FinTech

keys 5

Global Ai integrator

Services and products in the banking sector

1. Analysis of customer churn

Task:

High outflow of customers, expressed in the absence of purchases and payments for a certain period of time. The reasons for the outflow are not always obvious, and customer retention programs are ineffective. We To develop a model for evaluating each client for the propensity to outflow and taking appropriate measures to retain it.

Result:

Data on customer payment transactions, socio-demographic characteristics and information describing the bank's products are analyzed. As a result of the analysis, using machine learning technologies, an algorithm has been developed that predicts the probability of outflow and shows the most likely factors affecting the termination of each of the clients' use of the bank's services. Company increases revenue by effectively retaining existing customers and maintaining loyalty.

2. Forecasting customer spending in the future

Task:

Low efficiency of the loyalty program leading to the problem of timely delivery of a specific product to the target audience. Low accuracy in predicting customer behavior. We have to develop a model for predicting the spending of selected customers for a certain period of time

Result:

Based on the history of past transactions and additional information about users, a model is built that predicts customer spending in the future by specific categories (MCC codes). The forecast of the model helps in optimizing financial flows, to predict some facts from the client's life (for example, the fact of a trip abroad),and to improve the quality of recommendations and further increases the accuracy in identifying clients prone to churn.

3. Clustering of the client base. Recommendation system of banking products

Task:

New customers from advertising do not pay for additional services, or they pay, but after a very long period of time. We have to develop an algorithm for segmenting the customer base. Build a recommendation system for the bank's services.or the bank's services.

Result:

A system has been developed based on the recommendation of the bank's services, the input of which is provided with information about the client's transactions, income, socio-demographic characteristics, etc. Recommendations are based on the behavioral characteristics of one person or a group of people (groups are determined as a result of the algorithm for customer segmentation). As a benefit: increasing the profitability of banking products, reducing marketing costs and increasing its efficiency, increasing sales through cross-sell and upsell

4. Forecasting the delinquency of customers-companies on loans

Task:

At the moment, in most banks, the credit risks of companies are analyzed monthly manually, and selectively for some of the companies from the entire list. We have to develop models for predicting the probability of bank customers delaying loan repayments based on company data (information about the company, its transactions, concluded contracts, etc.)

Result:

Early detection of companies (customers) closest to the risk of delinquency on a loan (even before the fact of delinquency). The forecast of the model is aimed at helping monitoring specialists to more effectively find companies with increased credit risk and quickly notify owners and management of companies about possible risk in order to minimize it.

5. The model of automatic classification of texts of customer requests

Task:

A large amount of time is needed to process the flow of input text information intended for different persons (departments) of the company. The company's managers classify mail manually. We have to automate the process of classifying the input stream of textual information by thematic sections stream of textual information by thematic sections

Result:

The model classifies incoming customer requests received via email. Classified requests are automatically sent to the relevant persons. As a benefit: reduction of labor costs for working with letters, reduction of request processing timе

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