Drive Highly Personalized Consumer Finance Investment Recommendations with AI and ML

Nearly 80% of traditional financial institutions said they plan to increase innovations to boost customer retention. With changing regulations, economic uncertainty, and growing customer expectations of personalization and speed, staying competitive in the financial services industry request such bold digital changes. Incorporating new methods and digital tools such as data science, artificial intelligence (AI) and machine learning (ML) accelerates your time to market, increases your ROI, and provides your users with an unparalleled digital experience.

Data and Machine Learning in Financial Services

Data science has provided the financial services industry with the means for innovation by using data to improve investment services and operations. When combined with AI/ML solutions, data science delivers hyper-personalization. This leads to reduced churn, higher customer loyalty, and greater revenue.

Using Google Cloud’s expansive AI/ML and smart analytics capabilities to drive growth, reduce costs, mitigate risk, ensure compliance, and increase efficiency, financial organizations can further accelerate their digital transformation. Recognizing these strengths, SoftServe partnered with Google Cloud to develop a solution that provides highly personalized investment recommendations which improve user experience, increase customer retention, and attract new customers.

The Investment Product Recommendation Engine (IPRE)

Our team of experts saw the opportunity for a new consumer finance solution while using Google Cloud’s advanced data analytics and AI/ML such as Dataflow, BigQuery, AutoML, Cloud Functions, and more. This led them to build the Investment Product Recommendation Engine (IPRE) reference pattern.

Fully automated and easy to deploy, the IPRE begins by gathering market data such as quotes and daily or weekly open, high, low, close prices on available investment products such as stocks or bonds. It then uses ML algorithms to balance an individual investor’s risk preferences with the investment product’s expected return to provide a highly personalized recommendation for that investor.

This practical use case of Google Cloud data analytics and AI/ML services shows how SoftServe and Google Cloud work together to solve complex problems. SoftServe’s drive to create intelligent solutions using Google Cloud is one of the reasons we were named 2020’s Google Cloud Specialization Partner of the Year for Machine Learning.

Drive Innovation

Some of the biggest challenges facing consumer finance companies today are finding ways to inspire customer loyalty while meeting the unrelenting pace of changing regulations and a digital market. Automated solutions such as our IPRE enable data science workflows and improve applications with machine intelligence. This makes companies more agile while providing better customer experiences.

You can find more in-depth details about this solution in our technical whitepaper and at the IPRE Google Cloud pattern reference page, where you can access the technical reference guide and Github repo to implement your own IPRE.

Let’s talk about what combining SoftServe’s data analytics and AI/ML experience and Google Cloud’s services can do for your business.