Streamline applications, detect financial crimes, segment customers, and more!
Identify potential risks in loans and applications and proactively forecast and mitigate losses.
Identify transactions and applications that suggest fraudulent activity.
Identify and Segment Clients
Gain detailed insights about customer's patterns and behaviors and improve credit decisions.
Process applications, track customer activity, and automate workflows in different departments.
Discover some of the solutions we've provided for the banking industry.
Processing Loan Applications
Automating loan processing to increase efficiency and decrease errors
High volume loan applications were time consuming and costly for a leading bank in the MENA region, and decision-making transparency was compromised by human error and bias.
Leveraging Robotic Process Automation and AI technology, Paragon Shift built software bots that automated the process of screening applications and assessing loan feasibility and risk.
The bots helped speed up making decisions about loans, giving customers a seamless experience and freeing up time for human employees to direct their efforts to value-added tasks.
Identifying high value customers and targeting marketing strategies
A Gulf based bank was allocating large sums on marketing strategies that were not achieving target return and were reaching idle customers.
Leveraging Big Data, Paragon Shift segmented the bank's clients based on customer value, activity, and demographics, and created dashboards that highlighted client responsiveness.
The tools helped identify client preferences and direct marketing efforts accordingly to retain existing high value clients and gain new ones.
Anti Money Laundering
Identifying money laundering activities and financial crimes
A leading financial institution in the MENA region reported difficulty in detecting financial crimes. Although they had an AML system, false alerts were high and needed time to be inspected.
Leveraging the power of Machine learning, Paragon Shift built a flexible, adaptive model that accurately detected money laundering activities and improved its accuracy with time.
The model significantly reduced false alerts sent to the institution and successfully detected a higher volume of laundering activities, decreasing cost and time needed to review the alerts.