Driving Financial Service Excellence through Dynamic Decisioning & Analytics

Forward-thinking financial services organizations are increasingly using sophisticated tools to upgrade the end customer experience at various points in the customer journey. 

Banks and insurers have focused most often on lifecycle touchpoints such as new customer acquisition, account remediation, and promoting add-on products and services. 

In order to capture the full business value of their efforts, financial services firms need to take a more holistic view of transformation. They need to ensure that they are covering the entire customer lifecycle, and that the effort encompasses the entire organization. Only then can they become truly connected, agile, and resilient. 

We often see two key errors that need to be addressed in order to move forward and make dynamic decisioning and analytics the force for change that can drive true organizational excellence. 

Incremental Improvements to Old-School Decisioning 

Customer decisioning has evolved but not made quantum advances for several decades, relying on a mix of credit scoring, other analytical and statistical methodologies, and proprietary algorithms. 

Insurers and banks are tempted to incrementally adjust or tweak these standardized methodologies, in the hopes of gaining significant improvements with minimal investment. In the end, though, they all fall far short of the personalization and timely offer-making capabilities that consumers have come to expect from other modern businesses, such as online retail. 

Segmenting the Customer Lifecycle 

When many insurers and banks first moved beyond the practices prevalent in the late 20th century, they typically chose a portion of the consumer lifecycle that they deemed to be of the highest strategic value. 

For example, an insurer focused on consumer acquisition may choose to automate the rating and pricing functions first. Banks focused on cleaning up their loan portfolios may implement analytics in account monitoring and collections. 

These moves represent positive first steps toward improving internal operations and consumer engagement. 

However, these efforts often become mired in difficulties with unruly, siloed data and disconnected operations. Different functions across the organization may be at odds about priorities, such as what portion of the consumer lifecycle deserves the most attention first. 

By focusing efforts on discrete events or phases in the customer lifecycle, financial services organizations are not capturing the full potential of consumer engagement, and are not providing the holistic, connected experience consumers expect. In fact, by segmenting the customer lifecycle, they often perpetuate the disconnected consumer experience they set out to improve. 

A Vision for the Future – Enabling What’s Next

In order to capture the full advantages of modern technology, insurers and banks need to think more holistically. To do this, they must think and implement holistically in two important dimensions: 

Across the Entire Customer Journey 

Customers and prospects have become accustomed to attentiveness from the first exploratory contact to the deepest long-term engagement. Online retail in particular is often held up as the benchmark, with remarks such as “just make it like Amazon” an indication of how high the bar has been set. 

Across the Entire Organization 

In order to bring excellence to the customer journey, organizations must also break down organizational barriers and traditional ownership models. Functions such as marketing, underwriting, credit analysis, and account services must work in concert to own a connected, unified customer journey. 

All levels of the organization across all operating units must have access to the most sophisticated tools and applications possible, in order to execute on the mandate of delivering the best possible consumer engagement. 

Enter Dynamic Decisioning and Analytics 

In today’s world, forward-thinking insurers and banks have access to dynamic decisioning and analysis tools and technology of the highest order. 

Here are the benefits that these capabilities bring to the table: 

Integrating New and Existing Datasets in Real Time 

Insufficient data, bad data, missing data, outdated data, duplicate data. 

Every organization wrestles with these issues, and these maladies stand in the way of sound analysis and decision-making, including the use of artificial intelligence (AI) and machine learning (ML). 

The crucial first step of corralling and integrating internal and external datasets removes the data nightmare that all organizations face, and ensures that data flowing into data stores in the future can be captured and incorporated seamlessly. 

Driving Smarter Decisions and Achieving Organizational Alignment 

When dynamic decisioning and analytics are infused into every application across the organization, and made available to all levels of the firm, smarter operational decisions become automatic. The technology allows organizations to identify, implement, and monitor strategic initiatives more confidently, while reducing the manual effort needed to manage daily performance. 

Achieving Strategic Outcomes Cost-Effectively 

When approached systematically, and employing the right technology, dynamic decisioning and analytics enable clear-eyed visibility and insight into all operations, allowing for the monitoring and tracking of strategic initiatives with minimal manual effort. 

Product-level implementations can be monitored automatically in real time, and adjustments made on a timely basis, to keep pace with changes in the industry, market conditions, and competition. In turn, keeping manual effort to a minimum helps rein in costs and frees up financial resources for strategic priorities. 

The Path Forward – A Solution Roadmap

 

In order to achieve these objectives, there are four key components that make up a full suite of dynamic decisioning and analytics functionality: 

Dynamic Pricing 

Look for an AI-driven enterprise-scale rating and pricing engine that operationalizes advanced analytics, and builds in robust control and governance standards across the organization, allowing you to instantly deploy pricing to online channels, to serve up to millions of quotes and offers per day, and to leverage those digital channels in real time. 

Personalization 

Your next solution needs to deliver a new level of personalized insurance and banking consumer experiences, to better serve diverse audiences, implement new market/product strategies in real time, and build a more relevant, value-adding organization. 

Usage-based Insurance (UBI) and Telematics 

In the insurance space, usage-based and telematics insurance are revolutionizing the way business is done and how consumers are treated to highly-personalized experiences. 

This means that a leading-edge telematics app is required, one that collects robust data around braking, acceleration, distraction, speed, cornering, and other real-world driving events, then uses ML to generate predictive scoring algorithms. 

World-Class Consumer Engagement 

Timing is critical to capturing consumer attention and incremental business throughout the customer lifecycle. A key ingredient in your future is software that delivers prices, personalization, and communications to consumers at the optimal time and through the optimal communication channels. 

Wherever you are in your quest to make your organization a leader now and in the future, Earnix can help you apply dynamic decisioning as well as banking and insurance analytics to make the transition faster and the competitive advantages lasting.  

Discover even more about Dynamic Decisioning by downloading the eBook today. 

The post Driving Financial Service Excellence through Dynamic Decisioning & Analytics appeared first on Earnix Blog.

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