Your people need information, not data. On average, they waste a day a week searching across silos, systems, and clouds for information. It’s pre-digital-age work. Learn how AI-Powered Search gives your employees the information and intelligence they need.
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The Top 5 Business Outcomes for Financial Institutions with AI-Powered Platforms
Cognitive search capabilities help financial institutions make the best use of their data, while creating insights that drive business opportunities.
Data Management Challenges
Top drivers of the data explosion in financial institutions:
Data regulations require financial institutions to make data more secure, accessible, and transparent.
Information-Driven Financial Institutions Connect and Contextualize Data Using AI-Powered Platforms
AI-powered search and analytic platforms give knowledge workers the ability to see data in context.
5 Business Outcomes for Financial Institutions Using an AI-Powered Platform
Reinforce protection of confidential documents and improve productivity at the same time using natural language processing and machine learning.
As assets shift out of active investments into passive investments, beat the market in investor care with service alpha.
Develop a complete view of the customer at every level of your bank, from the branch to the board.
See and connect patterns across many sources, including people, transactions, phone calls, email, and travel activity to find financial crime faster.
Minimize the risk of digital transformation and big data projects. Instead, understand data across legacy systems and silos. And turn unmanageable amounts of data into information that can be used to make valuable decisions.
Financial institutions can deliver personalized customer experiences, make quicker decisions, and adapt quicker to regulatory changes.
This article originally appeared in Bio-IT World
Content and data in the biopharmaceutical industry are complex and growing at an exponential rate. Terabytes from research and development, testing, lab reports, and patients reside in sources such as databases, emails, scientific publications, and medical records. Information that could be crucial to research can be found in emails, videos, recorded patient interviews, and social media.
Extracting usable information from what’s available represents a tremendous opportunity, but the sheer volume presents a challenge as well. Add to that challenge the size of biopharmaceutical companies, with tens of thousands of R&D experts often distributed around the world, and the plethora of regulations that the industry must adhere to—and it’s difficult to see how anyone could bring all of that content and data together to make sense of it.
Information instrumental to developing the next blockbuster drug might be hidden anywhere, buried in a multitude of silos throughout the organization.
Companies that leverage automation to sift through all their content and data, in all its complexity and volume, to find relevant information have an edge in researching and developing new drugs and conducting clinical trials.
This is simply not a task that can be tackled by humans alone—there is just too much to go through. And common keyword searches are not enough, as they won’t tell you that a paper is relevant if the search terms don’t appear in it, or if a video has the answer unless the keywords are in the metadata of the video.
Today, companies can get help from insight engines, which leverage a combination of sophisticated indexing, artificial intelligence, and natural language processing for linguistic and semantic analyses to identify what a text is about, look for synonyms and extract related concepts. Gartner notes that insight engines, “enable richer indexes, more complex queries, elaborated relevancy methods, and multiple touchpoints for the delivery of data (for machines) and information (for people).” A proper insight engine does this at speed, across languages, and in all kinds of media.
For biopharmaceuticals, this is particularly powerful, allowing them to correlate and share research in all forms over widely distributed research teams. Here are several ways biopharma companies can use insight engines to accelerate their research.
Find A Network Of Experts
Many companies struggle to create the best teams for new projects because expertise is hidden in large, geographically-distributed organizations with multiple divisions. A drug repositioning project might require a range of experts on related drugs, molecules, and their mechanisms of action, medical experts, geneticists, and biochemists. Identifying those experts within a vast organization can be challenging. But insight engines can analyze thousands of documents and other digital artifacts to see who has experience with relevant projects.
The technology can go further, identifying which experts’ work is connected. If they appear together in a document, interact within a forum, or even communicate significantly via email, an insight engine can see that connection and deduce that the work is related. Companies can then create an “expert graph” of people whose work intersects to build future teams.
This technique can extend beyond the borders of the company, helping to identify the most promising collaboration partners outside the company in a given field, based on publicly available data, such as trial reports, patent filings and reports from previous collaboration projects.
Generate R&D News Alerts
Biopharma companies can also use insight engines to watch for new developments in drug research and stay on top of the latest trends. These news alerts can go beyond typical media sources to include scientific publications, clinical trial reports, and patent filings.
This capability can be used on SharePoint, Documentum, or other sources within a large company to surface relevant information. An insight engine ensures the right information gets to the right people in the right context, and in a timely way.
Optimize Clinical Trials
Clinical trials that stretch over many years generate millions of datasets for every drug and study provide a treasure trove of data. Biostatisticians can ensure they get a comprehensive list of patients having certain diseases within trials on a drug, something nearly impossible with traditional methods.
They can also search and analyze across many drugs and studies, across content and data silos. Over time, this allows biopharmaceutical companies’ growing number of clinical trials to become a valuable asset that can be easily leveraged across a growing number of use cases.
All of these uses can lead to biopharma companies developing new drugs more quickly and getting them to market faster—necessary as these companies face tremendous pressure to innovate quickly and develop new promising drugs as patents for older drugs expire. With insight engines, they can make every part of the journey more efficient, from research, to clinical trials, to regulatory processes, presenting incredible opportunities for everyone in this field.
In addition to the awards Sinequa has collected this year – KMWorld Trend-Setting Products, Datanami Readers’ Choice Award, and Bio-IT 2018 Best in Show, just to name a few – we are excited to return from KMWorld / Enterprise Search & Discovery 2018 with yet another trophy.
On Wednesday, November 7th, at the KMWorld conference in Washington D.C., we participated in the Awards Ceremony for the finalists of the KM World Promise and the KM World Reality awards. The KM Promise Award is given to a company that implements and integrates knowledge management practices into business processes and works with clients to ensure they reach their goals. The award recipient provides innovative technology that breaks through the hype to help customers gain insights, collaborate and compete in a mobile and global business environment. The KM Reality Award recognizes an organization in which knowledge management is a positive reality, not just rhetoric. The award recipient has demonstrated leadership in the implementation of knowledge management practices and processes, realizing measurable business benefits.
We are very honored to have received the 2018 KM Promise Award. The other finalists in this category included ASG Technologies, BP Logix, DocStar, Nuxeo, Unifi Software and Workgrid Software. Laurent Fanichet, our VP of Marketing, accepted the award on behalf of Sinequa, followed by Jill Harris, Delta Airlines Sr. Communications Coordinator, who picked up the KM World Reality Award.
“2018 is a fantastic year for Sinequa. Leader for the third time in a row in the Gartner Magic Quadrant for Insight Engines, we are experiencing triple-digit growth as we continue to expand in North America with the opening of an office in San Francisco, among other major milestones. Winning the KM Promise Award is great validation of the value of our approach and the completeness of our solution. This reaffirms our commitment to offer our customers the most advanced Cognitive Search & Analytics platform to provide them with relevant and contextual insights to make better decisions, drive innovation and achieve greater operational efficiencies,“ said Fanichet.
In addition to winning the award, we had a very successful show at KMWorld! It was a pleasure to meet with our customers and partners at our brand new lit-up booth and see new faces at the very well-attended keynote presentation from Scott Parker, Sinequa Director of Product Marketing, titled “Becoming an Information-Driven Organization.”
We look forward to returning to DC next year and adding more trophies to our “honors” shelf in the New York office! In the meantime, we are rounding up 2018 with a few activities – a KMWorld-hosted roundtable webinar on Cognitive Search and Analytics in Action (November 27) and exhibiting sponsorships at the AI World Conference in Boston (December 3-5) and the Forrester Data Strategy & Insights Forum in Orlando (December 4-5).
We’re off to a busy September here at Sinequa! We’re excited and humbled to have received a few different awards for our Cognitive Search & Analytics Platform and company as a whole this month. Sinequa recognition has included the following awards from leading industry publications:
KMWorld Trend-Setting Products 2018
KMWorld’s 2018 list of Trend-Setting Products features not only emerging software directed toward human-like functionality but also more traditional offerings impressively refined. It encompasses AI, machine learning, cognitive computing and the Internet of Things, as well as enterprise content management, collaboration, text analytics, compliance and customer service. Read more.
DBTA’s Cool Companies in Cognitive Computing for 2018
DBTA and Big Data Quarterly presented the 2018 list of Cool Companies in Cognitive Computing to help increase understanding about the important area of information technology and how it is being leveraged in solutions and platforms to provide business advantages. Read more.
Datanami Readers’ Choice Award Winner
Sinequa won the Readers’ Choice – Best Big Data Product or Technology: Machine Learning category.
The Datanami Readers’ and Editors’ Choice Awards are determined through a nomination and voting process with input from the global big data community, as well as selections from the Datanami editors, to highlight key trends, shine a spotlight on technological breakthroughs and capture a critical cross-section of the state of the industry. Read more.
Looking forward to continuing the momentum for the rest of the year!
For more information on Sinequa’s cognitive search and analytics platform visit: https://www.sinequa.com/insight-platform-2/