Zoral Social Data Service
“There is much talk of using social and web based behavioral data... but which data is predictive? and of what? Zoral SDS knows.”
Zoral SDS comprises a series of crawlers that extract and store publicly available, social data from a wide range of sources. Zoral SDS computes predictive, social features using its extensive NLP, and Sentiment Analysis library.
Zoral SDS is,
- artificially intelligent,
- cloud based,
- highly scalable
- API based.
Zoral SDS crawls multiple social networks and can be driven using flexible input criteria such as...
- ◦ company legal name
- ◦ aliases
- ◦ address(es)
- ◦ location(s)
- ◦ billing and shipping addresses
- ◦ industry classification(s)
- ◦ DUNS number (or similar)
- ◦ email(s)
- ◦ contact phone(s)
- ◦ SME's phone(s)
- ◦ website(s)
- ◦ Facebook account(s)
- ◦ twitter account(s)
- ◦ company description
- ◦ competitor’s information
- ◦ and others
Social networks crawled include,
- Google places (part of Google+)
Zoral SDS uses Zoral ML, fuzzy matching algorithms. It crawls iteratively and concurrently using intelligent, dynamically generated search queries and fuzzy matching. In this way, it can zoom-in or converge on matched information across all social networks, eliminating non-matching social data.
Once extracted, social data is matched to the SME client information or input criteria. Metadata is added and the data is,
- aggregated and de-duplicated
- integrated to the SME's information and
- sent via output channel(s), along with the input criteria.
If a match is not found, or service time-out limit is reached, the Zoral SDS service returns the appropriate error or warning message(s).
Zoral ML Social Score
This is used to
- estimate the probability of default for SME’s at targeted marketing stage
- verify customers during KYC and customer onboarding
- boost the accuracy of default probability prediction for small/medium sized, companies at underwriting stage, in conjunction with other predictive data,
- verify and monitor ongoing SME customer performance throughout the customer and loan life-cycle
- estimate SME creditworthiness when applying for a loan renewal
- optimize retention marketing
periodically re-value the SME loan portfolio, and pro-actively manage
- pre-default or increased risk situations
- loan loss provisions.