Hitachi Innovation and Wealth Management Robo-Advisory – Digital Investment Advice Dan Knight CTO Financial Services, Americas Brian Benedict Director of Financial Services
Robo-Advisement Landscape
The Profile of the Customer
Who Would Use the Tools?
What is Attracting the Customer?
Evolution of the Maturity Curve
The “Rewired Investor” § I trust me § Bespoke § Stay in control § Multichannel § DIY § Multiple sources of advice § Anywhere, anytime § Rich digital front-end § Digital and personal § Risk management as § Tribal wisdom hedging § Skeptical of authority § Democratization of investments § Risk defined as downside § Not a second class investor
Stages of Digital Advisory Solutions
Active Versus Passive
Customer Lifecycle
Options? Partner Acquire Develop
Pros and Cons of Financial Firm Partnering Pros: Cons: § Customers can be supplied with cutting § 3rd party now has access to your edge visualizations customer data § Not as many resources needed to § You are now one step removed from metrics from your customers and their embed partner into banking solution interaction with the partner § Time to market might be fast (but at what cost?) § A sizeable investment to the 3rd party is usually needed § Maintenance and updates are in someone else’s hands § No guarantees of exclusives, giving you nothing more than your competitors
So What’s Involved? § Business performance management ‒ Tracking business results and key drivers § Client acquisition ‒ Leverage internal and external data sources (social, transaction data) to create a comprehensive prospect profile ‒ Mapping of relationships and client leads § Client retention ‒ Leverage channel and social data to assess client sentiment and client risk real time ‒ Leverage internal and external data to understand client interests, life events, and personality to match client advisor to increase stickiness and connectivity
So What’s Involved? (cont.) § Client sales 1. Leverage external data sources to create net worth and share of wallet profiles for clients 2. Measure clients’ propensity to purchase or take advice 3. Assess the client lifetime value 4. Correlate transaction and channel data with market events to reveal the real client risk tolerance § Client advice 1. Leverage survey and other information to create tailored portfolio allocations 2. Re-balance portfolios real-time and trade and investment offerings based on client preferences and market events § Supervision 1. Compare personality and investment profiles and flag suitability issues and offer continued connection for client direction
Governance and Guidance § Digital investment advice tools are dependent on the data and algorithms that produce the tools’ output. Therefore, an effective governance and supervisory framework can be important to ensuring that the resulting advice is consistent with the securities laws and FINRA rules. Such a framework could include: ‒ Initial reviews assessing whether the methodology a tool uses, including any related assumptions, is well- suited to the task, understanding the data inputs that will be used and testing the output to assess whether it conforms with a firm’s expectations. ‒ Ongoing reviews assessing whether the models a tool uses remain appropriate as market and other conditions evolve, testing the output of the tool on a regular basis to ensure that it is performing as intended, and identifying individuals who are responsible for supervising the tool.
Regulatory Guidance § Rule 206(4)-7 under the Advisers Act requires: § Automated advisory systems may create or accentuate risk ‒ Written policies and procedures ‒ The development, testing and backtesting of the algorithmic code and the post-implementation monitoring of its performance ‒ Reviews of sufficient information for the financial situation and investment objective ‒ The disclosure to clients of changes to the algorithmic code that may materially affect their portfolios
Regulatory Guidance (cont.) ‒ The appropriate oversight of any third party that develops, owns or manages the algorithmic code or software modules utilized by the robo-adviser ‒ The prevention and detection of, and response to, cybersecurity threats ‒ The use of social and other forms of electronic media in connection with the marketing of advisory services ( e.g. , websites, Twitter, compensation of bloggers to publicize services, “refer-a-friend” programs) ‒ The protection of client accounts and key advisory systems
Digital Advice § Nearly 140 digital advisory companies have been founded since 2008, with over 80 of those founded in the past two years ‒ Customization ‒ Tax management ‒ Human intervention and oversight ‒ Type of entity providing digital advice
Key Observations and Recommendations § Digital advisors are subject to the same framework of regulation and supervision as traditional advisors; however, the applicability and emphasis may differ in some cases. We suggest that regulators focus on the following key areas: ‒ Knowing your customer and suitability of the solution ‒ Algorithm design and oversight ‒ Disclosure standards and cost transparency ‒ Trading practices ‒ Data protection and cybersecurity
Robo-Advisement Strategy – Build
Build Your Own Translation A combination of a mess of companies with varied experience in the financial services market that might not ”talk” to each other – This is a mess
Data Landscape for Robo-Advisory Conventional Unstructured Sentiment Data Financial Data Non-Financial Data
ACSI – Alternative Data Sources https://hbr.org/2007/03/beating-the-market-with-customer-satisfaction
Process of Building a Robo-Advisor service Unstructured Non-Financial and Sentiment Data Financial Data Conventional
Building the agile Robo-Advisory factory
Advantages of Integrating Robo-Advisement as a Client Option for Customer Connection § Future-proofing your process § Automate tax optimizations for current clients, building trust into the platform to know the customer more completely § Bundled wealth management fee for larger accounts § Add, change or iterate your data sources to adapt with market conditions § Embed the software for both clients and advisors to gain permission based access
Areas We Focus On in Digital Advisory Transformation and orchestration of data from both big and 1 relational data allowing for blending of data at scale The ability to build in automation with data science 2 algorithms that can change as your data sources do 3 Visualize and report internally, for regulator, and for client Managing data for the tracking of lineage from core banking 4 systems, and provide auditability for investment advice
Thank You
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