited Insight Extraction: The manual method lacked the ability to quickly extract meaningful insights. This inefficiency made it challenging to answer specific business queries, leaving opportunities for strategic improvements untapped.

These issues resulted in operational bottlenecks, slower response times, and reduced competitiveness in decision-making.

The Solution

We provided an AI-powered solution (deal analyser) tailored to the client’s specific needs. Key features of our solution included:
  1. Advanced Summarisation: Using Large Language Models (LLMs), individual call transcripts were Summarised and consolidated into a single, comprehensive summary, eliminating the need for manual review.
  2. Consolidation: The generated summaries were then aggregated into a single, comprehensive summary for each deal, providing a holistic view of the issues leading to lost opportunities.
  3. Scalable Integration: To ensure seamless adoption, our solution included a data integration layer to connect the client’s existing systems and datasets for efficient data flow.

Technology Stack

  1. Large Language Models (LLMs): Used for generating comprehensive summaries and precise responses to business queries.
  2. Natural Language Processing (NLP) Algorithms: Enabled topic-specific insights and streamlined analysis.
  3. Vector Databases: Facilitated contextual querying for accurate and relevant answers.
  4. Data Integration Layer: Ensured seamless connectivity with the client’s existing systems, improving data accessibility and flow.

Results

Our solution delivered transformative results, including:

  • 60% Faster Decision-Making: Automated document verification enabled quicker assessments, significantly reducing delays.
  • 20% Increase in Deal Win Rates: Faster processing and improved accuracy gave the client a competitive edge in closing deals.
  • Analysis Time Reduced to 40 Minutes: The AI solution cut down processing time from 6-8 hours to just 40 minutes, drastically improving operational efficiency.
  • Actionable Insights: The ability to generate precise responses to specific business questions significantly improved operational efficiency and strategic planning.