Companies run different schemes and promotions to fuel growth. But in absence of data, most of these schemes are planned using historic performance only and it does not take into account the true market potential. Because of this approach of not correlating the spend with potential, leakages happen and it is hard to detect them using secondary data analytics approach.
We have built an automated fraud detection and control through self learning evolutionary systems. Our risk detection platform uses ML based profiling for suspicious billing, outlier tracking, claims frauds and channel management and helps decision maker and auditors with risk scorecard, performance visualization and audit automation for seamless pan network controls. Since the platform is self learning, we can quickly move from fraud detection to fraud prevention with our real-time invoice tracking and alerts for pre-emptive controls.