In today’s competitive business environment, financial institutions need forward-looking predictive insights that can help shape tomorrow’s business strategy and improve day-to-day decision-making. Advanced analytical solutions can address critical business questions with ease, speed and accuracy by combining financial data with external data such as demographics, social media etc. We have a wide range of advanced data solutions in the areas of retail banking, card services, asset management and insurance services.
We help you filter and analyze large amounts of data easily and become a data-driven organization by identifying, targeting and retaining high-value customers. We believe analytics is a critical component for your business as it will help in reducing financial losses through real-time fraud detection, influencing customer purchase behavior through real-time targeted and personalized offers, hardening predictive credit risk models and optimizing delinquency models that can predict the probability of a loan default.
Fraud Analytics & Collections Modeling
Data and insights can be used to observe, decide and act in fighting fraud. Our experts combine statistical techniques along with machine learning to identify opportunities, hidden threats & risks in customer data; identify and isolate fraudulent transactions; provide cross-channel monitoring and combine diverse sources to identify matching values for potential fraud on a regular basis. Businesses often need to work with their customers to reduce their levels of debt quickly and manageably. We build predictive collection models by using customer insights and machine learning technologies to help you develop a strategy that can maximize collection revenues and minimize operational costs.
Companies need versatile, high-performance analytical tools in order to comply with new regulatory requirements that demand greater scrutiny of risk. At DecisionTree, we offer a suite of solutions for enterprise-wide risk management across asset classes. With financial risk analytics, you will get access to dynamic, real-time risk reports as well as credit risk analytics for complex portfolios, enterprise-wide stress-testing framework and comply with the Basel requirements by supplementing your existing infrastructure and processes.
Marketing Insights and Sales Analytics
We enable enterprises to mine structured and unstructured data, incorporate insights into the financial planning process and construct a single source of financial truth. We also help organizations identify business opportunities using predictive insights and improve ROI as using data is shown to make better decisions and increase marketing productivity by 15-20%. Sales revenue is the lifeline of any organization. Banks that apply analytics to customer data have a market share lead of four-percentage points over banks that do not.
Focusing on customer needs is going to be key to survival now and an organization’s ability to drive growth hinges on the depth of its consumer insights and how well it translates those into effective action. We help financial institutions drive new growth, facilitate better customer engagement and support customer-centric business transformation by helping them create a robust predictive analytics infrastructure. Some of our solutions include customer clustering, customer LTV, retention modeling, cross-sell and up-sell modeling and best product recommendation. etc.
Personalized Campaigns and Response Analytics
A personalized approach in the financial services industry will enable you to build deeper relationships with your customers by delivering consistent experiences across channels and devices. Knowing what your customers look like, what motivates them or influences their decisions is essential to clear segmentation and in turn personalization of the marketing strategy. By analyzing a customer’s offline and online behaviors, we will enable you to target high-value customer segments through accurately targeted offers, leading to an increase in response rates.
Using retail analytics on loyalty card data, a leading pharmacy retail company increased transactions by 15% and clocked 30% rise in average ticket size for loyalty card holders.
Sales at a leading US-based marketplace seller soared 1.5 times, while operating margins registered a 50% increase after changes were made to its pricing algorithm.
Retail giant registered 18% revenue growth by using analytics-driven targeted marketing.