Financial services companies comprise a significant portion of the Attivio client base. In fact, 8 of the world's top 10 banks work with us to address a variety of opportunities in risk and compliance, customer support, and knowledge management. Two events held last week focused on the risk and compliance scenarios and how modern, machine-learning based search can help improve investigator productivity, decrease false positives, and protect the brand.
We used to think of knowledge workers as a few librarian-like employees responsible for managing all kinds of information. But information has become like currency: the more you have, the more you can do with it. And that means everyone has the potential to leverage information to perform their jobs better and increase the quality – and speed - of their decisions.
Financial services organizations know that failure to effectively monitor trade communications exposes them to a tremendous amount of risk. Whether the risk is driven by the dissemination of sensitive information, inappropriate employee behavior, or a violation of regulatory policies, it’s imperative that firms confidently mitigate these risks so they can protect brand value.This is the reality organizations face and why it’s so important to monitor communications proactively.
Remember the Panama Papers? Those were the 11.5 million leaked documents detailing attorney–client information for more than 214,000 offshore companies associated with Mossack Fonseca, a Panamanian law firm that specializes in setting up offshore shell companies. Many of these companies were set up to “hide” money so wealthy individuals could evade taxes. Others seemed part of money laundering schemes.
Customers often interact with brands across various media and channels. From the customer’s point of view, they’re interacting with a single brand, but inside the company, all that information is often scattered in different databases.
It’s hard to imagine a function that requires access to a broader and more diverse set of information than investment research. After all, the typical research analyst pours through an endless amount of data as they strive to produce timely, accurate, and relevant investment recommendations. Annual reports, company filings, security analytics, risk analytics, industry blogs, social media, and market news are just a few of the many data points leveraged as part of the research process.
An entire ecosystem of tools and data processing frameworks have grown up around Hadoop. Almost as soon as someone identifies a weakness or limitation—and there have been more than a few—someone else creates a fix. That's one of the reasons the Big Data ecosystem is so complex. And why many large companies hung back before jumping in. They wanted to see if any leaders would emerge from the chaos.