Cognine

Category: Finance

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Finance

Transforming Financial Operations Through Technology

Financial Operations Through Technology

Today, business and technology are inextricably linked. And keeping pace with the emerging technology landscape can be difficult for even the most tech-savvy leaders. This case study dives deep into the challenges faced by the client in terms of manual and time-consuming financial processes, lack of data insights, and increased risk of errors followed by describing the solutions provided by Cognine that enhanced the overall functional efficiency of the client. 

About Client: 

Client is an American financial technology company that creates and provides financial advisors with wealth management tools and products. Their flagship product is an advisory platform that integrates the services and software used by financial advisors in wealth management.

Problem Statement: 

  • Client receives the customer data related to transactions, accounts, open positions, and other financial data in various formats from custodians such as Pershing, TD Ameritrade, Schwab etc. which made it difficult to analyze, understand and reuse it.  

  • Client receives more than 100 GB of incremental data on daily basis on to their on-prem servers which has computing challenges.

  • Most of the reports and metrics were shown in a tabular format, which were not providing enough insights and were not supportive for decision making.

  • Ensuring data quality of the large sets of incremental data had become cumbersome and was affecting downstream systems. 

  • There were architectural issues causing latency in the conversion of raw data into customer consumable data. 

Solutions Provided by Cognine: 

  • Cognine provided a highly scalable and robust architecture that supports various file formats with different sizes & data volumes which automated and improved client’s financial workflows, real-time data visibility. 

  • The new multi-layer (staging, standardized, curated) and multi-tenant architecture supports ETL operations to run parallel and different teams can access data at different layers based on their needs.

  • An event driven micro services architecture ensured the data load into targets without delay. Implemented configurations at environment and object level, such that very minimal changes are needed during the deployment. 

  • Embedded Collibra DQ to monitor the DWH jobs and notify users based on the requirement. 

  • Cognine analyzed the business requirements for their analytical needs, designed data models and developed reports. Implemented CI/CD functionality for auto deployment processes. 

Technology Stack Used: 

Implementation: 

Benefits/Results: 

Improved Data Accuracy And Increased Productivity:

Cognine successfully automated Normalization of files through UI. With the help of React UI the user can upload file metadata information and download the Normalizer file. Previously, each Normalizer file required manual development. Post automation, using the new UI, users can develop up to 20 Normalizer files at one time which saved user’s time largely and boosted efficiency. 

Reduced Processing time:  

We introduced a centralized library for standard logging where we implemented logging format for different steps and saved them into CloudWatch. 

Quantitative Data Management:  

There was a huge scale-down on manual intervention on client-specific data extraction. 

Quick Decision Making:  

Data insights  fostered the client to take quick decisions based on the highly sophisticated visuals 

Conclusion: 

  • Data insights are helping the business to take quick decisions based on the highly sophisticated visuals.  

  • Manual intervention on client specific data extraction came down extensively as we were able to automate the functionalities. 

  • Automating the on-boarding & processing of new client requests was made as easy as just a click and go. This is helping to scale up client’s operations. The marketing team can utilize this to grab the attention of new prospects. 

  • Latency of accessing data from Analytical system has been reduced tremendously, it was scaled down to multi-folded level. 

  • The cost of the DWH layer has been reduced nearly half per month. This gave financial freedom to the business. 

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Finance

Unleashing the potential of Digital Assistants in Fintech

So, what’s the difference between Chatbots and Digital assistants?

There are disruptive technologies that have positively impacted fintech, but none of them has revolutionized the financial world quite like smart AI, chatbots, and voice-enabled digital assistants. 

In making key financial decisions, the presence of a digital assistant through conversational AI enhances customer intimacy while optimizing costs & revenue to a large extent.

Digital assistants help FinTech companies to collect and process a large volume of information about customers’ needs, requirements, past transaction history, etc. They offer extremely personalised information about customers. With the detailed set of data, FinTech companies can easily amplify and automate operational performance.

Functions like analytics, billing, collections, renewals, upselling, and cross-selling of services are automated and organised in such a way that the personnel can rely on the digital assistants completely.

While both chatbots and digital assistants help in performing tasks as instructed and answering questions, chatbots are limited to making a conversation, making recommendations, and checking on statuses. 

Digital assistants use AI to understand customers’ speech and text and have the ability to understand complex questions and even localized slang. Digital Assistants can also advise the right service or product to the consumer based on the customer’s emotional sentiment.

Which digital assistant do I need?

Adopting a digital assistant won’t solve all of your company’s problems or reduce expenditures. A crucial factor to take into account is redefining organizational process trouble spots, using a step-by-step analysis process, knowing what you need from your digital assistants, and tailoring them to meet those demands are the key points to consider.

The best digital assistant for you will depend on your needs and the scorecard, which you should create. A custom-designed digital assistant might be the solution in many cases. 

Increase the ROI:

Digital Assistants bring a great ROI to any organization by cutting costs and time while providing great customer satisfaction. They also help in 

Sales, marketing-offering new products and promoting new services, lead generation, and an overall reduction in the company costs and increase in ROI. Here is a brief comparison:

Wrapping up

Digital assistant technology is opening-up an overwhelming world of innovation, optimization, and opportunity. If you are lost in translating how this technology shift could open new opportunities and transform their business model, let us TALK!

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