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Okapi's Real-Time Risk Intelligence Enhancement with AYLIEN News API
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Education
- Equipment & Machinery
Use Cases
- Real-Time Location System (RTLS)
- Track & Trace of Assets
Services
- Data Science Services
- System Integration
The Challenge
Okapi, a leader in innovative risk assessment for the commercial real estate (CRE) industry, faced a challenge in accessing real-time, relevant news content from a multitude of diverse data sources. These sources, which included HR platforms, labor statistics, location-based data, market-specific data, and financial reporting information, were crucial to Okapi's service but were often difficult to access and irregularly updated. Okapi's machine learning engine relied on this data to create accurate risk analysis reports for their CRE clients, providing insights for portfolio management, tenant risk, and asset acquisition. To enhance the effectiveness of their data insight tools, Okapi sought to incorporate real-time news data into their risk-prediction algorithm, which they believed would provide up-to-date data and a 'peek into the future'.
About The Customer
Okapi is a leading company in innovative risk assessment for the commercial real estate (CRE) industry. They work with some of the world's largest landlords, providing comprehensive, timely, and accurate risk assessment reports for asset acquisition risk, new tenant risk, and existing portfolio risk. Okapi aggregates data from hundreds of diverse data sources, which is then processed through their machine learning engine to create highly accurate risk analysis reports. Their goal is to provide substantive insights for their customers in relation to portfolio management, tenant risk, and asset acquisition.
The Solution
Okapi found their solution in AYLIEN News API, a leading data as a service solution for news. AYLIEN News API provides access to over 80,000 high-quality sources, enriching every news article with 26 data points in real time through a proprietary natural language processing (NLP) engine. This engine adds structure to unstructured news, making it easy for customers to pinpoint relevant news. Okapi used AYLIEN News API to aggregate relevant news and applied their own layer of risk-focused machine learning to further tag and categorize news data based on a custom domain-specific taxonomy. This ensured that the highest impact insights were included in risk assessment reports for their CRE clients. Okapi chose AYLIEN News API for its easy access to news content, powerful search functionality, accurate categorization, and simple integration.
Operational Impact
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