How New Technologies are Helping Banks Solve the Big Data Challenge
By Ryohei Fujimaki
Data science is a major area of investment for banks due to its proven impact on cybersecurity and fraud protection, risk mitigation, customer relationship management and more. When fully operationalized in production, data science enables banks to make data-driven decisions with unprecedented levels of speed, transparency and accountability, accelerating digital transformation initiatives and delivering better financial products and services that meet customers’ needs. Time-to-market to delivery data science impact is crucial to success, especially for traditional retail banks with physical branches and high overhead who must find innovative ways to compete with their online counterparts.
Financial institutions face many roadblocks, both external and internal, when it comes to automation adoption according to a recent Cognizant study. From security issues (91 percent of respondents identified this as a “high” or “medium” challenge) and development (91 percent), to servcie production line cooperation (84 percent) and ongoing maintenance (89 percent), it is no wonder that the study has found that 65 percent of automation efforts remain in the proof-of-concept stage.
Plano, Texas // www.m-files.com
Recently, Iceland-based bank Kvika selected M-Files, an intelligent information management solution, to help the firm effectively organize and manage documents in its branch offices, as well as its loan and pension savings departments. The solution gives the bank the ability to easily integrate with a custom-built customer relationships management system and accelerates loan processing between Kvika’s front office, loan department and back office.