Indian Banking Ecosystem

Topics: Data management, Bank, Cheque Pages: 6 (1351 words) Published: May 15, 2013
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Indian banking ecosystem
Automating data flow as a strategic initiative

We put the banking into business intelligence

indian banking ecosystem

indian banking ecosystem

Automating data flow as a strategic initiative
Frauds in the banking sector in india
the public sector banks, with their massive presence across the country, reported an annual average of more than 3,000 cases of frauds and cheating during the past four years. their better equipped counterparts in the private sector reported almost five times the number of cases. icici bank alone accounted for almost half of the total scams reported to the Rbi. of the total 21,244 cases reported in 2007-08, a whopping 10,976 were from icici. similarly, in 2008-09, icici reported 13,221 of the total 23,579 cases. the bank reported 15,074 of the total 24,788 fraud cases in 2009-10. the second highest number of cases were reported by hsbc (3,770, 3,481, 2,741, 2028); followed by citi bank (1,647, 1,182, 1,277, 666); american express banking (499, 703, 817, 637) and the distant fourth was state bank of india (561, 745, 545, 615) during the past four financial years 2007-08, 2008-09, 2009-10, 2010-11 respectively. the figures for the current fiscal are till December, 2010. Users

Application Server Report Server Cubes/Analytics Server
1. CBS 2. Treasury & Investment 3. Other IT Solutions 4. Text & Excel Files 5. RBI Docs Transaction Data / Snap Shot Data Data is moved into Staging Server on “As is where is basis” with a temporal cut off Historiacal Data Master Data New Accounts Data is moved into Temp DB validated on mapping of Source Masters with CRisMac Masters

The increasing complexity in the banking industry has made monitoring of transactions and operations a herculean task. This is especially in light of the rising cases of frauds that have tarnished the image of the sector as the ancillary to the economy’s growth. As per some estimates, the frauds in Indian banking sector had hit a record high of Rs 20 billion in 2009-10 and the figure was estimated to go much higher in 2010-11, given the trend seen so far. Amidst this, the banking regulator RBI’s role has become vital, not just in bringing the perpetrators of banking frauds to law, but also to see that banking frauds do not occur in the future. This is precisely the reason the RBI recently came out with an approach paper on what it calls the ‘automated data flow’ or ADF. In simple terms, the ADF will ensure a seamless flow of data from banks to the RBI without any manual intervention. Currently, banks receive information from their various branches, then integrate the data and store it, followed by data conversion and then data submission to the RBI.

Dataflow from banks to Rbi

Source Databases

ETL Tool

Staging DB

Temp DB

Data Acquisition

Data is moved into main server after checking for credentials & duplications

Data Integration, Storage (Production Server)

Central Data Repository

Data Cleansing Functionality

Data Conversion & Data Submission

As per the proposed move i.e., ADF, the entire data flow would be completely automated and would help the banks in terms of enhanced data quality, timeliness, and reduced costs, besides a direct oversight by RBI for any possible frauds.

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indian banking ecosystem

The key idea behind ADF will be to significantly enhance the quality and timeliness of data, which is critical to avoid frauds and remove data asymmetry from the banking system. The ADF will also help the Indian banking sector by enabling more informed policy decisions and better regulation. Apart from this, the ADF will also help the RBI create a centralized data repository, which it can easily leverage for various purposes. Such a repository would also cut down on the time for investigations and other oversight operations. All this would be possible because the ADF will...
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