 The insurance industry has many industry-specific components, including an ever growing range of product offers, and a multitude of distribution forms requiring the set-up of specific customer relationship management types. In order to differentiate, insurance companies must constantly innovate product and service offers, in terms of customer knowledge and distribution networks, all the while integrating front and back office functions.
In this world where customer relationships constantly evolve, insurance providers are also burdened
with numerous regulatory constraints, including Basel II and MIFID (both designed primarily for the banking sector),
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and Solvency II (requiring prudential risk management and surveillance), so as to act with greater transparency and more carefully manage risk. For over 10 years Soft Computing has helped some of the largest Insurance providers across all activity sectors, to develop and equip their Customer Knowledge strategy with up to date efficiency improvement and profitability objectives. Soft Computing adapts its savoir faire to its insurance clients’ culture and distribution practices (direct sales, salaried employees, agents, etc.) so as to bring them the value-added elements of our “Data into Results” strategy:
- Accompany clients with the implementation of customer relationship management systems:
The choice of customer relationship management systems and programs must take into account different product types, existing practices and network structures, while insuring fluidity between the different CRM components.
- Optimize long distance customer relations:
Internet tools and call centres have developed a larger and more important strategic role in customer acquisition and development. Guaranteeing high quality contact with customers and efficient order and request treatment has become key success factor for customer satisfaction,
- Use operational customer segmentation:
Building a customer scoring system allows a company to optimize the allocation of customer portfolios to specific agents and orient sales pressure in function of customer potential,
- Master the risk of customer attrition:
Over solicitation of customers by competitors requires companies to put in place or to optimize processes and tools designed to anticipate and follow the risk of customer attrition (scoring, data mining, attrition rules database, etc.),
- Develop relationship marketing:
Reinforcing a profitable and sustainable customer relationship is centred on strong incentives, and designed around the identification of differentiated marketing actions and levers, and the use of relational charts and diagrams (i.e. farming or nursing),
- Adapt portfolio management to each customer’s potential:
By setting up dashboards designed to facilitate the identification of progressive sales-activity margins; a customer management system that is network accessible, and favouring the sharing of best practice, that can be rapidly adopted by all users,
- Automat fraud detection:
Evolving statistical methods and identification criteria now allow us to generalize and diffuse expert knowledge concerning the detection of fraudulent acts, notably for fraudulent claims and transactions.
Selected Examples
- AGF:
Qualitative and quantitative studies on why insurance contracts are eventually signed.
- AXA:
Campaign management optimization.
- La Mondiale:
Database enrichment and qualification.
- Mondial Assistance:
Satisfaction barometers for beneficiaries of assistance services.
- A life insurance provider:
Re-built sales management system.
- A general insurance provider:
Developed sales force automation tools and built decisional systems (dashboards, customer segmentation, scoring systems and processes).
- A general and life insurance provider:
Implemented sales force automation tools (SIEBEL) for insurance activities and bank.
Main references
AGF, AVIVA, AXA, Azur GMF, Europ Assistance, FGAO, Fortis, Gamex, GE Capital Assurances, Generali, Groupama, La Mondiale, MACIF, MMA, Mondial Assistance, SMENO.
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