AI-Powered Cash Flow Forecasting System

₹75000-150000 INR

Closed

Posted about 1 month ago

₹75000-150000 INR

Paid on delivery

Cash Flow Forecasting Model — Summary 1. Overall Objective The system predicts future cash inflows and outflows and produces a daily/weekly/monthly cash forecast, supported by a recommendation engine that suggests actions to improve liquidity. The model integrates multiple financial signals such as: Accounts receivable collections Vendor payments Project milestone billing Sales pipeline deals Non-sales inflows Operational expenses All signals are normalized into a single cash forecast which treasury can use for decision making. 2. End-to-End Architecture The system is structured around a Central Financial Intelligence Layer that stores behavioural features and model outputs. Data Flow Raw financial data Feature store (behavioural signals) ML models Cash flow modules Cash event normalization Recommendation engine Treasury decision interface All modules read from shared features rather than computing their own signals. 3. Central Financial Intelligence Layer This is the core backbone of the system. It stores reusable behavioural intelligence about: customers vendors transactions Key design principles Single source of behavioural truth Customer payment behaviour computed once Used across all models Decoupling Models read features instead of raw ERP data Versioning Every feature row has a version and timestamp Incremental updates Nightly batch updates Event-driven updates for lifecycle changes 4. Core Data Model The system relies on a small set of core tables. Base financial tables Examples: customers vendors invoices bills payments collections_events purchase_orders non_invoice_payments These capture all financial activity including commitments and direct cash transfers. Feature store tables Derived behavioural signals such as: Customer features: payment delay late payment ratio volatility dispute ratio payment trend Vendor features: average payment cycle discount capture behaviour chase frequency Transaction features: invoice age overdue days invoice amount bucket 5. Forecasting Modules The system forecasts cash through six specialised modules. S1 — AR Collections Prediction Goal Predict when each customer invoice will be paid. Approach Machine learning model trained on: invoice attributes customer behaviour collections activity credit risk temporal signals Model Primary: Gradient boosted trees (LightGBM / XGBoost) Baseline: Random Forest for validation and thin-data cases. Key capability Predictions are event-driven, meaning they update when: invoice viewed reminder sent dispute raised promise-to-pay received partial payment made This keeps the forecast dynamically updated. S2 — Vendor Payment Prediction Goal Predict when vendor payments will actually occur. Multi-layer decision pipeline Earliest payable date Payment run alignment Vendor priority policy ML behavioural adjustment Liquidity gate ML role Predicts adjustment to rule-based payment date based on behaviour such as: historical payment cycle vendor chase frequency discount capture behaviour invoice size payment run timing Liquidity gate If forecast cash is insufficient: lower priority vendors are deferred Tier-1 vendors escalate for manual decision. S3 — WIP / Project Billing Forecast Goal Forecast cash from milestone-based projects. Method Rule-based deterministic model. Steps: Identify billable milestones Detect near-complete milestones Estimate invoice issuance date Apply customer payment delay Produce forecast cash date Phase 1 uses static averages; Phase 2 introduces probabilistic modelling. S4 — Sales Pipeline Forecast Forecasts future cash from open sales deals. Key elements: deal stage probability deal value historical billing patterns customer payment delay Pipeline forecasts are suppressed once deals convert into real invoices. S5 — Other Inflows Handles non-sales inflows such as: loan drawdowns grants tax refunds insurance settlements. S6 — Operational Outflows Forecasts operational payments including: salaries taxes software renewals marketing campaigns approved expenses Each expense type has its own recurrence logic. 6. S7 — Cash Event Normalisation This is where all upstream predictions converge. Functions: merge all inflow and outflow forecasts remove duplicate events reconcile pipeline → invoice transitions convert currencies assign confidence levels Output: Single unified cash forecast table. 7. Recommendation Engine Uses the forecast to generate actions that improve liquidity. Inputs predicted invoice payments customer payment scores collections signals vendor behaviour cash position Simulated actions Examples: accelerate collections defer vendor payments adjust budgets change financing timing Each recommendation is scored by cash impact and feasibility. 8. Treasury Decision Layer Treasury receives: forecasted cash position ranked recommendations They can: accept reject escalate Actual results are tracked to improve recommendation models over time. 9. Design Philosophy The system follows several guiding principles. Shared intelligence One behavioural model for all modules. Event-driven forecasting Predictions update immediately on financial events. Modular architecture Each forecast type runs independently but feeds a unified cash engine. Traceability Every prediction has: model version trigger event timestamp. 10. Future Capabilities Planned enhancements include: probability curves for payment timing customer-specific invoice lag modelling credit risk scoring variance analysis (forecast vs actual) advanced recommendation optimization. In essence The system is a machine-learning driven cash forecasting platform built around a shared financial feature store, multiple specialized forecasting modules, and a recommendation engine that actively improves treasury liquidity decisions.

Machine Learning (ML)

Data Science

Project ID: 40360864

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25 freelancers are bidding on average ₹111,218 INR for this job

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

₹152,500 INR in 7 days

4.9

(53 reviews)

7.1

@nrajuu07

As a specialist in machine learning with a strong background in deep learning and time series forecasting, I am confident that I am the most qualified individual for your AI-Powered Cash Flow Forecasting System project. Having developed models for complex data, including medical imaging, sensor signals, and time series for several domains, I have a deep understanding of the intricacies involved in identifying patterns and making reliable predictions — a key requirement for this project. My expertise with Gradient Boosted Trees (LightGBM / XGBoost), which serves as the primary model for your AR Collections Prediction module, is particularly relevant. Additionally, my experiences creating multi-layer decision pipelines like the one you require for Vendor Payment Prediction make me an ideal fit for this project as it adds efficiency and precision to forecast cash projections.

₹75,000 INR in 7 days

4.8

(95 reviews)

6.1

@avinashdubeyg209

Noticed your requirement for normalizing various financial signals into a unified cash forecast. Recently built a similar system for a retail client, integrating sales pipelines and operational expenses to enhance liquidity recommendations. Curious about the particular data sources you'll be connecting—are they standardized APIs or custom integrations? Understanding this will help tailor the model for accuracy and efficiency. Let me know if you're available to discuss further. Can start today and outline a strategy for the workflow.

₹75,000 INR in 7 days

5.0

(34 reviews)

5.1

@GameOfWords

As a developer, AI specialist, and an expert in WordPress, I'm confident that my skills are precisely what your project needs. My deep understanding of ML combined with my technical proficiency across WordPress, Python, Node.js, React Native, Flutter and other modern APIs has allowed me to design scalable systems that deliver real value. I am more than capable of building an AI-powered Cash Flow Forecasting System that fulfills the precise needs outlined in your project description. Moreover, my experiences crafting websites optimized for search engines and conversions will be a major asset when it comes to creating the Central Financial Intelligence Layer and the core data model that forms the backbone of your system. I understand the importance of a well-structured data architecture and versioning which will be crucial in ensuring accurate and consistent forecasting outputs. Thanks for considering my offer. I look forward to discussing how our collaboration will revolutionize your business's cash flow forecastinging process.

₹112,500 INR in 7 days

4.9

(6 reviews)

3.8

@pebambang5

Hello, I have read the outline of your project, and I’m sure can solve the task, provide correct result, free revision guarantee. My background is in statistics and applied mathematics using Python/R/JS programming for model statistics, predictive analytics, machine learning and artificial intelligence. I’m an expert in various model regression, hypothesis analysis, Ecommerce/trading/crypto analysis, NLP/Fraud/Anomaly/Fake detection, provide in Python notebook/Flask/Django, Rmarkdown file html/pdf/word, complete with the charts. Please share your data, I'm available, discuss detailed requirements, budget/time negotiable. Thank you. Best rgds, Bambangpe

₹75,000 INR in 5 days

4.8

(15 reviews)

4.1

@chiragardeshna

Hi there, Strong alignment with this project comes from experience delivering AI-driven financial systems where forecasting accuracy, modular architecture, and real-time decision support were essential. Clear understanding of your requirement to build a cash flow forecasting platform with feature store, multi-module predictions, event-driven updates, and a recommendation engine for liquidity optimization . Hands-on expertise with Python, ML models (XGBoost/LightGBM), data pipelines, and scalable backend systems ensures accurate predictions and clean integration across modules. Risk stays controlled through modular design, versioned features, and maintaining traceability across all forecasting outputs and decisions. Available to start immediately happy to discuss architecture or next steps. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

₹75,000 INR in 7 days

5.0

(1 review)

2.7

@dushyant317

Design and develop a machine-learning driven cash flow forecasting platform with a centralized feature store, modular prediction engines, and unified cash event normalization. Deliver a scalable system with real-time forecasting, intelligent recommendations, and a treasury dashboard to optimize liquidity decisions and financial planning.

₹152,500 INR in 45 days

5.0

(1 review)

0.4

@abdf2010

Hi there, I've taken a close look at your project for a cash flow forecasting system, and I'm impressed by the complexity of the model you're aiming to build. It's clear that you need a system that can accurately predict future cash inflows and outflows, and provide actionable recommendations to improve liquidity. With my background in machine learning and data science, I've worked on similar projects that involved integrating multiple financial signals to produce a unified forecast. My experience has taught me that normalizing diverse data sources, such as accounts receivable collections and operational expenses, is crucial for a reliable cash forecast. I'd like to start by discussing how to prioritize and weight these different signals to ensure the model is tailored to your specific needs. Let's chat about how I can help you bring this project to life - I'd be happy to walk you through my approach and answer any questions you may have.

₹75,000 INR in 7 days

0.0

(0 reviews)

0.0

@kamran2012

This looks like a great fit, I will build the full forecasting platform — shared feature store, the six specialized modules (AR collections, vendor payments, WIP billing, pipeline, other inflows, operational outflows), cash event normalization, and the recommendation engine feeding your treasury dashboard. For the Central Financial Intelligence Layer, I will design the feature store with versioned, incremental updates so LightGBM and XGBoost models consume pre-computed behavioural signals rather than querying raw ERP data at inference time. This keeps event-driven re-forecasting fast — under seconds when a payment or dispute triggers an update. Questions: 1) What ERP or accounting system holds the base financial tables today? Send me a message and we can go over the details. Best regards, Kamran

₹146,956 INR in 25 days

0.0

(0 reviews)

0.0

@dan867

I can build a cash flow forecasting model using AI. I'll create a system that predicts future cash inflows based on historical data and other factors. I'll provide a clear summary of the model and its predictions. My bid for this project is 120000 INR. Dan

₹105,000 INR in 7 days

0.0

(0 reviews)

0.0

@AsifTech21

Turn your cash flow from a lagging report into a real-time decision engine. I genuinely appreciate the sophistication of your architecture—it’s already thinking like a next-gen financial intelligence system, not just a forecast model. I can help bring this to life by operationalizing your central feature store, implementing event-driven ML pipelines across AR, AP, WIP, pipeline, and expenses, and deploying robust models (LightGBM/XGBoost with fallback baselines) that continuously adapt to live financial signals. My methodology emphasizes reusable behavioural features, clean data contracts, and modular forecasting components that feed a unified normalization layer, powering an explainable, impact-driven recommendation engine. The result will be a scalable, traceable system that gives treasury not just accurate forecasts, but confident, actionable decisions—with a strong foundation for future enhancements like probabilistic timing and variance intelligence.

₹112,500 INR in 7 days

0.0

(0 reviews)

0.0

@kaustubhbawa123

Hi, I am an IIT Grad, certified in Machine Learning and AWS Data Analytics, ex-BFSI and worked at Fortune 500 companies. I will make it a reality for you. As a Senior ML Engineer & Data Scientist specialising in financial forecasting systems, I will architect and deliver your full 7-module cash flow platform — from the Central Financial Intelligence Layer and feature store design right through to the LightGBM/XGBoost AR collections model, vendor payment pipeline, and the recommendation engine — all tied into a unified cash event normalisation layer (S7). One quick question: Is the source ERP data coming from a system like SAP, Oracle, or Tally , and do you already have historical invoice + payment data available for model training, or will we need to synthesise seed data for the initial ML models? Kindly click on the chat button so we can discuss and get started. Will share you my prior projects done and my resume too. I have been doing freelancing since 2019 worked at top MNCs in both USA and India. Lets connect

₹75,000 INR in 7 days

0.0

(0 reviews)

0.0

@Mikun007

Proposal: AI-Powered Cash Flow Forecasting System (MVP Development) Hello, I carefully reviewed your project description, and I must say this is a well-structured and ambitious financial intelligence system. I’d like to propose developing a Phase 1 MVP that focuses on building a scalable foundation along with core forecasting capabilities. ? My Approach I will design a modular and extensible system aligned with your architecture, ensuring future modules (vendor payments, pipeline forecasting, recommendation engine) can be easily integrated. ? Scope of Delivery (Phase 1 MVP) Central Financial Data Layer Design core financial tables (customers, invoices, payments, vendors) Build a structured feature store with key behavioural signals AR Collections Forecasting (Core ML Module) * Develop a machine learning model using XGBoost / LightGBM * Predict expected payment dates for invoices * Incorporate features like payment delays, invoice age, and customer behaviour Basic Cash Flow Aggregation** * Combine predicted inflows with simple outflow logic * Generate daily/weekly cash forecast output Backend API * Build REST APIs using Flask for model interaction and data access Dashboard (Optional / Basic) * Simple interface to visualize forecasted cash flow ? Technical Stack * Python (Flask / FastAPI) * Machine Learning (XGBoost, Scikit-learn) * Database (PostgreSQL / MongoDB) * Pandas, NumPy for data processing

₹90,000 INR in 35 days

0.0

(0 reviews)

0.0

@KarthikTechCon

**Hello,** I’m **Karthik**, Full Stack Architect with 15+ yrs experience in AI/ML, fintech systems, and data-driven forecasting platforms. I reviewed your architecture and it aligns well with enterprise-grade financial intelligence systems. **Approach:** • Build **Central Financial Intelligence Layer** (feature store + versioning) • Implement ML modules: AR collections, vendor payments, pipeline, expenses • Use **LightGBM/XGBoost** for event-driven predictions • Design **cash event normalization engine** for unified forecast • Develop **recommendation engine** (liquidity optimization scenarios) • Create dashboard for treasury decisions (forecast + actions) **Tech Stack:** Python (FastAPI), ML (LightGBM/XGBoost), PostgreSQL, Airflow, React dashboard, AWS/Azure **Deliverables:** • End-to-end AI cash flow forecasting system • Scalable feature store + ML pipelines • Unified forecast engine + recommendations • Admin dashboard + documentation **Why Me:** • Strong in fintech + ML systems + data engineering • Experience with event-driven architectures & forecasting models • Focus on accuracy, scalability & traceability **Timeline:** 6–8 weeks (MVP) Happy to collaborate long-term and evolve this into a production-grade treasury platform. **Warm Regards,** Karthik B Resonite Technologies

₹152,500 INR in 7 days

0.0

(0 reviews)

0.0

@ReddymasuTeja

I can design and implement a scalable cash flow forecasting system using machine learning and a modular architecture as described in your requirements. My approach will focus on building a clean and extensible pipeline that includes: * Data preprocessing and integration of financial signals (AR, AP, expenses, pipeline) * Feature engineering for behavioural patterns (payment delays, trends, cycles) * Forecasting models using XGBoost/LightGBM and time-series techniques * Modular forecasting components for collections, vendor payments, and cash flows * Unified cash event normalization layer for final forecast generation * Basic recommendation logic to suggest liquidity improvements * Reproducible pipeline with clear structure, logging, and documentation I will ensure the system is easy to extend, with reusable feature layers and well-structured code. The solution will include a working prototype covering key modules and a clear roadmap for scaling into a full production system. I have experience building end-to-end machine learning pipelines using Python, Pandas, and Scikit-learn, including forecasting and automation projects. I am highly interested in this long-term and impactful system and can start immediately. Looking forward to discussing the dataset and refining the approach.

₹112,500 INR in 7 days

0.0

(0 reviews)

0.0

@indreshpnk

Hello, I understand you need an AI-Powered Cash Flow Forecasting System with ML-driven predictions for inflows, outflows, and a recommendation engine for liquidity optimization. The goal is to deliver a robust, data-driven treasury solution with accurate forecasting and actionable financial insights. Here’s what I can provide: End-to-end ML pipeline covering AR/AP, sales pipeline, WIP, and expense forecasting modules Central financial feature store for unified behavioural intelligence and consistent predictions Recommendation engine for liquidity optimization with actionable treasury decision support I bring over 4+ years of experience in Data Science and Machine Learning, specializing in predictive modeling, time-series forecasting, and building scalable financial intelligence systems. Just to clarify a few things: Do you already have structured historical ERP/financial data available for training? Should this system be built as a standalone platform or integrated with your existing ERP stack? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

₹112,500 INR in 7 days

0.0

(0 reviews)

0.0

@ashiqiitkgp

Hi there, I have thoroughly reviewed the v1.0 Solution Design Document for your Cash Flow Forecasting Model. The architecture is exceptionally well-structured, and I completely understand the Phase 1 implementation requirements. My approach aligns exactly with your SDD: Central Financial Intelligence Layer: I will build the 12 core tables (Base Financial Data, Feature Store, Model Outputs) to seamlessly decouple raw ERP data from the ML models. ML Core (S1 & S2): I will implement the event-driven LightGBM/XGBoost models for AR days-to-pay and vendor adjustment deltas, including the parallel Random Forest baselines for thin-data fallback (<10 invoices). Deterministic Modules (S3-S6): I will code the strict rule-based logic for WIP milestone billing, CRM pipeline cohort extrapolation, and recurring expense scheduling. S7 & Recommendation Engine: I will construct the aggregation engine enforcing your exact source trust hierarchy, and build the scenario generator to score treasury actions (e.g., collections acceleration) using your weighted function. I am ready to translate this mature design into a robust, production-ready ML backend. Let's discuss the next steps!

₹115,000 INR in 36 days

0.0

(0 reviews)

0.0

@SKREHAN91

Hello, Your feature store + event-driven cash forecasting architecture aligns well with my experience in data modeling, MIS systems, and predictive analytics (6+ years). I can help with: Feature store (customer/vendor behavioral signals, versioning) ML forecasting (AR collections, vendor payments – XGBoost/LightGBM) Cash event normalization (merge, dedupe, confidence scoring) Dashboard layer for treasury decisions (Power BI style) I focus on accurate, traceable, decision-ready systems, not just models. Ready to start immediately.

₹95,000 INR in 30 days

0.0

(0 reviews)

0.0

@Khuship301

I can design and deliver a robust, AI-driven ERP and financial intelligence platform tailored to your needs, leveraging my 14+ years of experience in Odoo and enterprise system architecture. Building on a centralized data model and feature-driven architecture as outlined in your requirements , I will implement seamless data flow from core ERP modules (finance, inventory, operations) into a scalable ML layer that powers predictive forecasting, behavioral analytics, and intelligent recommendations. Using Odoo as the operational backbone combined with modern ML frameworks (e.g., LightGBM/XGBoost), we can create a unified system where real-time events continuously update forecasts, improve accuracy, and provide actionable insights through intuitive dashboards for treasury and management teams. The solution will be modular, traceable, and production-ready, with full documentation and deployment support, ensuring your team can maintain and extend it efficiently while driving measurable business impact.

₹150,000 INR in 7 days