Artificial Intelligence in Banking - use casesRead post
Banks use Machine Learning to increase their bottom lines through gaining competitive advantages, reducing expenses and improving efficiency. They optimize all areas of their businesses, starting from risk analysis and fraud detection to marketing, to make data-driven decisions that lead to increased profitability.
1) DIRECT MARKETING
To be successful as a bank, the key is to maximize ROI. You can do this with boosting marketing response rates and minimizing misdirected communication. Current state-of-the-art algorithms give the best results, but they also require specific, deep domain (subject-matter) expertise in Machine Learning.
Marketing to prospects is expensive and is going to be more difficult with the coming of GDPR regulations. There is no point in using default schemas for direct emails and telemarketing, as it is not going to help you target your customer base. Incorrect targeting hurts your brand and makes your prospects feel like they are being spammed, resulting in low response rates that lead to a high cost-per-lead.
Our cutting edge algorithms included in the Data-Driven Sales Optimization System can deliver data about which people are most likely going to purchase your product or service to yield higher ROI. To achieve your goals, maintain a favorable image of your company with targeted communication to save time and money.
Our Machine Learning systems will make your marketing campaigns more effective. You don't have to be an AI expert - that’s our job.
2) CREDIT DEFAULT RATES
What makes the difference between unsuccessful and successful loan portfolios? The accurate judgements on the likelihood of default rates. Individuals and businesses often need loans and the only way is to use real-time systems to automate loan assessments.
Judging the likelihood of default is not an easy thing. Of course, people with years of experience can do it, but this is not an efficient method, especially if you have a rapidly growing business. You need to have a well prepared and scalable solution to check the default risk of applicants (that indirectly allows you to increase the value and number of loans) and earn more money.
Our cutting edge algorithms included in the Data-Driven Sales Optimization System can deliver information about the predicted likelihood of default for future borrowers. We utilize past information about the default rates for borrowers and incorporate the predictive models into a real-time loan analytics application to allow your business to scale up and earn more money while expanding the loan portfolio.
We make it easy and fast to build and deploy systems for Default Rate-based models and to automate risk predictions in real-time. You don't have to be an AI expert - that’s our job.
3) CREDIT CARD FRAUDULENT TRANSACTIONS
Banks lose billions of dollars per year due to credit card frauds. To reduce the number of these illegal transactions, they need to accurately predict which transactions are most likely fraudulent based on transaction characteristics.
Even if the fraudulent transactions are expensive for banks, it is even more expensive to check every single transaction for fraud. It is very inefficient and takes a lot of time. Investigation of innocent customers leads to a very poor customer experience and pushes clients to leave your business.
Efficient and extremely accurate predictive models that identify likely fraudulent activity. This allows you to investigate only those incidents that likely require it. It results in a better utilization of your resources - they are used to match the greatest return on the investigation. We allow you to build a better customer experience and protect customer accounts at the same time.
Our systems automate predictions of likelihood that a specific financial transaction is fraudulent or not. You don't have to be an AI expert - that’s our job.
4) FRAUD DETECTION
Fraud costs the global economy hundreds of billions of dollars per year. Detect frauds in seconds, instead of months.
The global economy loses hundreds of billions of dollars a year due to fraud and improper payments. Every sector is affected by this. Investigation of every single claim is highly inefficient and time-consuming. Fraud tactics are very sophisticated and evolve quickly, making solutions obsolete not long after they are implemented.
Our Information Extraction System and Pattern Finder are straightforward solutions that use the current data combined with the historical data and can detect fraud in seconds, not months. This allows your company to react immediately and save money.
We build Machine Learning-based solutions available to leverage current market requirements, that result in huge savings in time and money for your company. You don't have to be an AI expert - that’s our job.
5) DIGITAL WEALTH MANAGEMENT
Machine Learning can help wealth management advisory companies and banks with portfolio management.
The primary focus of wealth advisory companies is to capture a greater share of existing assets and to attract new clients. In this competitive market, development of new investment products that reach and engage new customers is crucial.
Efficient solutions for portfolio management to provide new clients with top opportunities that match their financial profile (including their risk tolerance). Our algorithms included in Data-Driven Sales Optimization System and Multilingual Virtual Sales Assistant System will help you with predicting information that can be used to rebalance portfolios without (or with a little) human intervention. They will also help managers in matching customers with the right products.
We use Machine Learning to help wealth advisory companies to develop, test and deploy ideas that can help with portfolio management and get more customers. You don't have to be an AI expert - that’s our job.
Tuesday, 22 May 2018