Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Research Article: 2022 Vol: 26 Issue: 1

How Cognitive Automation of Marketing Activities can Transform the Processes of A Financial Institution

Jensolin J, Central University of Tamil Nadu

Preeti R Gotmare, Central University of Tamil Nadu

Citation Information: Jensolin, J.,& Gotmare, P.R. (2022). How cognitive automation of marketing activities can transform the processes of a financial institution. Academy of Marketing Studies Journal, 26(S2), 1-3.

In order to combat the effect and achieve profitability in an ever changing business environment influenced by low interest rates, cut-throat competition, market overcapacity and mounting regulatory regimes (such as ASC 606 in the US and IFRS in EU), financial organizations bank on automation (Madakam et al., 2019). Robotic process automation (RPA) has been an effective cost cutting measure. While on a journey to embark on digital transformation, organization encounter tumbling blocks such as legacy infrastructure and lack of automation with about 20% of data stored in an organization is structured stored in spreadsheets, CSV files or databases; while 80% is either semi structured or unstructured comprising of invoices, purchase orders, contracts, mortgage apps, emails, instant messaging, voice, images or videos. These have resulted in budding of cognitive automation (Weyer et al., 2015).

Cognitive Automation (CA) – What is it?

The evolution of RPA occurred in four folds. Cognitive Automation falls under RPA 4.0 wave with greater technology advancements and high business impact and is rarely prevalent in the market. Cognitive RPA (Robotic Process Automation) is a knowledge based rather rule based automation method that leverages Artificial Intelligence (AI) technologies , fuzzy logic, machine learning (ML), and text analytics to bring in human like behavior (judgment and prioritization) in decision making that can work well to process data that are non-standardized, semi-structured and unstructured. Through cognitive automation, firms can radically bringing in change in their straight through processing aided by bots and applications without human involvement.

Cognitive Automation – Why is it used?

Cognitive automation has a few compelling benefits due to which it is sought after. They include:

1. Fast realization on RPA investment which could result in headcount savings from 10-25%.

2. Faster implementation which could be 3-4 weeks for proof of value and 3-4 months for deployment.

3. Higher accuracy and reliability where RPA error rate could be zero.

4. Improved customer experience because employees can focus on value addition on their roles, thereby resulting in enhanced customer experience.

Embracing Disruption - How Does CA Transform the Financial Services Value Chain and Marketing Activities?

RPA along with AI/ML, Application programming interface (API), Blockchain and data analytics help organizations implement cognitive automation in financial services sector.

In the banking value chain, CA finds its application in core processes such as marketing and sales contributing to customer profiling, potential customer identification, customer demand management and precision marketing; AI credit rating, automatic data review under risk management and review processes; and automatic report generation, voice and image recognition and customer service robots under Customer management and services processes (Koltai et al., 2017).

While in the insurance value chain, CA finds its application predominantly in front end marketing under cross/up selling, churn prediction; user behavior evaluation & property status testing, underwriting automation, client request transfer, smart customer satisfaction recognition, remote claim investigation, fraud detection and claims forecasting under underwriting, policy management and claims processes; in addition to portfolio management and reinsurance advice under back-end asset management (Kolbeinsson et al, 2017).

Roadmap To Implementation - How Can Financial Firms Adopt CA?

An organization that plans to adopt CA can conduct a thorough current state assessment to how an activity/process is taking place currently, time duration for completion, bottlenecks, areas of improvement, identify those activities that can be automated and decide upon the most efficient, quick and cost effective method for implementation (Mattsson et al., 2018). While the next step would be to identify and map processes based on complexity of automation. Following which, the firm can choose a technology implementation partner for a hassle free role out after which a pilot program can be run to check the success of automation and then carry on with the automation of the entire processes and scaling up.

Top Technology Implementation Partners In the Market

The ecosystem of RPA technology supplier involves three partners such as service providers like Infosys, TCS, Wipro, HCL, EXL, Mphasis, Hexaware etc., ; technology vendors like Automation Anywhere, Blueprism, UiPath, OpenSpan, Celaton, Antworks, AutomationEdge etc., who feature in the Gartner magic quadrant and technology integrators like Virtual Operations, Symphony, genFour to name a few (Fasth‐Berglund, and Stahre, 2013). Leading platforms and products available from the Indian IT service providers are Dryice by HCL, Tron by NIIT, Mana and AssistEdge by Infosys, Ignio by TCS, Holmes by Wipro SyntBots by Atos & Syntel to name a few.

Success story – An example of CA implementation

Implementation of AutomationEdge in HDFC Life for processes such as quote generation, payouts which resulted in massive reduction of manual errors with robots handling circa 2,000 cases per day; drastically reducing turnaround time from 3 days to few minutes for quote generation and from 7 days to 2 days for payout (Tsujii et al., 2009).

Conclusion

Cognitive automation can help in quick turnaround. The steps are current state assessment, next identify and map processes based on complexity of automation. Next, choose a technology implementation partner and conduct a pilot program to check the success of automation and finally automation of the entire processes and scaling up.

References

Fasth‐Berglund, Å., & Stahre, J. (2013), "Cognitive automation strategy for reconfigurable and sustainable assembly systems", Assembly Automation, 33(3), 294-303.

Kolbeinsson, A, Lindblom, J, & Thorvald, P. (2017). Missing mediated interruptions in manual assembly: Critical aspects of breakpoint selection. Applied Ergonomics, 61, 90-101.

Koltai, T., & Kalló, N. (2017). Analysis of the effect of learning on the throughput-time in simple assembly lines. Computers & Industrial Engineering.

Madakam, S., M. Holmukhe, R., & Kumar Jaiswal, D. (2019). The Future Digital Work Force: Robotic Process Automation (RPA). Journal of Information Systems and Technology Management, 16.

Mattsson, S., Fast-Berglund, Å., Li, D., & Thorvald, P. (2018). Forming a cognitive automation strategy for Operator 4.0 in complex assembly. Computers & Industrial Engineering.

Tsujii, T., & Watanabe, S. (2009). Neural correlates of dual-task effect on belief-bias syllogistic reasoning: A near-infrared spectroscopy study. Brain Research, 1287(0), 118-125.

Weyer, S., Schmitt, M., Ohmer, M., & Gorecky, D. (2015). Towards Industry 4.0 - Standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC-PapersOnLine, 48(3), 579-584.

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