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The competitive landscape of wealth management industry is evolving very rapidly by a range of forces including an increasingly diversified client base with much higher expectations, hybrid advisory model powered by technology, regulatory change, geopolitical volatility and aggressive fintech with efficient digital business models.
The leading wealth management firms are gearing towards a future-ready enterprise. Some of the key strategic goal includes,
Wealth firms are embracing hyper personalization in context of client’ life goals and looking forward to offering customizable solution including innovative products such as crypto funds, direct indexing, private equity etc.
For many wealth firms, the top priorities are to harness data, use advanced analytics and generate actionable insights with a real-time understanding of the customer and the business to shape-up integrated business decisions. Firms are rebuilding their tech stacks and embracing advanced analytics to personalized wealth management services. Some of the use cases include,
1) Client onboarding Client acquisition and onboarding includes client discovery, risk profiling, account opening and onboarding. Firms are using analytics for lead generation and share-of-wallet modeling.
2) Personalise and improve quality of investments Wealth firms offers a wider range of solutions, from the simplest products (equities, mutual funds, exchange traded funds) to complex higher-yielding investments (private markets, venture capital, pre-IPO, and structured products). Advisor must be equipped with analytical tools that help clients make complex investment decisions.
3) Client engagement Client engagement and deepening relationships includes personalized research, portfolio management, client segmentation, recommendation engines (next best actions). There are also opportunities to use behavioral analytics to de-bias investment decisions i.e., transform behavioral data into advisor recommendations. Firms are aspiring to personalize customer journeys using data insights across the value chain.
4) Flexible pricing model
The wealth managers need to build in flexible pricing models aligned to clients’ needs at every stage of their lives. An increasingly common pricing model is for clients to negotiate a flat fee based on the value of their investments. While embracing new revenue model wealth firm must use data analytics to create new efficiencies and equip advisor with nextgen analytical tools to increase its client base
Conclusion Most wealth management firms have already embarked on a data analytics journey and are at distinct levels of maturity but have not fully realized the potential of data insights. With customers at the core, wealth management firms must evaluate whether the data insight capability allows them to connect with customers with compelling value propositions in a highly personalized manner. Firm must empower the financial advisors with NextGen analytical tools to deliver superior wealth management services to clients and drive business growth.
References
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Sonali Patil Cloud Solution Architect at TCS
20 December
Retired Member
Andrew Ducker Payments Consulting at Icon Solutions
19 December
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