Default Prediction Analytics
Predicting default propensity on loan portfolio through advanced analytics
Operation scale of 6 million records and 6 million upserts per month as well as external data
ViewMortgage Analytics
Mortgage data is complex to handle due to its volume and stored inconsistently at varying time intervals. Data maintenance will be tedious for the organization, and it also subjects in deviation of tracking foreclose, forebear and buy/sell portfolio. A large mortgage servicer in North America enabled portfolio & mortgage analytics to build large voluminous data repository based on specific constraints.
Maveric’s datatech team worked with the organization to analyze its unstructured data, and developed analytics workflows to extract meaningful data with the help of data stores which were powered by Oracle and Mongo.
Explore how we took this challenge and provided feasible solution with our proactive mortgage predictive model to ease the decision-making process developed within stringent SLA’s.
ViewOpen API Case study
Awaiting content
ViewPatent Analysis
Data-driven approaches has become an industry standard. Furthermore, the power of analytics empowers decision-making capabilities. A valley funded patent technology firm enabled advanced analytics to build large voluminous data repository from the patents across US & EU.
Maveric’s datatech team worked with the firm to develop a data cleansing framework, which could assist them to drawing valuable insights from unstructured data sources. The data stores were powered by Mongo & MySQL on the cloud platform using AWS and Azure.
Learn how Maveric’s data solution team explored the scenario with our patent analytics solution to support the decision-making process. Also, the model was replicated and is currently being used by 2 of the fortune 50 customers.
ViewFunctional And Performance API Testing
Customer experience has become the central point for any digital transformation journey. A leading retail and business bank in UAE wasn’t happy with the performance and quality of their customer facing application, which was integrated with many surround systems. On top of it, their environment was surrounded with extremely high volumes of complex interfaces. Maveric’s digital quality engineering (QE) team was put to action for conducting comprehensive API testing for client’s middle-ware upgrade. An initial assessment workshop was conducted by Maveric’s specialists to give a comprehensive view of the complexities within the middle-ware architecture.
Learn the API testing approach used by Maveric’s digital QE team, which accelerated the transaction processing by 60 times.
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