Financial Services is undeniably converging around digital, analytics and advanced algorithms. In order to better understand this market, I simply had to experience this phenomenon for myself. After searching far and wide, I found Glenn.
After some hustling, a fresh set of "D" sized batteries, I felt like I'd made the investment of a lifetime. Let me share some impressive facts about Glenn.
He is a Scooter 2000 model, created circa 1980. His creators needed to embody wealth management into only 5 functions. In a stroke of genius they chose;
- Move forward: The core mandate of any respectable wealth plan and execution
- Change direction: Way ahead of their time here as today's markets swing with wild volatility
- Make Noise: Vital in alerting clients of new ideas / threats / opportunities
- Repeat basic phrases: Important to stay consistent through the cycle "Our thesis is still intact "
- Carry a beer and nuts from "A to B": Because it can.
Moore's Law projects that computing power doubles each 18 months (as adopted by Intel's David House).
"Glenn's 7 functions in 1980 becoming an impressive 117 million functions in today's grunt."
So the question I'd like to explore is; with the remaining capacity of roughly 116,999,997 functions available to Glenn, what should we add so that Glenn has a fighting chance in assisting wealth management practices today?
By blending data from across their practices into a single analytics platform, wealth managers including BT Financial Group, use Qlik to harvest insights by seeing the whole picture, answering these common questions.
Which client to contact?
Client sales / trust / retention are largely driven by timely, insightful contact. Analytics is often employed by combining data from CRM, transaction, research, market data and portfolio holdings to highlight clients in need of contact based on:
- Significant change in portfolio value via market moves
- Country / industry / company news and outlook and its impact on holdings
- Deviation from agreed portfolio allocations
- Lifetime Value (LTV)
- Behavioral triggers like deviations in deposit size / frequency
- Likelihood to take up an additional offered product
- Days since last contact
- Sharing of relevant research based on client's historical trades
What Risk Is My Practice Carrying?
Wealth managers globally have been reeling from damage to their reputations and hefty fines levied by regulators for misselling financial products and misconduct. Our clients adopt analytics to help mitigate this risk by:
- Linking client's risk tolerance with invested product risk / complexity where visual analytics can quickly identify misalignment
- Failure to perform regular client reviews, or perform portfolio rebalancing according to agreed mandate
- Tracking commission and revenue patterns to identify those advisors with lumpy revenue, particularly in the dying moments of their performance period
- Modeling profit & loss (P&L) attribution to detect outliers in large Day 1 P&L, where reference rates may have been booked incorrectly
- Linking application login with annual leave & attendance records with P&L sign-off / computer or terminal ID, to identify instances of account sharing and failure of segregation of duties.
Connect with me in the comments below if you'd like to hear more as Glenn tackles the analytical challenges of today's financial services industry.
What are your biggest analytical challenges?