In financial services, the competition for customer share is intense with corporations searching for any marketing advantage while countering fraud, money laundering and other challenges. Increased customer satisfaction and loyalty, reduced fraud, and reduced regulatory fines benefit businesses that make successful use of AI. For a variety of situations, including fraud detection and credit risk scoring companies use AI.
In the banking industry, fraud is a major problem. As per fraud expert Frank McKenna, the top 10 forms of fraud, comprising card fraud,loan fraud and wire fraud, accounted for $181 billion in annual losses in 2016, and the figures are only growing. Identifying and mitigating fraud is a massive challenge for banks because of the broad range of forms of fraud and the number of transactions that have to be checked and it is not possible to keep up with manual or rule-based systems.
In order to detect fraud patterns, AI can be used to examine vast amounts of transactions and then use those patterns to recognize fraud as it occurs in real-time. AI models could be used to refuse transactions directly or mark transactions for investigation when fraud is suspected, and can also rate the probability of fraud, so that investigators can focus their work on the most promising cases.
At Cyber Chasse Inc., the goal is to democratize AI for everyone so that more individuals across sectors can use AI’s power to solve business and social problems. With strong alliances with leading brands, the financial services market is a key focus for the company.
Cyber Chasse enables teams in data science to scale by significantly increasing the pace of building highly precise predictive models. Innovative features of special interest to financial services are integrated including machine learning interpretability, reason codes for individual predictions, automatic modeling of time series etc.