Symphony Marketing Solutions

Industries | Financial Services

The fast-paced environment of financial services is rife with mergers, globalization, increased competition, and new regulatory requirements -- radically altering the financial services business and challenging the ability of financial service providers to maintain a strong, reliable brand in their marketplace. Symphony Marketing Solutions helps financial services firms maximize customer value and minimize risk in every interaction through every channel. Our data solutions ensure accuracy and quality of your information, while our analytics make it possible to leverage the distinct multi-channel nature of the financial services business, the tremendous volumes of data available, and the many points of interaction with the marketplace.

At Symphony Marketing Solutions, we help our Financial Services clients take on their marketplace challenges by providing accurate, timely and actionable marketing insights that aid in designing and implementing effective marketing programs and campaigns to establish and sustain a profitable, loyal and satisfied customer base.

Analytics Landscape: Retail/Consumer Finance
Retail/Consumer financial services includes of “secured” credit products such as Mortgage, Home Equity Loans, Auto Loans and White Goods Loans; as well as “unsecured” credit products including Credit Cards and Personal Loans.

SMS Analytics improve decision making at each stage of the credit product management life cycle, and provides insights into the portfolio health of products throughout the credit products’ lifecycle as well.

Financial Services Product Lifecycle Continuum
Product Planning -> Origination/Acquisition -> Account Management -> Collection -> Write-off.

Our Analytics Solutions and Services for the Financial Services companies include:

Sales and Marketing

Response Modeling: With the continuous pressure of low response rate and high account origination costs, targeting the right customers is the only way to improve both. A good Response Model will help focus your campaigns while reducing origination costs.
Prospect Segmentation: The segmentation technique is useful in identifying prospect customer groups for product solicitation. This service will optimize your marketing spend and improves profits by lowering acquisition costs.
Campaign Management: Develop and deploy multiple-channel marketing campaigns to target groups or individuals and track the effect of those campaigns, by customer segment, over time.
Channel Optimization: Channel optimization balances delivery of a good customer experience with the ability to better control costs. Based on data derived from a thorough needs assessment, it can help reduce costs while increasing service quality and customer loyalty.
Cross Sale/Up Sale: Identify existing customers and offer another product to increase customer relationship.
LTV Modeling: Prediction of Customers Life Time Value using profitability and attrition probability.
Attrition Modeling: We generate a model to help identify probable attrition and provide guidance for retaining profitable customers.

Credit Risk Management Analytics

Credit Scoring (Origination and account management): Credit scoring uses statistical techniques to estimate and rank order the repayment capability of potential customers or the activity of current customers.
LGD Modeling (Basel II Accord): Do we need to know only probability of default or how the portfolio is impacted from the default account? Loss Given Default (LGD) is used to estimate the lifetime loss from any particular customer. LGD= probability of Default * Exposure at default.
Credit Risk Underwriting: Develop policy based on credit score and other risk parameters (Credit history and collateral quality) to maintain portfolio bad rate at tolerance level and also to help grow business.
Risk Based Pricing: A flat price/interest rate for every body or pricing based on risk? Risk based pricing helps acquiring and retaining good customers and at the same time it allows the company to recover maximum from a high risk customers by charging high price. This also acts as an indirect deterrent to the high risk customers.
Fraud Detection: Develop model and policies to identify and decline fraudulent credit applications.
Loss Forecasting: Traditional Methodologies – Net Flow Rates, Vintage Loss Curves and Score Distribution. Macro economic variables also impact default rate/loss rate. A time series model is also used for long term forecasting.
Credit Line Management Strategy: This can be proactive or reactive. At every cycle providers review the credit worthiness of an account and increase or decrease credit line as required. This can also help improve customer relationships.
Authorization Strategy: Should we allow everybody to do over-limit transactions? Should delinquent customers be allowed to do further transactions? Having a robust authorization policy in place will help address these questions.
Collection Strategy: When should we start collection activity? How do you use your limited customer service team effectively? Is it required to call everybody manually or is a dialer enough to address a specific group of customers?
Score Validation: Is the score still performing as expected? Changes in economic factors might cause a population shift, which will eventually impact the performance of the existing score card. Regular score tracking and validation is required to identify the need for redevelopment of scores.