A3S - Industries

Most industries working with large amounts of data have recognized the value of machine learning technology. Various research reports show that companies using machine learning and AI for decision making are substantially (over 50%) more profitable compared to the ones that don’t. By gleaning insights from this data – often in real time – organizations are able to work more efficiently or gain an advantage over competitors.

Banking (Financial sector).

The time has come for financial institutions to accelerate the transformation into more strategically focused, technologically modern, and operationally agile organizations, so that they may remain dominant in a rapidly evolving ecosystem.

Most of them grapple with multiple challenges such as complex and diverging regulations, legacy systems, disruptive models and technologies, new competitors, and finally, an often restive customer base with ever-higher expectations. In most cases, machine learning and AI serve as central components to resolving the issues more efficiently and effectively.

We will help you in the following areas:

  • Customer Analytics: help improve the outcome of customer interactions both online and offline by leveraging machine learning and AI so that every customer interaction is guided by analytic insight? These enable to predict customer product and channel preferences (next-best action programs), likely customer behaviours (retention strategies), expected spend and lifetime value. Furthermore, data is used to profile customers in order to determine behaviour segments, derive NPS as loyalty/recommendation likelihood, or estimate customer sentiment from social media.
  • Credit Risk and Credit Decisioning: help reduce time to market for advanced IRB (PD, LGD, CCF) models, minimize default rates and make the right decisions (in real-time) while ensuring governance and transparency of the entire scoring and decisioning process.
  • Enterprise Analytics: in order to fully deliver the expected business value we can help you bring machine learning and AI across the organization and support the complete lifecycle from discovery to build to monitoring and deployment to production in any diverse business context. In this way, you will be able to reduce CAPEX investments, decrease TCO of multiple analytical platforms, reduce operational risk and shorten time to market.
  • Fraud (payment, online, card): use machine learning to help with customer risk ranking/profiling that are at risk to be involved and highlight those potentially involved in fraud, money laundering, sanctions, etc. thus bring efficiency to operational resources with AI and protect company reputation and keep customer satisfaction high through better management of false positives.
  • Personal Assistants and Chatbots: is a form of AI, where a software algorithm takes natural language input from a customer via text or voice, processes it, and gives an answer. It can replace menu-driven IVR on the telephone to provide a better customer experience, or it can handle simple to complex queries without human involvement, thereby increasing efficiency. If you want a chatbot that can answer, apart from simple queries like “What is my current account balance”, also more sophisticated ones, combining disparate sources of available data, like, “Tell me how much I spent at restaurants last month!”, we will be happy to help.
  • Call Center Analytics
    • Call Center Text Analytics: analyze and monitor all incoming emails, social media posts, complaints, call center transcripts and chatbot logs. Analyzing unstructured data may give you several insights. From a customer perspective, you can estimate his/hers loyalty, satisfaction, and sentiment scores.  From the operational perspective, you can precisely identify call reasons, create dynamic topic categorizations, follow topic trends through time and spot emerging issues in real-time. This is vital in seeing any potential issues through the customer lens.
    • Call Center Workforce Planning and Optimization: Do you want to decrease waiting time and FCR rates while increasing customer satisfaction and loyalty? Or, do you want to know how many agents with particular skills will be needed in next time slot? Or, how will your new product rollout affect call volume on weekends? Or, what will this change to your fee structure do to your customer satisfaction score? Using in-depth review of past performance in areas as diverse as call volume, service level, handle time, marketing events, system/network failures, and customer satisfaction, machine learning makes it possible to predict future workforce needs. By analyzing past behaviour, companies can plan and strategize for the future.
  • Human Resources Analytics (HR analytics) is a systematic identification and quantification of the people drivers of business outcomes. It enables HR professionals to make data-driven decisions and helps to test the effectiveness of HR policies and different interventions. Do you want to measure turnover, understand its causes and design programs to control it to reduce vacancy posts and avoid their effects on business performance?
  • Blockchain analytics is improving operational processes and safer business implementation has brought us closer to blockchain technology. A new age mechanism that enhanced the privacy protection, moved the barrier from paper to electronic and open the door to easy-use access, making the collaboration with companies all around the world even more authentic and possible. Implementing this type of technology in your work ethics, can affect your business income and market competitiveness, by increasing both and help you answer crucial questions like: who can I trust to make business with? How reliable is my business partner? Are the products that I’m trying to reach authentic? Can I safely sign a document and not worry about privacy that can be tampered with by malicious actors?

Our goal is to provide these services at your request and desire, shaping them in the frame that your vision brings.

Telecommunications.

With the help of the machine learning systems, we manage to break the resembling features that churn and non-churn customers have. Our company got involved in developing, implementing and deploying models  for churn prediction for broadband and mobile customers in the Adriatic region.

We have developed a various models and campaign for pre-paid users, including also required processes such as documentation, campaign preparation and results tracking.

Retail.

By developing models for up-sale and cross-sale marketing campaigns, our company assured its place in the retail and FMCG industry. Many of the projects that we have encountered, included analysing a big amount of data that help our clients conclude what is the closest to their customer wish and requirement.

Our way of giving answer to questions related to preferability of products and services, discovered criteria by which business will guarantee certain degree of success to retail clients involved in this decision making process.

Public.

Areas:

  •     Forecasting, Planning and Optimization
  •     SNA/CLA

No matter where your business is on its digital transformation journey, our key capabilities can effectively help you shape the Analytical platform around your customer needs and become the analytically-driven company that you deserve to be.