An effective in-house E-Discovery function is essential in addressing the challenges faced by financial services organizations. Knowing which processes are supported better by internal resources and which should be outsourced is key to building a scalable and cost-efficient, end-to-end E-Discovery service. Many of the E-Discovery challenges faced by a financial organizations will be familiar to practitioners in most industries. We are faced with an environment where Electronically Stored Information (ESI) and big data continue to grow exponentially. Data sources are increasing in number and complexity and laws and regulations governing litigation and information governance evolve constantly. This results in higher eDiscovery costs as the volume of ESI to be collected and reviewed rises.

Within a financial organization the requirements to create and retain records are broad; retention periods are long and cover many types of ESI which need to be addressed by the organization. Additionally, eDiscovery professionals working in global organizations are only too aware of the sometimes competing requirements of discovery on the one hand and privacy and protection of data on the other. Financial institutions are faced with additional obligations arising from banking secrecy regulations. With the addition of blocking statutes in certain jurisdictions, the process of collecting and producing ESI, particularly in a cross-border context, becomes an increasingly complex task.

Thirdly, the IT landscape of a global financial organization contains thousands of custom-built applications, managing both structured and unstructured data and often with data retention policies applied automatically. Volumes of transactions are high with system knowledge residing with a limited number of specialists. Output formats can be non-standard, challenging even the most advanced E-Discovery platform to process, parse and render the data in a reviewable format. To speak of unstructured data, a typical preservation and collection project may involve data from more than 10 internal and external chat systems, with extracted files running from one single line of text to years of conversations in an ongoing chat room.