Chennai, April 19 (IANS) Business analytics and technology services company Dun & Bradstreet Technology and Data Services is focusing on African, Middle East and South Asian markets for its banking analytical solutions, said a top company official.
"In Africa we will start first in Nigeria and then Ghana, Tanzania and others. We are in advanced talks with two banks in Nigeria," S.Ganesh, CEO at Dun & Bradstreet told IANS.
The city-based company provides analytical models and information technology (IT) services converting raw data into valuable insight information for banks, credit bureau's rating agencies and others.
Ganesh said the Middle East market size for analytical solutions for the banking sector is around $500 million and Dun & Bradstreet is looking at around $5-10 million in the two years time frame.
"It is more of a market building exercise for us," he said.
Speaking about the analytical tools for the domestic banking sector, Ganesh said the banks have such tools but they are not used in a systematic way.
"Every 12 months the banks have to relook their analytical model and make alterations if need. But it is not done," he remarked.
According to Ganesh, businesses are showing lot more interest in analytics in the past one-and-half years as the data can be structured in the required manner.
"In the earlier days, CEOs believed in their instinct/gut feeling while taking business decisions as there was not much of a data. What ever was there it was not stored in a structured manner," he said.
Queried about mining data from the social media and using the same for decisions like lending, Ganesh said reliability of the available data is one major issue.
He said business decisions on data from social media are 5-7 years away.
"But a bank can get additional information on existing clients which may serve as positive/warning signals for banks and others. Banks may decide their pricing strategy for a client based on that information," he said.
He said data from the social media will give a fair idea about the catchment market.
According to him, a well known company will have a negative bias on the internet. The negativity can be factored in the analytics.