Credito helps cross-border institutions by sharing risk models, and working together to combat fraud

Credito is a decentralized credit intelligence network running on Ethereum and IPFS coupled with Smart Contracts and is an open network, anyone can mine the up to date data and potentially come up with revolutionary risk models. Credito will be a beneficiary of the network effect — each and every new transaction will add intelligence and value to the network.

The Shared Global Intelligence provided by Credito helps institutions across borders by sharing the risk models, and work together in fighting fraud.

You can start CREDITO by:

  1. Visit our site
  2. Go through the whitepaper
  3. Help us improve the whitepaper
  4. Get involved in our slack
  5. our telegram channel
  6. What is Credito Network?

Despite the efforts made by Financial Institutions, currently they are losing the battle against financial fraud. Credit card fraud continues to grow faster than credit card spending. Data breaches have resulted in more card details being compromised and the growth in online shopping has led to more opportunities for eCommerce fraud.

Credit Card Fraud

According to a 2016 report by Nilson, losses from credit card fraud amounted to $21.8 billion in 2015 That’s an increase of 162% from the 2010 figure which was $8 billion. The losses for 2016 are already estimated at over $24 billion, and these losses are expected to reach $31 billion by 2020.

The total value of credit and debit card transactions was $31 trillion in 2015. So, nearly 0.6 percent of the value of all transactions was lost to fraud. While the total value of credit card transactions is growing at close to 7 percent a year, credit card fraud is growing at over 16 percent every year.

According to the same report, gross fraud losses accounted for 6.9 cents per $100 spent. That was up from 5.7 cents per $100 in 2014. Credit card issuers bare 72% of these losses, while merchants and ATM operators share the other 28% of the losses from card fraud.

Data breaches are also growing at a rapid pace and compromising more cards every year. And, while eCommerce continues to take market share from in store purchases, the opportunities for fraud continue to grow.

Other Transaction Fraud

While credit card fraud accounts for the lion’s share of bank fraud, identity theft and eCommerce fraud are also on the rise.

Identity theft allows criminals to empty savings accounts and commit other forms of fraud. While merchants and card issuers usually bear the losses from credit card fraud, account holders often bear the losses incurred through identity fraud.

Experian reported that eCommerce fraud rose 33% in 2016. eCommerce fraud takes many forms, usually involving stolen credit card details or identity theft, while charge back schemes, or friendly fraud, are also on the rise.

Combating Fraud

To combat fraud at a global scale we need a decentralized system with high availability and providing live risk scores for transactions. Storing the anonymous transaction data securely on a decentralized data network and building a shared layer to access this network on a block chain will create an entirely new set of possibilities for AI capabilities and insights.

The benefits of decentralized/shared control, particularly as a foundation for AI results in more data, thus improved modelling capabilities and Qualitatively new data leading to entirely new models.

Such an open network will yield many interesting byproducts such as Credit scores providing financial inclusion for Credit invisiblesTransaction scoresto predict transaction fraud, Shared Global Intelligence which would make the risk models portable especially online transaction patterns and eventually becoming a playground for data scientists, which will encourage them to mine the up to date data and even come up with revolutionary risk models to safeguard the global community from fraud.

What does Credito provide?

Financial Inclusion to the “Credit Invisibles” by providing accurate and reliable credit scores.
A Global Credit Intelligence Network for the credit industry to prevent credit risk by identifying fraudulent transactions as they happen, allowing the industry to take well informed decisions.
A Decentralized collateralized lending marketplace enabling connections between lenders and borrowers located anywhere in the world removing physical constraints and reducing the traditional lending costs and management fees, thus creating a better credit marketplace than anything available today.
What does that mean?

In the near future, Banks and Lenders will need Credito to:

Get up to date and accurate credit scores.
Score the credit card and online transactions in real-time to prevent credit fraud.
Get detailed insights and patterns to detect transaction fraud.
Securely lend to the verified borrows, with the option of collateralized lending to significantly reduce risk.
And this is just for The beginning

The election contract has two main functions:
1. Response to individual credit account requests

2. Verify requests for third party transaction calculations. In addition, it also keeps track of loan balances and utilization rates

For certain analytic nodes, lease contracts control the following indicators:
1.Total number of assigned queries: number of last requests approved by node, completed and not executed.
2.Total number of completed queries: total number of past queries performed by node. This can be averaged based on the number of requests assigned to calculate the completion rate.
3.Average response time: punctuality of the knot response, which is an indicator of the effectiveness of the node. Average response time is calculated based on completed queries.
4.Site reputation: site reputation based on previous transactions. All nodes check and evaluate each point, if most nodes return the same value, the node becomes reliable. This reputation system helps identify and remove bad sites from the network.

Credit — Online Credit Proof

Loans are the ERC20 tokens that serve as currency, management mechanism and reward system at Credito. Credito will be able to set prices and receive payments for its services in the form of Loans.

Token Distribution

To continue development, Credito will conduct a one-time event to generate tokens (“TGE”) and sell sales credits, where 50% of tokens will be available for public sale. The TGE start date will be announced soon, and will allocate a total of $ 1 billion in loans. As follows:

  1. Employee distribution will have a 12 month transition period, 25% — every quarter, with 6 months old rock. The allocation will be proportionate to the ownership of each employee on the date of sale of the token.
  2. With the distribution of Dana Credito, the transition period will be 12 months.

Credito will expand in 6 stages, performing important milestones at every stage.

Stage1 Completed
Concepts and research.
Credito Registration.
White paper
The proof of the concept is a high-speed transaction system.
Launching a website.
Second stage registration, verification and partnership
CreDApp interface development
User registration
Automatic ID verification
Working closely with financial institutions
Phase 3 Infrastructure and Intelligence Development
Development of external APIs.
Infrastructure of analytical nodes.
Development of Credito Credit Development.
Creating a credit score.
Modeling of transaction estimation
Stage 4 Development and dissemination of intellectual contracts
Calculations and leases of intellectual contracts.
Smart audit audit.
Integrated smart contract with Credito Analytic Engine and nodal infrastructure.
Runs on the test network.
Try the trial version, give your partner a direct result.
Stage 5 Launch
The main network starts.
Decentralized intelligence controls are available for couples.
External analytic node The operator that connects the network.
Marketing and new partnerships.
The 6th stage protocol of end-to-end loans on major networks
Developing CreDApp and mobile apps
Development and audit of credit agreement Smart Credit
CreDApp brand with Credit Smart Credit credit integration
CreDApp in the test network and the transition to the main network

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