Artificial Intelligence in Finance - use casesRead post
Financial institutions 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 fraud detection and marketing to wealth management, to make data-driven decisions that lead to increased profitability.
1) CREDIT DEFAULT RATES
What makes the difference between an unsuccessful and a successful loan portfolio? 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 it 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 to quickly 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.
2) FRAUDULENT CREDIT CARD TRANSACTIONS
Financial institutions are losing billions of dollars per year due to credit card fraud. 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 also very inefficient and takes a lot of time. Investigation of innocent customers leads to a very poor customer experience, which risks pushing them away.
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 better utilization of your resources - they are used to achieve 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 the likelihood that a financial transaction is fraudulent. You don't have to be an AI expert - that’s our job.
3) DIRECT MARKETING
To make a successful business, the key is to maximize ROI. You can do this by boosting marketing response rates and minimizing misdirected communication. Current state-of-the-art algorithms give the best results, but they also require a 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 the right customers. 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 information 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.
As a financial system, blockchain is a distributed and robust system that is particularly vulnerable to many security threats. Use the newest technologies to maintain security and trust in your systems with the detection of anomalies anywhere along the chain.
Blockchain, also called the distributed ledger technology, is one of the fastest growing technologies in the field of financial services. It allows for transparent recording of transactions without an intermediary while still offering high security.
We developed a solution that utilizes the power of our Pattern Finder, Information Extraction System and Distributed Knowledge System to automate the process of identification and prevention of identity theft, frauds and illicit transactions in the whole blockchain. We also used some parts of our Data Driven Sales Optimization System to detect anomalies anywhere along the chain.
Our systems will rapidly predict potential intrusions across multiple vulnerability vectors. Combining our deep knowledge in Machine Learning and Security topics, we make sure there is a chance to take steps against potential security threats before they happen. 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 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, the 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 profiles (including their risk tolerance). Our algorithms included in the 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 their ideas that can help with portfolio management and to get more customers. You don't have to be an AI expert - that’s our job.
Thursday, 21 June 2018