Irfan Khan believes more data will help banks avoid a similar crisis in future.
Big data could have saved us from the credit crunch, according to one SAP executive.
Irfan Khan, senior VP for database and technology, said a wider pool of data could have helped banks better test subprime mortgages, largely blamed for triggering the global financial downturn that started in 2008.
Speaking to CBR yesterday, he claimed: "There was a lack of insight around the customer - if you have little or no credit history and you want to take out a 20-year mortgage you're going to be underwater from day one."
It was this lack of data that led to banks lending to people unable to pay back such large sums of money, he added, with banks relying on small windows of data.
"You're only looking at data in a very prosperous period leading up to 2008, when the banking industry was in boom," Khan added.
"There was a necessity to be able to have a larger data sample to be able to do back testing [of mortgages] against.
"Big data plays a significant role in back testing and I believe in future banking generations to come ... we should be able to avert such calamities as took place in 2008."
He was speaking after a roundtable in which he and other executives discussed the ways financial institutions could use big data to improve their businesses.
An SAP-commissioned study of 1,500 financial experts found 77% believed technology would help them comply with regulators faster, but they are struggling to implement better IT infrastructure.
While 61% of respondents said their banks plan to increase IT budgets by at least 25% over the next three years, they appear to prioritise mobile banking over cloud and in-memory databases, with six in 10 saying mobile is the future for banking, with in-memory following it with 48% and cloud with 47%.
However, Henry Cook, principal consultant for SAP HANA, the firm's in-memory database technology, said: "Banks care about customer insight, they're very much concerned with the regulatory environment and also about cost. We're using big data to give banks the ability to assess trading risks within the day, even second by second."