Fraud Detection & Prevention
Detection of fraud in insurance business could create a significant impact to the company’s bottom line. Starting from detection of information misrepresentation at the underwriting stage to detecting fraudulent claims, data analytics could be a significant strategic advantage in this highly competitive space. Having a strong fraud detection and prevention capability around data, information, analytical methods, and operational infrastructure is a key differentiator.
Our offerings in this space are the following:
- Predictive Modelling: Detecting likelihood of a fraud event (a falsified application, a bogus claim, etc.) for subsequent actions, such as, auto rejection/ deeper investigation. With a proper blend of experience and analytical rigor, our model development process involves inclusion of varieties of data elements, feature engineering, rigorous model training (traditional/ machine learning) and testing to arrive at models that are fit for purpose. These models provide benefits at scale and help organization achieve a productivity gain of 30% – 50%.
- Prevention and Detection Strategy: Given the highly dynamic and ever-changing modus operandi of fraudsters, we help firms create analytics-led strategies for faster detection/ prevention of fraud events. This involves development of new rules, ongoing management of rules in order to ensure effectiveness and optimization of two competing objectives – operational losses and revenue/ customer experience. The resulting benefits are visible in terms of improved detection rate and reduced false alarms.
- Operations Analytics: While tightening the upstream areas as above, we also help operations manage the investigation process effectively and efficiently. Our approach around planning operational capacity optimizes cost, quality, risk and customer experience. Key services include capacity modelling, queue design, investigators’ decision quality assessment and MI for gamification.
- Fraud Reporting and Analysis Packs: Comprehensive reporting packs for having an eye on the hotspots, emerging trends, flash frauds, our reporting packs are custom designed as a service using powerful visualization tools and analytical middle layer.
- Investigation App: Designed using intuitive graphical interface and right amount of information, we design custom apps so that firms can uncover hidden patterns and complex interplay of customer attributes. Usually meant for smaller sized organizations, this results in significant cost advantage using open source tools like R/ Python.
We have been working with both smaller and larger players in this field for several years. The analysts specializing in this area brings with them a rare blend of analytical rigor (Statisticians/ ML specialists), programming skills (R, SAS, Python), and domain (insurance and the broader financial crime risk analytics).