The data provider is developing its pricing, risk and lifecycle capabilities as structured products become more customised, while its index business is extending into QIS, ETFs and indexed annuities.
Demand for structured products pricing and analytics is being driven by market growth, increased automation and the need for more sophisticated tools to assess increasingly complex investment strategies, according to Thomas Chin, global head of structured products at Bloomberg.
Wealth managers and advisers need tools to assess relative value - Thomas Chin
Chin said investors and distributors were looking for more efficient ways to identify, evaluate and compare investment opportunities, while issuers faced growing pressure to improve pricing, valuation and risk analysis across the product lifecycle.
“The requirements extend beyond the initial structuring and pricing of a product. Wealth managers and advisers need tools to assess relative value, understand risk-return profiles and determine whether a particular structure is suitable for a client,” he said.
The Bloomberg team at the SRP Americas 2026 Awards in Scottsdale, Arizona on 23 September 2026 with Thomas Chin on the right.
Bloomberg's offering covers structuring, pricing, analytics and lifecycle management, allowing users to analyse products before execution and monitor positions after issuance. This includes product design and pricing, scenario analysis, valuation and risk assessment, as well as monitoring key lifecycle events such as barriers, coupons, calls and maturities.
The capabilities sit alongside Bloomberg's wider enterprise solutions, which include order, risk and portfolio management.
The expansion of QIS
The growing demand for tailored investment outcomes is also influencing product development. Chin pointed to the increasing use of quantitative investment strategies (QIS) to create exposures linked to specific underlyings, asset classes, factors and investment themes.
In the US, traditional structured-product strategies are also being packaged in exchange-traded funds (ETFs), including autocallable and defined-outcome structures. The development reflects an effort to make established payoff strategies available through different investment wrappers.
Customisation, according to Chin, does not necessarily mean creating entirely bespoke products. It is also about giving users flexibility to adjust parameters such as the underlying asset, maturity, strike, level of protection, yield target and payoff, while retaining a consistent framework for pricing and operations.
“Reusable building blocks, automated pricing and risk analytics, request-for-quote (RFQ) execution and lifecycle management can help support this flexibility without adding unnecessary operational complexity,” he said.
Bloomberg's involvement in the index market also extends into structured products and indexed annuities. The company worked with RBC Capital Markets and Salt Financial to develop the Bloomberg Versa 10 Index, which was subsequently licensed by SILAC Insurance Company for fixed indexed annuity offerings. Bloomberg and RBC have also worked together on products linked to Bloomberg indices, including in the QIS and structured notes space.
Enhancing the investment lifecycle
Technology is expected to play a greater role in how investors and advisers identify opportunities, analyse products and monitor portfolios. Chin said artificial intelligence and automation could help users process information, compare structures and conduct analysis more efficiently.
According to Chin, AI could make it easier for wealth managers and advisers to generate investment ideas and carry out independent analysis using their knowledge of clients and their investment requirements. Issuers, meanwhile, would continue to focus on developing more complex solutions and bringing new products to market.
Looking ahead, Chin sees further scope to connect data, pricing, analytics, execution, risk and lifecycle information. “Bringing these elements together could provide a more comprehensive view of structured products within portfolios, while natural-language interfaces could make it easier for users to interact with analytics and initiate workflows,” he said.
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