Industry
Banking
Banking Services Transformation: Unlocking Exponential Value
Highlights
- In the recent past, the service desk industry has become highly competitive due to developments in world of digital transformation, evolving customer needs and constant innovation.
- It is now imperative for service providers to charge the customer only for the service that has been consumed.
- The critical need is for a tailored pricing model which takes into consideration coverage window requirements; revenue predictability for service providers; budgetary challenges of clients; and, value driven pricing, which differentiates the provider from other competitors.
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Current landscape
Pricing in the service desk industry has shifted from traditional FTEs to outcome-based models in recent years, to better align costs with business value and client KPIs. The adoption remains limited due to risk and operational factors. GenAI can enable this shift by intelligent automation, predictive demand management, and proactive SLA governance.
Pricing Evolution
The evolution of pricing models and the challenges faced by outcome based models.
In the late 1990s and early 2000s, IT Service desk pricing was centered primarily on FTE deployments and clients used to eventually pay for resource availability rather than parameters such as service quality, SLA adherence, automation or productivity, which in turn resulted in limited performance related incentives.
In the next phase, the shift was to a ticket-wise tier pricing where billing reflected actual efforts. This approach gained popularity as it aligned more closely with clients’ service consumption patterns. This model also faced challenges due to varied ticket types, each differing in SLA, effort and skill, which means there was a requirement for complicated multiple rate structures. Additionally, the ticket volumes fluctuated due to seasonality and market factors so for service providers, the low volume scenarios could not cover fixed costs, and the high-volume scenarios stretched their service capacity. These resulting complexities made it difficult to sustain this model and occasionally led to fairness concerns.
The shift to a user/application-based fixed rate model in later years resulted in simplification of the billing process and improved cost predictability but still lacked alignment with client preferred outcome driven approach. In the late 2010s, a hybrid model emerged which combined the features of user/application and ticket-based pricing models but the day-to-day challenges in practically managing this became a deterrent in further adoption.
The latest evolution is the outcome-based model where pricing is aligning with client defined KPIs and SLAs such as resolution quality and response time which were then directly linked to business outcome parameters such as improved customer service and faster uptime.
Challenges
Key challenges in implementing outcome-based pricing models in the service desk industry.
Even though outcome-based pricing is universally preferred by clients due to its alignment with business performance criteria, there are multiple challenges associated with it. The service provider must bear more risks since the outcome can also be influenced by other factors such as technology, business priorities, and processes which cannot be controlled by the provider.
The dependency on third party entities and downstream partners may also influence SLA performance. The model will be difficult to implement for new engagements since it will be challenging to forecast performance due to lack of baseline data. Contacts made via mediums such as emails, chats etc. will be in an unstructured format and it will be challenging to track/measure the data and assign an effort.
From a client perspective, the service provider may compromise on quality to meet outcomes, so a thorough due diligence of the contract terms needs to be done to ensure comprehensiveness and flexibility in performance parameters.
Solution
GenAI tools to enable pricing model.
Multiple banks and financial institutions have introduced automation related drivers in their service desk operations, but it is felt that this approach alone is not sufficient to meet the pace of transformation hitting the industry. To revolutionize this, the service desk industry must pivot towards Agentic AI/GenAI strategies that enable end-to-end transformations with cognitive intelligence and manage the operational challenges with agility.
Some of the use cases that can be deployed to modernize service desk operations will be:
Volume forecasting and demand management: GenAI can predict demand in volumes by analyzing historical ticket data, product launches, software updates, and seasonal trends. It can continuously learn from live data and make necessary adjustments to forecasts.
Billing and invoicing: Direct integration between GenAI tools with the client’s financial systems will assist in the generation of real time data for billing models. This will align revenue with actual consumption patterns of the service desk. Anomaly detection in billing can thereafter flag duplicate entries or billing errors.
Classification based on complexity: Using natural language capabilities, GenAI models can identify ticket complexity basis the keywords and the sentiments mentioned in the ticket, email or voice call. It can predict complexity based on time needed for resolution, frequency of escalation etc.
SLA management: In an outcome-based pricing scenario where meeting SLAs is the top priority, GenAI models can predict the occurrences of SLA breaches by analysis of historical incident data, logs etc. and allocate resources to ensure proactive escalation. Gen AI can monitor SLA adherence across thousands of tickets and generate summaries.
TCS Advantage
TCS contributes to business growth by designing tailored outcome-based solutions.
The success of outcome-based solutions is dependent on the tailoring a pointed solution that is aimed at meeting business objectives. By partnering with the right technology and domain stakeholders. TCS with its global IT expertise, GenAI and innovation capabilities, can create a niche space and stand out in the overcrowded market by developing strategic pricing models.. that are aimed at result-oriented commercial models, and optimized delivery frameworks. In turn these will create ripple benefits by building greater client trust and improving business opportunities.