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As the global financial services sector opens to automation and AI, the possibilities to improve operations have blossomed. However, there lies another layer of operational issues for the business users when it comes to incorporating AI solutions and products into their ecosystems. Quite often, many of these AI solutions are either too narrowly focused, confining their use case to a small segment of possible workflows or the products are too technical for a typical business user to use, requiring an expert data scientist or machine-learning programmer to create a solution.
Bridging this operational gap in the financial services space, Coalesce brings its User-Defined Machine Learning (UDML) technology that allows business users to teach the AI software to automate specific use cases by filtering and analyzing data the way they do themselves. Greg Woolf, founder and CEO of Coalesce says, “The main idea behind Coalesce is that it’s not just a point solution that addresses a specific operational issue, instead it’s a generalized application that can be applied across the spectrum of financial services workflows.”
Born from a previous software company for investment managers, Coalesce initially addressed the domain of investment research. After witnessing a deluge of operational inefficiencies on the business side of the financial services space and a raging demand for a solution to ease their processes, the Coalesce team shifted their focus to streamline the workflow of financial services with the help of their AI expertise.
Coalesce is a generalized AI application that can automate a broad array of financial services workflows
Coalesce developed the UDML platform to understand five core content types that financial services users work with every day: companies, people, documents, communications, and transactions. Through a reinforcement learning algorithm, Coalesce’s UDML allows business users to impart their own domain-specific expertise and knowledge into the system. For instance, the platform is used by a global asset manager to identify potential risks in their investment portfolio by scanning through an ocean of external content associated with lawsuits, corruption and fraud in the minimal amount of time.
With UDML, Coalesce has also helped one of its banking customers who was burdened with 50,000 customer emails per month. The bank had a team of 300 customer service reps manually going through and replying to all those emails. “Coalesce learned to categorize the majority of the customer emails into a handful of common requests, reducing the volume of repetitive responses from the customer service reps and allowing them to focus on higher value inquiries,” explains Woolf.
Woolf also recalls a recent customer engagement for a large global financial services firm facing a challenge in processing tens of thousands of PDF documents it receives every month. “We stepped into the picture with our UDML technology which learned to save the documents in a repository, automatically extract key information and update the customer’s financial reporting system, saving them more than 75 percent of the effort compared to doing it manually,” adds Woolf.
Coalesce has established its stature as a prominent AI enabler for the financial services sector and leads a successful AI think tank comprised of some of the largest financial services organizations in Boston. These organizations come together regularly to discuss how AI can be used to streamline operations and reduce risk not just for individual firms, but for the entire industry as a whole through collaboration. “We are excited about the rising awareness of AI’s capabilities and what it can potentially accomplish for the financial services industry,” concludes Woolf.