Financial Services and Insurance
Financial Services and Insurance
There is increasing competition, stringent rules and compliance and tightening margins in the financial services and insurance sector today. Processes need to be improved and agile by incorporating available digital data along with existing data sources for faster decision-making.
The second largest title insurance company in North America engaged Business Brio to guide them in understanding and getting insights into fraudulent transactions. Understanding the patterns in the title plant from various data sources for previous transactions on properties and identification of the outliers for flagging for special diligence were critical success factors. Dynamic models enabled quicker diligence and faster decision-making.
At Business Brio, we have used Single Exponential Smooth, Double Exponential Smooth, ARIMA and back-propagation neural network. We did find Neural network to have better forecasting performance than the classical forecasting algorithms in case of wind energy forecasting for a particular project and won the NASSCOM Analytics Innovation award in 2015 for effectively using the same for business.
Unsupervised and supervised learning methods like regression, support vector machines (SVM),KNN, K-means, PCA are used to recognize patterns and make data-driven predictions or decision outputs. We extensively use Python and R for applying the algorithms.
Business Brio uses advanced analytics techniques for faster decision making in loan processing and fraud detection.
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Applications
Early Warning System
Analyze trend and patterns by leveraging big data from different systems on various attributes like geography, agent groups, mortgage release information and develop an early warning system for possible frauds using machine learning algorithms
Customer Analytics for Growth
Leverage data to boost customer base, develop customer retention strategy, up-sell and cross-sell for boosting portfolio growth and analyze campaign performance by visualization and interactive dashboards
Customer Analytics for Growth
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Fraud Detection
Detect medical cases with high probability of fraudulent claims from providers and create diligence path for prevention of frauds using predictive models
Credit Risk
Identify customers with high probability of default for quick decision making while loan disbursement in financial services using machine learning and decision models
Customer Analytics for Growth
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Advantages
View how our technology works
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Quality & Innovation
Our Engagements
We equip our clients to deliver value out of volume of data.
Contact Information
14th Floor, Unit 14, Tower 1,
Srijan Corporate Park,
Block GP, Sector 5,
Salt Lake City,
Kolkata 700 091, India
