Banking happens in an environment where massive amounts of data is generated in real time, and where each transaction needs to monitored for risk from the perspectives of customer safety, regulatory compliance and banks' own exposure. While AI offers promise to simplify these tasks, the 24x7 monitoring needs, ever changing macro regulations to comply with, and newer services that customers demand, make it challenging to organize and execute on competing dimensions, while keeping within stretched operational budgets.

Autonomous systems are able to stay in always-on scan mode, while monitoring on risk parameters on a far larger scale than possible with traditional systems while being intelligent enough to uncover emerging risk parameters and broad patterns across geos and time periods.

  • Use Autonomous AI systems to design customer specific intelligence that can manage customer lifecycle right from targeting to sustenance thus delivering a differential experience

  • Automate the transaction monitoring strategy that would consider thousands of dimensions, beyond human assigned rules, to monitor in real time and flag risks with high precision and recall

  • Provide comprehensive  coverage on transactions through expertise based on historical data, risk and regulatory policies and independent outlier spotting and trend discovery abilities 

  • Using Deep learning based vision and reasoning systems to automate transactions thereby handle higher volumes, decrease human involvement and deliver quicker turnarounds.

Delivering differential product experience to customers through deep learning that can understand the customer proactively

Improve transaction monitoring efficiency through flagging risks in real time and with high capture and hit rates

Efficiently monitor trade transactions through lower effort towards risk and compliance with high recall on identifying transgressions.

Automate mundane 'cost' tasks with high efficiency thus improving the bottom line and delivery TAT and improving customer experience.

Improve the efficiency of Underwriting by at least 40% and speed of the process by 30%, impacting the business from topline and bottom line

Delivering differential product experience to customers through deep learning that can understand the customer proactively

Use Autonomous AI systems to design customer specific intelligence that can manage customer lifecycle right from targeting to sustenance thus delivering a differential experience

Improve transaction monitoring efficiency through flagging risks in real time and with high capture and hit rates

Automate the transaction monitoring strategy that would consider thousands of dimensions, beyond human assigned rules, to monitor in real time and flag risks with high precision and recall

Efficiently monitor trade transactions through lower effort towards risk and compliance with high recall on identifying transgressions.

Provide comprehensive  coverage on transactions through expertise based on historical data, risk and regulatory policies and independent outlier spotting and trend discovery abilities 

Automate mundane 'cost' tasks with high efficiency thus improving the bottom line and delivery TAT and improving customer experience.

Using Deep learning based vision and reasoning systems to automate transactions thereby handle higher volumes, decrease human involvement and deliver quicker turnarounds.

Starting your AI journey?

Leverage our team experience in deep learning and autonomous systems in financial services to productionize complex AI system in production through our off the shelves products or platforms.

Ideate, Innovate & Stay ahead!

Connect with arya.ai