Banks and credit unions are in a constant battle to maintain the loyalty of their members. Member attrition is discovered only after the customer has switched institutions. According to a study, repeat business contributes to over one-third of revenue for more than half of the…
Segmenting members and understanding their behavior is crucial to increase sales and revenue. Marketing campaigns need to target important member segments which have different behavioral characteristics and needs. Some credit unions and banking companies that neglect targeting important segments may find themselves falling behind their…
Maintenance costs are estimated to range between 15% and 40% of total production costs. In the last three years roughly 82% of companies experienced at least one instance of unplanned downtime; in just the automotive industry alone, the average manufacturer loses $22,000 per minute when…
Roughly 2.3 million Americans are victims of medical identity theft per year and have to pay an average of $13,450 in out-of-pocket expenses–two-thirds of those patients reported paying over 13,500. Medical identity theft is estimated to cost the healthcare industry over $30 billion a year….
According to the California Department of Insurance, the Fraud Division received 15,112 suspected fraudulent claims (SFCs), assigned 532 new cases, made 201 arrests, and referred 317 cases to prosecuting authorities from 2020 to 2021. The potential loss amounted to $215,383,939. However, auto insurance fraud is…
Industry: Government, Financial Services
Business Application: Fraud Detection
Avijit Datta is CEO of Aviana Global Technologies, a company dedicated to working with organizations that need predictive analytics to make better decisions, effectively manage risk and improve profitability.
Avijit Datta is CEO of Aviana Global Technologies, a company dedicated to working with organizations that need predictive analytics to make better decisions, effectively manage risk and improve profitability.
Knowing where to go next is the superpower of savvy companies. Predictive tools guide executives to better decisions. Yet getting these insights has a history of implementation delays, incomplete information leading to incorrect insights, and predictions too old to be useful. How do you fix this?
