Data Analysis & Insights for Financial Industry

Business Impact

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Whether mortgage banks, payment processors, insurance companies, or any financial provider, digital products have made a turning point in improving service quality and overcoming shortcomings.

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Big data analytics has become one of the key components for helping financial institutions analyze a large wave of information to get financial insights, predict future trends, & calculate risks.

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Instead of scraping data manually from sites and deriving solutions with limited data, we can use a data engineering model to scrap or aggregate data from multiple sites and derive actionable insights from a large volume of appropriate data, and make smart decisions easily.

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We have helped a Finance company in getting data-driven insights from 20 years of data aggregated from multiple sites, which helped them in decision making.

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In this solution, we have scraped stock data from multiple sites, followed by Complex custom financial ETL calculations.

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Merged missing data points from multiple sites and verified using a third-party website. The extracted data is provided to the client in the form of an Excel template that contains 20 years of stock data

Technology Stack

Solution Approach

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End to End solution with bot input (stock name) – data will be crawled, ETL processed, and delivered in customer required excel template

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Build a framework to handle different platforms and deployed it in airflow for an automatic run every week

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

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50+

AI & ML
Engineers

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40+

AI & ML
Projects for
reputed Clients

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5 yrs

in AI & ML
Engineering

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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