The credit score prediction model reduces exposure to credit risk and loss by identifying applicants who are at high risk of default and have no credit value but do not have an extensive credit history in case they can cause events (e.g., bankruptcy, default, etc)
Risk management is an important part of financial company management. Risk managers can prevent bank losses in advance by determining whether to repay a customer's loan using the customer's income status, credit history, payment level, external credit evaluation data and other indicators without spending time managing risk. You can save time and money in determining whether a financial service company will approve a loan, and manage risk by quickly predicting a customer's repayment capabilities.
By recommending products to customers, you can prevent customers from churning while doing customized marketing to customers who do not know what products they need. Personalized services are available by introducing products such as credit cards, savings accounts, and deposits that are suitable for customers based on data such as customer's personal information, consumption patterns, and financial performance. Through this, we provide differentiated counseling services. By providing personalized services, you can increase consumer confidence and increase corporate value.
Customer retention is more important than acquiring new customers. If you can prevent churn by predicting which of your existing customers are likely to churn, the benefit can be greater than acquiring new customers. You can analyze customer attributes, behavior, engagement, and external factors to help predict and prevent churn. Customer churn prevention can optimize corporate profitability. By predicting customer churn, financial services companies can increase customer satisfaction as well as increase customer lifetime value.
You can detect suspicious transaction behavior in the market that indicates illegal behavior through transaction patterns using big data of trade and foreign exchange transactions of import and export companies. If fraud is suspected, such as deceiving false trade bonds as legitimate transactions, you can predict the transaction to reject the transaction entirely, or report the transaction for investigation and assess the likelihood of fraud. Fraud predictions can lower false positives. Reducing false positives leads to increased customer satisfaction, sales protection, and cost savings.
Financial crimes are on the rise due to the increase in the volume of financial transactions as financial companies adopt technologies such as fintech and blockchain. Currently, money laundering poses a serious threat to the financial services sector. To prevent money laundering, illegal money laundering can be detected and prevented to identify suspicious transactions and irregular transaction networks. Artificial Intelligence(AI) can detect suspicious transactions and build fraud and money laundering models efficiently, as well as improve employee and business productivity.
We can recommend insurance products that customers need by analyzing their personal information and lifestyle. Personalized insurance product recommendations can improve customer satisfaction and prevent them from leaving. Customized pricing and services are possible through AI-based predictive analysis. Provide accurate insight and prediction of customer preferences and improve customer satisfaction through the personalized marketing activities.
When looking at insurance, the most common form of fraud is plain and difficult to detect. CLICK AI analyzes customers' claims and reviews insurance fraud patterns or customer profiling to avoid insurance fraud risks. Early detection of fraud by employees or customers can significantly reduce industry costs and positively impact insurance premiums. By learning collected customer data, you can analyze and predict whether newly filed claims are inappropriate manipulation behavior.
AI, learned by collected customer personal information (gender, age, occupation, coverage, insurance payments, past chronic information, etc.), can determine conditional acceptance/no insurance coverage to create a fast and accurate insurance screening system. AI can automatically accept or reject contracts on behalf of the underwriter, using customer information to determine whether they are eligible for insurance coverage.
It takes a long time to check the estimate of the accident cost after the traffic accident. You can get a repair cost estimate after all the procedures such as the insurer's dispatch, identification of the accident site, warehousing of the factory for vehicle maintenance, and calculation of the budget. If AI learns repair costs for damaged car photos, it can create a model that can predict repair costs just by sending accident data at the scene of subsequent traffic accidents. The insurance rate can be calculated by recognizing the depth of the damage. These services allow you to establish a fair standard for insurance premiums. AI can also be used to simplify insurers' screening procedures and streamline internal procedures to increase productivity.
With AutoML + Consulting, you can request a professional consultant of DS2.ai to develop artificial intelligence.