KiRTi: A Blockchain-based Credit Recommender System for Financial Institutions

KiRTi: A Blockchain-based Credit Recommender System for Financial Institutions

₹5,000.00
Product Code: Java - BlockChain
Availability: In Stock
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Product Description

Aim

        The main aim of this project to remove the third party agent between the perspective lenders and perspective borrowers.

Abstract

In this paper, we propose KiRTi, a deep-learning based credit-recommender scheme for public blockchain to facilitate smart lending operations between prospective borrowers (PB) and prospective lenders (PL) to eliminate the need of third party credit-rating agencies (CRAs) for credit-score (CS) generation. Thus loan grants to PB from PL is secured, authorized, and automated so as to expedite the disbursement process. KiRTi stores PB historical transactions, current assets, and liabilities as time-series sequenced data in a public blockchain. The sequenced data is fetched from blockchain by a long-short term memory (LSTM) model that generates CS for loan recommendations based on proposed lending algorithms for PB and PL. To ensure real-time updation of CS, edge-weights are updated based on boolean indicators from PB and PL, which indicates the successful repayments and loan-defaults. The process is iterated to improve the accuracy of edge-weights and generated CS to ensures the correct credibility of PB for future lending. Smart contracts (SC) are proposed for automatic setup of loan repayments between PB and PL. To model the LSTM recommender scheme, a German credit dataset from UCI repository is considered with 1000 credit-histories of PB, with 700 successful repayments and 300 defaults. KiRTi achieves an accuracy of 97.5% in comparison to conventional approaches with an Fmeasure of 0.98304. The security evaluation of KiRTi shows that it has computation cost of 20.96 ms and communication cost of 121 bytes compared to other state-of-the-art approaches.

 Proposed System

In proposed System, loan disbursement cycle is high. Perspective lenders and perspective borrowers have direct communication. So, that they can know their details clearly. In this approach we implement a sentiment analysis to read a borrowers reviews. For using sentiment analysis we can find out the total percentage of positive reviews negative reviews. Based on the reviews and positive negative reviews percentage PL will decide to lend the loan to that particular user or not. So that maximum users can get a loan without any difficulties. We will store the perspective lender lending details and perspective borrower’s payment history in block-chain.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.