The last two years in retail banking have been turbulent times to say the least, particularly in the United States and Europe. Banks have been taken over by governments, government "rescue" loans or had to raise money from the markets to stay afloat. Some have even gone out of business. After enjoying unprecedented growth from 2001 to 2007, led by the booming mortgage market, growth in mortgage revenue came to an abrupt halt in 2008 as high-risk borrowers in the sub-prime market defaulted on their mortgages.

Banks need to get smarter, attract the right customers, implement customer level risk management, improve propensity to default predictions and implement risk adjusted customer relationship pricing. All of this is dependent on trusted data. Just imagine, then, the impact on their ability to achieve these things if the data flowing through their core processes is unreliable.

This paper examines the impact of unreliable data on retail banks. It then defines the requirements needed to guarantee data reliability in retail banking and offers a practical approach to creating and governing that data. It then shows how you can get started in making trusted data available in to help improve marketing, customer service, risk management, compliance and profit ability.