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The platform analyzes and forecasts the financial data of your business for the next 18 months. Grown from the need of having immediate access to the past, present, and future financial performance. The biggest challenge for Financial Companies is to forecast precise financial data. Using complex algorithms and integration with Xero for fast access to the historical data, the app is calculating very fast and shows an overview for all the financial indicators.

The most interesting feature of the platform is that it permits the user to select the financial indicators that he aims to change in the future. After setting those data, the platform is recalculating how the changes influence the other indicators.

Built With

Angular logo
Angular
awslogo
AWS
AWS Lambda Logo
AWS Lambda
cloudfront
Cloudfront
Docker logo
Docker
Jenkins logo
Jenkins
Mongo DB
Mongo DB
nodejslogo
Node.js

Key highlights

The time for financial analysis was reduced by 80%

Platforms simulated financial data for the features based on your goals set for the future period

Integrates financial data from Xero Platform

For Monte Carlo simulation, the platforms performs more than 50000 iterations under 2.5 seconds

FROM IDEA TO DIGITAL SOLUTION

The application aimed to engulf modeling, valuation and analyzing systems in an industry standard platform. This platform is for businesses that need to analyze the economic trends based on prior data and generates precise financial forecasts up to 18 months in advance. This makes us wonder on how a financial consulting firm can look like in the future and the potential that fintech has.

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In the first phase, we have developed an MVP to validate the main purpose of this application. The used core technologies facilitate the mathematical logical processes, we took advantage of a variety of auxiliary technologies in order to fully shape the app. Ideating, building, and testing were conducted over the course of 6 months. This time was spent with modeling with Linear Regressions, to expanding upon large classes of algorithms such as the Monte Carlo, Linear Regression, Holt-Winter, keeping a very fast process due to the big number of iterations, up to 50.000.

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FACING THE CHALLENGE

The most challenging step was to create a way to analyze large data sets in a time-efficient manner. Monte Carlo algorithms came in handy, as they can undertake extensive sets of data at a fast rate by making use of multiple iterations processes without losing accuracy. The Monte Carlo algorithms proved to be a much more intricate process to implement. Through a deeper understanding of the inner workings of these, we managed to surpass these challenges.

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The ease with which the user can approach and interact with this app was always one of our top priorities. A clustered interface can be a barrier for the user when engaging with the app. Faced with this challenge, we decided to strip the interface down to what is essential for the user.

As the app allows uploading reports, we had to implement restrictions regarding Microsoft Excel. Graphics are a result of multiple formulas, but for users, they have to be readable, legible, and instantaneous. These statistics are generated by the criteria that need to be met before uploading Excel files.

OUR RESPONSIBILITIES

Our team provided good communication, constant collaboration, and a problem-solving approach during the development process. We take pride in delivering an immersive experience for the user and adapting creatively to the challenges we face, always tailoring to the clients' needs.

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Summary

Solution

MVP, Data Analytics

Duration

6 months, 20 man-months.

Team

1 Project Manager, 2 developers, 1 DevOps

Engagement Model

Fixed Price