With Bespoke Custom Investing (BCI), Polly Portfolio offers financial advisers a platform that makes it easier to provide personalized financial management and investment plans. The technology gives advisers the tools for better engagement by using natural language processing to transform client concerns—on issues like investment philosophy and economic outlook—into customized investment advice.
Advisers can either use their own model portfolios as a base investment strategy or select one of Polly Portfolio’s models. They engage with their clients to determine tax planning, investment preferences and risk tolerance, economic outlook, and the status of any held-away assets (assets not actively managed nor affiliated with the adviser’s firm). After any additional adviser or client customizations are factored in, the BCI investment engine builds a personalized investment strategy with natural language explanations.
The release of Bespoke Custom Investing comes as the company transitions toward a B2B model. As Polly Portfolio began working with wealth managers, it became increasingly clear that the path of least resistance for its technologies was to “decouple” its signature solutions—Bespoke Custom Investing and Sophograph (demonstrated at FinovateSpring 2016)—to better target the markets that would most benefit from each technology.
The initial challenge for Polly Portfolio was figuring out how to maintain the customization, natural language processing, and portfolio-building of BCI without plugging in to Sophograph. The answer was to leverage the model portfolios offered by the financial adviser. “Many advisers use very basic model portfolios,” says Tom McCosker, Polly Portfolio’s COO and CFO. “We built BCI to plug into model portfolios. Then customize around (their) model, using basic risk exposure, and then customize for taxes, headway assets, views on the economy, and so on.” The integration is API-driven, so there is no need for full stack integration.
BCI’s ability to increase and deepen customer engagement is another worthwhile feature of the platform. “Engagement calls are a trick for advisers,” McCosker points out. “What do you talk about on the investment side? You’re in a model portfolio, so that’s it.” By making it easy to translate client preferences into customized investing ideas that are explained in natural language, the platform can be a significant engagement solution for advisers, as well.
Founded in 2014 and headquartered in New York, Polly Portfolio demonstrated its technology at FinovateSpring 2016. This summer, the company launched a free, investment chatbot for Facebook Messenger, Polly Chat, that develops personalized trading and investment ideas through interaction with the user. Jasen Yang is founder and CEO.