Helping a Major Global Investment Bank Meet Demanding U.S. Regulatory Deadlines
Reconstructed Quantitative Models to Manage Risk for a $4B Mortgage-Backed Securities Portfolio in Record Time
Driving Revenue Growth by Optimizing the Customer Onboarding Experience
Driving Change and Creating Customer Value for a Wealth Manager’s HR Department through Integration, Process Design, and Culture
Addressing Employee Engagement and Implementing a Self-Sustainable Culture for Driving Continuous Improvement
Introducing a New Operating Model by Creating a Center of Excellence for a Global Wealth Manager
Doubling Efficiency for a Global Investment Manager through Report Automation and Increasing Client Engagement Using Data Visualization
Protecting Sensitive Client Data in Markets with Complex Regulatory Environments and Strict Data Privacy Rules
Delivering a New Identity for a Global Asset Manager and Refreshing the Brand in 3 Regions Across 22 Countries
Using Machine Learning Algorithms to Increase Sales Conversion Rates by 40% and Reduce Marketing Expenses by 20%
Using Natural Language Processing to Identify and Resolve Negative Online Feedback More Quickly
Our client faced a demanding timeline to conform its US operations to the requirements of Foreign Bank Enhanced Prudential Standards and needed a partner to help assess, design, execute, and test against a clearly defined critical path.
SCOPE
The effort required establishing a 22-person team to work across regions and functional groups and included the following critical activities:
Develop and define the client’s current operating model for 6 business work streams related to 8 US entities
Develop a clear critical path to drive conclusions on key business strategy decisions
Create a new front-to-back booking model and infrastructure
Create new target operating models and documented related requirements
Facilitate communications and buy-in with stakeholders on the new target operating models
Manage the cross-functional review and sign-off processes for 30+ proposed changes
OUTCOME
The additional expertise and resources enabled the client to meet its required regulatory deadlines, while delivering improved processes, controls and analytics to drive better decisions related to its funding costs.
The bank’s in-house mortgage analytic system had been effectively turned off for several years, consequently allowing the prepayment model and database to degrade. As a result, a growing buy-side investment business, desperately needing optimized models to manage risk, was surviving on an unreliable vendor system and a broken infrastructure.
SCOPE
With our subject matter expertise and commitment, our team achieved the following:
Tuned the prepayment model to recent data, as well as towards a predictive view of housing mobility
Repaired the mortgage database, comprising millions of rows of entries, to ensure proper integration and timely updates to feed the most accurate analytics
Produced evidence of the conceptual soundness and stability of the models to the governance committees within the framework of the Fed guidance SR 11-7 and the bank’s internal guidelines
Independently tested the entire analytic engine by replicating the results through millions of cash flow-discounting calculations via Monte Carlo simulations
Advised programmers how to build bug-free code by surgically finding and fixing subtle, analytical nuances
Influenced risk management to approve a practical, two-stage VaR/Stress solution with a viable present state and an innovative future state
OUTCOME
Within 4 months of initiating our quantitative mortgage services, we calibrated a new prepayment model and optimized it for a $4 billion mortgage-backed securities portfolio, gaining approval from the risk control and bank governance committees on the prepayment model, OAS model, and the entire analytic engine, ultimately deploying it to production within an expedited timeline. Moreover, while we managed the integration of this model into a previously decommissioned mortgage analytic system, we discovered and repaired all the discrepancies within the existing system. With renewed confidence in the Asset Liability Management group’s ability to manage risk through our reconstructed models, the bank began planning for its other entities’ reinvestment in such products.
To sustain revenue by retaining clients, this investment bank sought to improve customer satisfaction through optimization of the end-to-end client-onboarding experience.
SCOPE
Our work included the following:
Conduct workshops to develop an end-to-end customer on-boarding journey map that identified all touch points, involving stakeholders at each step
Survey existing customers to understand problems and frustrations and developed customer-service assessment tools to monitor ongoing customer satisfaction
Conduct a gap analysis of existing processes to identify sub-optimal operational and risk-management processes
Create a dashboard to monitor and track on-boarding status along each step of the journey
Define and develop comprehensive customer-service standards, SLAs, and new processes and procedures
Create, track, and evaluate onboarding metrics to root out inefficiencies and bottlenecks
OUTCOME
We created a streamlined customer-onboarding process that decreased throughput time, reduced errors and risks, lowered costs, and improved customer experience, which led to measurable increases in revenue.
A global wealth management bank’s HR department suffered from an inefficient operating model, fragmented infrastructure, and culturally siloed teams across multiple regions, which led to poor customer experience. We sought to improve the customer view by creating a ‘one HR’ culture, with global processes and standards that removed individual silos and integrated teams globally,
SCOPE
We sought to improve the customer view by creating a ‘one-HR’ culture, with global processes and standards that removed silos and integrated teams globally, by doing the following:
Coordinate and manage 36 projects across 10 locations globally using Target Operating Model, Value Stream Optimization and Kaizen methodologies
Align transformational process-redesign work around end-to-end customer journeys to ensure quantifiable value creation goals were met
Build the capability of the HR teams to ensure self-sufficiency of process excellence (PEX) techniques and sustainability of the change
Train 1,000 staff on performance excellence and to use visual-management, data, and root-cause problem solving techniques to identify and eliminate waste and non-value add activity
OUTCOME
Customer engagement increased by 15%. Staff engagement increased by 20% and operating costs were reduced by 30%. Twenty senior managers were mentored, and forty internal Lean champions were trained to deliver execution strategy and operational excellence, which empowered them to identify opportunities, deliver solutions, and create a continuous-improvement environment of sustainable change.
A large credit card company wanted to drive change and transform their business with existing resources and technology, so an Operational Excellence program was implemented to improve employee engagement and to develop a culture of continuous improvement, which enhanced client experience.
SCOPE
The following are the key activities for the initiative:
Establish 6 streams: Customer, Process, Performance Management, Organization and Skills, Mindsets and Behaviors, and Sustain
Identify the customer base, collect customer satisfaction data, demand expectations and opportunities, leading to the development of 5 Key Performance Indicators (KPIs)
Map 16 key value streams and assessed efficiency opportunities/waste removal
Design the future state and agreed on first-wave quick wins for early adoption
Introduce Visual Management for 135 FTEs, focusing on KPIs, short-term improvements and capacity
Redesign the operating model, with a focus on building value maps, team capabilities, and KPIs
Train 140 people on Lean principles, waste identification and elimination, and leadership skills
OUTCOME
Customer Net Promotor Score increased by 6%. Staff engagement increased by 11% and operating costs were reduced by 14% in less than 16 weeks. The changes were sustained, and the business is now more client-focused, as it uses enhanced data and KPIs to ensure it continues to make operational improvements.
A global wealth manager created a center of excellence that could be used as the role model of operational excellence for several business streams, including performance and visual management, delivery management, and improvement management.
SCOPE
Introduce a new way of working by implementing 10 Lean standards across 3 key streams, Performance Management, Delivery Management, and Improvement Management, to ensure and sustain continuous operational improvements
Develop tailored training and coaching modules for colleagues to become certified change agents, equipped with the mindsets and skills needed to drive successful improvement efforts and build internal capabilities
OUTCOME
We delivered front-to-back and top-to-bottom transformation of working practices and increased the overall effectiveness of the center, as well as customer and staff engagement. We increased capacity by 15% and trained 1,200 colleagues in performance-excellence awareness, waste identification and elimination, and root cause problem solving. We also trained senior leaders to identify opportunities and deliver solutions to create and sustain a culture of continuous improvement.
An inordinate amount of time was spent on reporting by a business group, given a large dependency on external business functions to manually generate business-critical reports, which were created using SQL, then downloaded and emailed each day. This created a significant bottleneck which needed to be removed.
The organization also needed self-service access to, and insight from, customer data being housed in five separate data sources, so they could capitalize on customer sales and marketing opportunities.
SCOPE
Architect a golden source and universal-data model and multiple-application-plug-in capability for three regions
Automate the integration of sales and financial data from the CRM system, as well as web and email data from the cloud, into the internal big-data warehouse using API’s
Assess the best BI tools to deliver the right information to decision makers
Identify key areas for process re-engineering to eliminate downstream data-quality issues
Ensure user adoption of new tools by developing a program of online, recorded training modules and wiki’s for continuous learning
Define a 24/7, global support model for data reconciliation and error processing to ensure 95% accuracy of data in near-real time
OUTCOME
The Marketing Operations team went from spending 132 hours/week to only 66 hours/week on reporting by using a drag-and-drop BI tool to automate reporting and distribution. Capacity was freed up, and this enabled the redeployment of resources to higher value-add business activities.
An interactive visualization dashboard that plugged into the big-data warehouse gave decision makers on-demand access to the insights they needed to optimize KPIs, eliminating their dependency on other teams’ inefficient and manual reporting processes, while also improving confidence in the data.
An asset management company embarked on a multi-year initiative to implement a single, CRM instance across the globe and faced the complexities of implementing cloud solutions in highly regulated markets.
SCOPE
The initiative involved the Institutional and Retail businesses and encompassed all regions, including restrictive countries such as, Switzerland, Singapore, Korea, and Japan. The work included the following:
Establish a core group of local experts in the Risk, Oversight, Compliance, Technology, Legal, and Controls groups for each jurisdiction to guide requirements and get stakeholder buy-in
Assess various encryption, tokenization, data-security and segregation solutions, and customize the platform to meet specific local regulations
Obtain approval from local regulators (e.g., the Monetary Authority of Singapore) to implement cloud solutions
Create user-provisioning approval workflows and control-audit capabilities to monitor access to sensitive data and ensure continued compliance
Develop a roadmap to onboard each market as data privacy enhancements were completed and local market sign-off was provided
OUTCOME
Delivered global sales and marketing platforms and processes, which were compliant with PII-data-privacy regulations across all markets. By using a combination of standard business procedures and tokenization, encryption, and data segregation technologies, we obtained approval from regulatory authorities and local control parties to implement key customer-facing systems for each market on time and on budget.
The asset-management business of a multinational financial services company undertook a large rebrand and refresh initiative and sought a disciplined approach to unify and reposition the company’s brand globally, to deliver a consistent customer experience, and solidify the brand’s promise as a long-standing and sophisticated asset manager.
SCOPE
The branding initiative and refresh programs spanned multiple regions, countries, and markets in various languages, and included the following work:
Establish governance and steering committees of key stakeholders and influencers in each market to understand local nuances and create global alignment under a single-brand experience
Map customer experience and inventory all content and media in each market to identify inconsistencies in brand values, tone of voice, colors, typography, and imagery, and assess the level of effort to transition
Create a unified playbook of brand guidelines, centralize repository of templates, and image library, and create and deliver a global training program
Create Centers of Excellence in each region to manage the creation of shared content and to provide design and delivery services, where economies of scale were realized
Onboard users on to standardized technology platforms for mobile, marketing automation, content management, and websites in phases over a 4-year period to standardize and improve brand delivery
OUTCOME
The broader rebranding effort created a distinct and consistent global brand identity for the asset-management business. Additional brand refresh efforts provided consistent and cohesive customer experiences and better processes to support brand delivery.
A FinTech startup wanted to optimize their marketing spend and sales team’s activities, so we leveraged their database and implemented a K-Means Clustering algorithm to identify the highest priority customer segments, and implement next-best action, and next-best offer strategies.
SCOPE
The implementation of the predictive and marketing strategies included:
Collect and integrate raw customer data into an enterprise data warehouse from various sources, e.g., CRM, webinar registrants, third-party data, and sales data
Prepare and clean data to create training and test sets and to identify appropriate features to use for the algorithms
Identify key customer segments by using feature sets such as age, employment status, purchase history, and Income
Work with sales and marketing teams to craft a customized message and action for each segment based on priority and opportunity
OUTCOME
The start-up executed three separate outbound-call and email campaign strategies to more efficiently deploy resources in a targeted way. Marketing expenses were reduced by 20% and the sales conversion rate improved by 40%, from call-to-close.
A university received negative feedback on its campus facilities, including restaurants, cafes, and stores. By using data science to process unstructured text from online reviews on the university’s website, the university was able to automate the detection, escalation, and resolution of negative student feedback.
SCOPE
Development of the data analytics processes involved the following work:
Prepare online data by removing non-value add reviews and words in order to increase the efficiency of the algorithm, which was developed
Implement a natural language processing (NLP) algorithm using Python libraries to create a bag-of-features model
Use a classification algorithm to train the model and implement sentiment analysis that automatically triaged positive and negative reviews
Create a process and priority queue for ongoing handling of negative feedback to ensure it was addressed, within agreed upon SLAs
OUTCOME
During the first 6 months of implementation, the university was able to process over 2,000 reviews and identify 200 complaints, which required immediate action. The ability to react and address negative feedback more immediately helped to improve customer experience and led to a Net Promoter Score increase, for campus facilities, from 6 to 8.