Machine Learning in Finance
Sales
Make personalized offers through customer segmentation and analysis of current products;
Predict customer churn based on loyalty score and user history (social media messages, number and frequency of purchases, average spend, and etc.);
AOptimize ATM network based on customer traffic, balance, cash collection data (time, cost of transport, banknotes ordered, currencies and etc.)
Call Center
Reduce workload on first- and second-level support staff with chatbots that can recognize spontaneous speech and instantly answer to customer query;
Script optimization and assessment of calls through transcription and further analysis of call impact (customer emotions, whether they made a purchase, call length, script deviation, and etc.).
Cyber Security and Risk Assessment
Protect payments from fraud and phishing attacks using customer behavior rules (receipts, geolocation, goods purchased, and etc.);
Loan scoring system, which takes into account external information about customer.