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Kotak Mahindra uses DataFIX for identify Unique Customer Relationships and Households prior to forming Kotak Bank

  The Customer

Kotak Mahindra is one of India's leading financial institutions, offering diverse finance solutions, that encompass every sphere of life. From Corporate Finance, to Retail Finance to Investment Banking, to Mutual Fund, to Life Insurance, they meet the everyday financial needs of an individual as well as a corporate giant.

Kotak Mahindra has international partnerships with Goldman Sachs (one of the world's largest investment banks and brokerage firms), Ford Credit (one of the world's largest dedicated automobile financiers) and Old Mutual (a large insurance, banking and asset management conglomerate). The Group operates in over 50 cities in India and the USA, UK and UAE, employing over 1100 dedicated professionals and services a client base of over a half million customers

To offer prompt and efficient service to it's clients, the Group has been structured into three SBUs of Wealth Management, Knowledge Management and Asset Management. Through 8 companies created for the purpose of the above, Kotak Mahindra has operations in the areas of Retail Broking, Mutual Funds, Investment Banking , Debt Trading, Auto Finance, Corporate & Technology Finance and Consumer Finance to name a few.

Kotak Mahindra Finance Ltd. (KMFL) would be shortly converting itself into a Commercial Bank bringing all its operations under a single head. The new Bank is due to be launched by the last quarter of the current fiscal, and is expected to offer a wide range of services to retail and corporate customers across India.

As part of its IT strategy, one of Kotak Mahindra's early initiatives was to combine the various customer databases across the various companies into a single central repository containing unique individuals and other business and family relationships. The Data server was on an Oracle/Unix Platform. In order to gain an early advantage the Group needed to meet critical time-frames.

  The Challenge
  • To identify and extract relevant data from as many as 8 host systems
  • To be able to get from the IT managers in each of the 8 companies, the various non-address static information regarding the data.
  • To understand and solve the anomalies represented by this data in the short available time
  • To generate a single database consisting of cleansed, deduped and enriched data consisting of unique corporate and individual customers.
  • To map and combine entire data (address and non-address) across the various systems into a single system.
  The Solution

Kotak Mahindra used Spectrum Business Support Limited's expertise in understanding data-related issues, anomalies and exceptions in the data and resolving them. Spectrum Business Support Limited provided its considerable experience and knowledge of working with data related issues to identify problem sources and fixes.

Spectrum's DataFIX tools were used to cleanse, standardize and dedupe the data of over 1 million in a short span of 25 days, and to provide a unique base of Individuals and Households. The data covered more than 25 metros and mini-metros including some from rural India as well. Customised rules were generated and provided for the various types of data - depending on customer type (Corporate or Individual), customer location and customer address. Spectrum leveraged the full power of its automated routines, data-sensitised manpower, comprehensive master tables and experience in the financial domain to undertake this task as a time-critical mission.

In addition to a one-time legacy Deduplication this project involved Spectrum conducting an incremental deduplication (matching new records added in the interim while the cleansing process was going on, with the already matched data).

In addition to name and address information, Spectrum also cleansed a lot of non-address information like marital status, date of birth etc. Finally Spectrum undertook the task of integrating the data across the various source systems using mapping tables and a thorough understanding of the data elements and data ranges in each of the individual systems.

At the end of the day, Kotak Mahindra was a satisfied and happy customer having met its goal on time.

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