Private Wealth Management Solution for Choosing Optimal Asset Allocations
Market Background
The individual investment advisory practice for many years had no significant changes in its process. Private wealth management requires direct interaction of the advisee with a financial advisor who assesses information, trends, and market sentiment to develop potential investment strategies.
But this model is hardly scalable with the growing quantity of transactions in the market and is losing its prime position to automated solutions featuring integrated algorithms and streaming data processing.
A solution that brings reliability, convenience, transparency and accessibility into managing private wealth investments by utilizing big data, artificial intelligence and business intelligence can meet the evolving needs of a dynamic market.
Business Challenge
Individual investors place a great emphasis on the reliability of their financial advisory when making investment decisions. Smarter, more transparent software algorithms ultimately translate to higher investor confidence when making assets allocation decisions. Customers also show increasing interest in having quick access to their financial holdings, circumventing the hurdles of a traditional financial advisory or broker.
Another challenge is that as a portfolio becomes increasingly comprised of different assets, its dynamics becomes more complex. Investors are looking for a forecast of these future dynamics for a given portfolio, as well as recommendations for products that have large upside potential with minimal risk. Providing reliable data for customers supports and guides them in developing their personal investing strategy and custom portfolio composition.
Project Description
Though forecasting capabilities already play an increasing role in high-frequency t rading, it is not as common in consumer portfolio management systems. SoftServe aimed to merge those to bring more value to managing individual investor assets.
Stock price predictions – calculating the future time series for an input of shares (current portfolio).
Portfolio optimization – the tool uses smart algorithm to analyze the predicted time-series for a set of shares and defines asset allocation options that will align with user requirements to risk tolerance and desirable profitability.
SoftServe R&D team decided to make the commonly used algorithm even smarter than before. We included market signals, corporate network and sentiments analysis to be part of the input data for the analyzing function.
As the result, the algorithm developed by our team uses a few types of input parameters for conducting the individual stock price prediction:
- historical data on stock prices, volume history, and market average
- Sentiment analysis index based on reliable news sources
- Network science to embrace corporate network effects.
This covers both the quantitative and qualitative parameters influencing the future price.
Secondly, accessibility and convenience. The voice enabled personal assistant in SoftServe’s private wealth management solution is able to seamlessly lead customers through the whole investing journey up to placing an order to a broker according as aligned with a chosen strategy. The smart algorithm is integrated into the user-friendly interface and works with the Amazon Alexa Echo Show to bring the investing interaction experience with a robo-adviser to a whole new level.