The Introviz Data analytic platform (VizIntel ™) is a software designed to help enterprise IT teams manage, deploy, and retrain machine learning models at scale. Our AI experts will help to extract data, train and create a model that can assist you in strategic and tactical decisions. VizIntel ™ has external integration to multiple data sources including social media to enable a sophisticated model.

VizIntel AI models:

 

Insurance

Insurance claims fraud isn’t new — it’s been around since the inception of our industry in the 17th century. Yet it is an industry challenge that continues to worsen at an alarming rate as fraudsters become more sophisticated and organized.

Insurance claims processing is a notoriously laborious intensive and prone to error and tends to miss cases of fraud which result in over $40 billion dollars in losses per year. This results in almost $400 – 700 in premium increases per family!

 

 

While rules-based detection might seem like a good starting point, it fails to take into account the changing landscape, where fraud schemes continue to evolve. The system must continuously and automatically adapt using current data – and a lot of it. VizIntel ™ goes well beyond an insurer’s own claims data and tap into other industry data sources such as third-party public records, police reports, criminal records, financial stress indicators, social media and more.

 

 

Banking & Finance

Financial services companies are drowning in data. Banks have to process many millions of transactions per day. Their compliance departments may have to monitor hundreds or even thousands of authorizations per second. They may have only a few milliseconds to judge whether a given transaction is fraudulent or not.

Many of them are forced sample only a tiny percentage of total transactions as they learn to model fraud. Massive downsampling means that these banks are not taking into account almost 90 – 95% of the transactions flowing through their system every day, and in doing so, they lose valuable information and put the bank at a risk!

More efficient machine-learning is crucial to process transactions for efficiently and to learn from a wider array of data. Our model can be trained with existing data and promises more accurate models for detecting fraud and other anomalies, it is able to learn from new data automatically on our platform.

 

Mortgage Fraud

In the United States, financial analytics firm CoreLogic has reported that the risk of fraud in the mortgage market has spiked by 12.4% year-over-year in the second quarter of 2018. The data was alarming enough that mortgage giant Fannie Mae has issued a warning to its affiliated lenders about the increasing risks, including a glimpse of what may be fueling it. At issue, they say, is that rising interest rates and skyrocketing home prices are driving many applicants to overstate their earnings in an attempt to qualify for loans that are beyond their means. Ordinarily, lenders cross-check and verify income statements from applicants, and in the past, detecting inflated earning statements was a simple matter of following up with employers. Now, the internet is providing a way to fool even seasoned fraud prevention specialists.

For its part, the mortgage industry seems to be realizing that they need to take new steps to curb the rising rate of fraud. To tackle the problem, they’re turning to a whole new generation of AI-powered analytics systems such as VizIntel ™,  that have the capability to comb through vast amounts of data to find patterns indicative of fraud that would otherwise go undetected. A McKinsey survey indicated that a majority of risk managers believed that the new tools would reduce credit decision times by 25 to 50 percent, and reduce losses due to fraud by at least 10%. VizIntel ™ platform analyzes previous fraudulent applications and trains the model using machine learning techniques to develop smarter filters. That means that each fraudulent application that makes it through the system provides more data to make the system even smarter going forward. Good news is –  future fraudulent transactions will be caught!