Data mining case study in banking

As a result, to stay competitive in business entails the efficient use of modern tools to track past transaction records to analyze past business trend and future forecasts. Business Organizations faces different reactions and behavior from customers, which is partly due to insufficient information or the inability of a human analyst to understand the hidden pattern in business data. Customization of an investment portfolio for customers remain an enormous challenge to financial institutions even though there exist enough data in the financial market for analysis.

Data mining case study in banking

Number of unspent transaction outputs The bitcoin blockchain is a public ledger that records bitcoin transactions. A network of communicating nodes running bitcoin software maintains the blockchain.

Network nodes can validate transactions, add them to their copy of the ledger, and then broadcast these ledger additions to other nodes. To achieve independent verification of the chain of ownership each network node stores its own copy of the blockchain.

This allows bitcoin software to determine when a particular bitcoin was spent, which is needed to prevent double-spending. A conventional ledger records the transfers of actual bills or promissory notes that exist apart from it, but the blockchain is the only place that bitcoins can be said to exist in the form of unspent outputs of transactions.

Bitcoin network Number of bitcoin transactions per month logarithmic scale [67] Transactions are defined using a Forth -like scripting language. When a user sends bitcoins, the user designates each address and the amount of bitcoin being sent to that address in an output.

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To prevent double spending, each input must refer to a previous unspent output in the blockchain. Since transactions can have multiple outputs, users can send bitcoins to multiple recipients in one transaction. As in a cash transaction, the sum of inputs coins used to pay can exceed the intended sum of payments.

In such a case, an additional output is used, returning the change back to the payer. Though transaction fees are optional, miners can choose which transactions to process and prioritize those that pay higher fees.

The size of transactions is dependent on the number of inputs used to create the transaction, and the number of outputs.

In the blockchain, bitcoins are registered to bitcoin addresses. Creating a bitcoin address requires nothing more than picking a random valid private key and computing the corresponding bitcoin address.

This computation can be done in a split second. But the reverse, computing the private key of a given bitcoin address, is mathematically unfeasible. Users can tell others or make public a bitcoin address without compromising its corresponding private key.

Moreover, the number of valid private keys is so vast that it is extremely unlikely someone will compute a key-pair that is already in use and has funds. The vast number of valid private keys makes it unfeasible that brute force could be used to compromise a private key.

Data mining case study in banking

To be able to spend their bitcoins, the owner must know the corresponding private key and digitally sign the transaction. The network verifies the signature using the public key. This was when difficulty was much lower, and is no longer feasible.

Data mining case study in banking

Semi-log plot of relative mining difficulty [d] [67] Mining is a record-keeping service done through the use of computer processing power. Every 2, blocks approximately 14 days at roughly 10 min per blockthe difficulty target is adjusted based on the network's recent performance, with the aim of keeping the average time between new blocks at ten minutes.

In this way the system automatically adapts to the total amount of mining power on the network. Mining pool Computing power is often bundled together or "pooled" to reduce variance in miner income.

Individual mining rigs often have to wait for long periods to confirm a block of transactions and receive payment. In a pool, all participating miners get paid every time a participating server solves a block.

This payment depends on the amount of work an individual miner contributed to help find that block. To claim the reward, a special transaction called a coinbase is included with the processed payments.

The bitcoin protocol specifies that the reward for adding a block will be halved everyblocks approximately every four years. Eventually, the reward will decrease to zero, and the limit of 21 million bitcoins [f] will be reached c. Their numbers are being released roughly every ten minutes and the rate at which they are generated would drop by half every four years until all were in circulation.

Data mining in banking and finance: A case study of BICEC

While wallets are often described as a place to hold [88] or store bitcoins, [89] due to the nature of the system, bitcoins are inseparable from the blockchain transaction ledger.

A better way to describe a wallet is something that "stores the digital credentials for your bitcoin holdings" [89] and allows one to access and spend them. Bitcoin uses public-key cryptographyin which two cryptographic keys, one public and one private, are generated. There are several modes which wallets can operate in.

They have an inverse relationship with regards to trustlessness and computational requirements.

Full clients check the validity of mined blocks, preventing them from transacting on a chain that breaks or alters network rules. Lightweight clients consult full clients to send and receive transactions without requiring a local copy of the entire blockchain see simplified payment verification — SPV.Kitts, B.

(), The Making of a Large-Scale Ad Server, in Data Mining Case Studies Workshop and Practice Prize 5, Proceedings of the IEEE Thirteenth International Conference on Data Mining Workshops (ICDMW ), December, Dallas, TX, .

Churn problem has got great attention. A large number of industries were study user churn, especially based on the service industry, including the telecommunications [4, 5], banking [6], online gaming [7], P2P networks [8], and online social networks [9, 10].

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Lilian Sing’oei1 and Jiayang Wang2 1 School of Information Science and .

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