Advancement in AI and high-performance computing technologies offers banks the potential to fight fraud, improve security
and operational intelligence in radically new ways
Banking & Finance
In the digital age, financial crime is accelerating rapidly. Consequently, fraud detection and prevention now represents one of the biggest areas of concerns for the financial services industry. The banking and financial services industry is one of the earliest adopter of AI, especially in the of use of chatbots to improve customer support services and predictive customer churn analysis. With AI, financial institutions can also maintain a step ahead of fraudsters, effectively combat threats and maintain a secure operating environment. These facilitate immediate actions that will mitigate financial losses, preserve customer trust, and safeguard the reputation of your bank.
Fraud Detection and Prevention
Real-time fraud detection is of paramount importance in today's fast-paced business environment. Fraudsters are becoming increasingly sophisticated, constantly adapting their techniques to exploit vulnerabilities and evade existing detection systems. Rule based systems are static and can’t learn new fraud patterns. A paradigm shift in the approach to mitigate fraud risks is now needed by financial institutions going forward.
Existing approaches to identifying fraud and money laundering rely on databases of human-engineered rules that attempt to match patterns that are indicative of fraud. New rules are added to the rule engines as new fraud schemes are identified. AI-based models, trained with historical financial transaction, can generalize to learn new fraud schemes autonomously. While rules are the first line of defense and an important part of overall fraud detection strategy, combining them with cutting-edge self-learning models will provide the optimal solution.
Surveillance and Operational Intelligence
By harnessing existing surveillance networks in banking halls and around ATMs, AI-driven video analytics can enable financial institutions to increase safety and situation awareness. Security officials will be equipped to respond to events in near real-time as well as review video recordings with ease and precision to accelerate post-event investigations.
By aggregating video analysis data, financial institutions can extend the value of their cross-site surveillance systems, Video analytics can be used to observe customer trends, traffic and also detect potentially suspicious behaviours across multiple branches. Real-time alert notifications can then be sent to a centralised dashboard based on rules for monitoring the increase or decrease of people in a pre-defined range of view or area, which is ideal for tracking queues and waiting areas. These can be used to improve operational efficiency, business productivity and customer experiences by the operations team. Count-based rules can also generate alerts to assist security team in monitoring people traffic in restricted areas and/or time of the day.
Facial Recognition
There are ethical and privacy concerns surrounding the use facial recognition technology in public places globally. However, responsible adoption of this technology is being used by financial services and other sectors to enhance their businesses, protect their employees, customers and assets. For example, many banks use face recognition to authenticate a customer’s identity for online or mobile banking applications. Banks also use facial recognition to control entry and access to secure and restricted areas. For example, a whitelist of people who are authorized to be in the building at a particular time be compiled, so that alerts can be triggered when people that do not match faces on the list are detected.
Another key area where facial recognition can provide the greatest value to banks is real-time alert generation when a suspect on the banks watchlists enters their premises or is seen near any of the ATMs. Banks can save valuable time by utilizing face recognition to alert on potential suspects and expedite the forensic review of post-incident investigations. With or without facial recognition, you can drive exponential value for your bank or financial institution by leveraging video analytics to accelerate investigations, empower preventative security, and drive intelligent decision-making.