USE CASES

Coalesce understands the five core content-types that financial services professionals work with every day: companies, people, documents, communications, and transactions.

Our user-defined machine learning (UDML) allows business users to teach the application to automate tasks using their own domain expertise and knowledge, thereby imparting their knowledge into the system.

Which workflow can Coalesce automate for your organization?

Companies

Faster identification of company risk

Documents

Cheaper, faster, and more accurate data entry

Emails

Faster response to customer emails

People

Identify your top prospects, automatically

Transactions

Better Identify Operational Risk

COMPANY USE-CASE

Result:

125x

Faster Identification of company risk

Customer: $75 Billion global asset manager

Problem: Looking to run a thorough risk analysis on a portfolio of 10,000 investments.

Solution: Coalesce learned from the customer’s analysts to screen 15,000 news articles per month for negative signals surrounding companies.

Benefit: Before, the customer manually screened less than 5,000 companies per year, but now with Coalesce they screen 10,000 companies per week.

Click below to see Coalesce discuss this use case at the Global Big Data Conference

DOCUMENTS USE-CASE

Result:

80%

Cost reduction on processing customer statements

Customer: $24 Billion institutional investment advisor

Problem: A team of 25 analysts manually extracting financial information from 6,000 alternative fund statements per month

Solution: Coalesce learned from the client’s analysts to identify relevant financial information from PDF statements and automatically export to the client’s reporting system.

Benefit: Improved speed and accuracy by automating the bulk of manual valuation updates.

Click below to see Coalesce discuss this use case at the Global Big Data Conference

EMAIL USE-CASE

Result:

200x

Faster response to customer emails

Customer: Top 20 Bank in the United States

Problem: Customer receives 40,000 emails per month which were addressed by 300 customer service representatives.

Solution: Coalesce learned to read emails on behalf of the customer service representatives and automate responses to the majority of common inquiries.

Benefit: Improved response time to time-sensitive inquiries from days to minutes.

Click below to see Coalesce discuss this use case at the Global Big Data Conference

TRANSACTIONS USE-CASE

Result:

95%

Better identify operational risk

Customer: $400 billion Global Asset Manager

Problem: Identify potential unreported trade errors in a total of 100,000 trades monthly.

Solution: Coalesce learned from customer’s compliance analysts to automatically find potential trade errors and their matching corrections.

Benefit: Coalesce was able to highlight the 5% of potentially erroneous transactions for the client’s compliance analysts to resolve.

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