Published by Gbaf News
Posted on December 7, 2016
12 min readLast updated: January 22, 2026
By Ashoke Dutt
Banks have always had to manage large amounts of critical data. Yet, in spite of the buzz around the value of “big data”, most frontline employees in mid-tier and smaller banks still lack direct access to timely and relevant data insights.
Ashoke Dutt
Traditionally, data analytics has been seen as a back-office function that utilizes expensive,complex business intelligence solutions and requires a level of IT support often out of reach for smaller institutions. But not anymore.
Thanks to innovative, new “decision management technologies”, smaller banks — without large IT staffs — can transform how their less tech-savvy employees work with data and get the same kinds of actionable insights as larger banks.
As the banking industry becomes increasingly complex, these new cutting edge data technologies help mid-tier and smaller banks mitigate risk and fraudulent activity and create more compliant environments. And, they provide real time metrics to improve customer service and enhance product development — all at a fraction of the cost.
Struggles With Traditional Data Analytics
Many mid-tier and smaller banks struggle with basic customer and business analytics because they cannot afford traditional data management platforms that are expensive, highly technical, and often in compatible with their existing infrastructure. Built for power users who routinely prep, collate, extract and compile data and reports, these platforms are difficult and time consuming for nontechnical employees — even after training.
Unfortunately, these barriers prevent frontline employees and their managers from having direct access to information that is critical to timely business decisions and customer response. Prompt responses to regulators is also of particular importance to smaller banks since they are often subject to as much, if not more, regulatory scrutiny than larger banks.
New decision management solution stake aim at all of these challenges. Most are highly “self-service” in nature, low maintenance and do not require expensive technical consultants to get work done. They empower smaller players to be more nimble, competitive and satisfy their employees’ growing need to access information.
How It Works: Conversations with Data
Today’s decision management platforms use technologies like artificial intelligence, machine learning and cognitive search to perform simple vocabulary-based data analysis. What this means is that non-technical users can perform their own analytics by simply typing questions like “How many customers with more than one account take advantage of special perks for having multiple accounts?” into a familiar, Google-like search bar. Within seconds (not minutes!) the platform responds by generating a customized report of real time, authenticated data in easy-to-understand formats.
Business users in every corner of the organization can become their own data analyst, engaging and collaborating in real time data exploration to investigate business hunches, increase efficiencies, share insights and information,maximize returns and minimize risk exposures. Here are just a few ways teams can benefit:
Considering the latest advancements in data analytics, there is no reason why mid-tier banks still need to rely on yesterday’s expensive, complex technologies and deny their business users access to the kinds of actionable data insights that benefit larger banks.
Ready to take the Plunge? Avoid the Pitfalls
In order to insure your organization gets the long term value it deserves from a decision management solution, make data analytics a part of your corporate DNA. This means getting top management involved as well as line-of-business managers.
Let’s take a look at some basic things to keep in mind:
Data has always played a critical role in day-to-day bank operations and solving business problems. Until recently, most mid-tier and smaller bank employees have missed out on the benefits of direct and prompt access to big data. But now, thanks to the growing and evolving world of data technologies, smaller financial institutions finally have the opportunity to level the playing field.
About the Author:
Ashoke Dutt is the CEO of Semantify, a pioneering semantic search technology platform company based in Chicago, Illinois. His career in global financial services spans more than 30 years and includes the launch of India’s first credit card business in 1989 at Citibank. Dutt went on to assume various other leadership roles at Citibank, including EVP, International Cards. He also served at Morgan Stanley (EVP, International Retail), and Discover Card (EVP, Marketing). Today, Dutt is an active entrepreneur and investor, serving as on boards of various start-ups and philanthropic organizations.
By Ashoke Dutt
Banks have always had to manage large amounts of critical data. Yet, in spite of the buzz around the value of “big data”, most frontline employees in mid-tier and smaller banks still lack direct access to timely and relevant data insights.
Ashoke Dutt
Traditionally, data analytics has been seen as a back-office function that utilizes expensive,complex business intelligence solutions and requires a level of IT support often out of reach for smaller institutions. But not anymore.
Thanks to innovative, new “decision management technologies”, smaller banks — without large IT staffs — can transform how their less tech-savvy employees work with data and get the same kinds of actionable insights as larger banks.
As the banking industry becomes increasingly complex, these new cutting edge data technologies help mid-tier and smaller banks mitigate risk and fraudulent activity and create more compliant environments. And, they provide real time metrics to improve customer service and enhance product development — all at a fraction of the cost.
Struggles With Traditional Data Analytics
Many mid-tier and smaller banks struggle with basic customer and business analytics because they cannot afford traditional data management platforms that are expensive, highly technical, and often in compatible with their existing infrastructure. Built for power users who routinely prep, collate, extract and compile data and reports, these platforms are difficult and time consuming for nontechnical employees — even after training.
Unfortunately, these barriers prevent frontline employees and their managers from having direct access to information that is critical to timely business decisions and customer response. Prompt responses to regulators is also of particular importance to smaller banks since they are often subject to as much, if not more, regulatory scrutiny than larger banks.
New decision management solution stake aim at all of these challenges. Most are highly “self-service” in nature, low maintenance and do not require expensive technical consultants to get work done. They empower smaller players to be more nimble, competitive and satisfy their employees’ growing need to access information.
How It Works: Conversations with Data
Today’s decision management platforms use technologies like artificial intelligence, machine learning and cognitive search to perform simple vocabulary-based data analysis. What this means is that non-technical users can perform their own analytics by simply typing questions like “How many customers with more than one account take advantage of special perks for having multiple accounts?” into a familiar, Google-like search bar. Within seconds (not minutes!) the platform responds by generating a customized report of real time, authenticated data in easy-to-understand formats.
Business users in every corner of the organization can become their own data analyst, engaging and collaborating in real time data exploration to investigate business hunches, increase efficiencies, share insights and information,maximize returns and minimize risk exposures. Here are just a few ways teams can benefit:
Considering the latest advancements in data analytics, there is no reason why mid-tier banks still need to rely on yesterday’s expensive, complex technologies and deny their business users access to the kinds of actionable data insights that benefit larger banks.
Ready to take the Plunge? Avoid the Pitfalls
In order to insure your organization gets the long term value it deserves from a decision management solution, make data analytics a part of your corporate DNA. This means getting top management involved as well as line-of-business managers.
Let’s take a look at some basic things to keep in mind:
Data has always played a critical role in day-to-day bank operations and solving business problems. Until recently, most mid-tier and smaller bank employees have missed out on the benefits of direct and prompt access to big data. But now, thanks to the growing and evolving world of data technologies, smaller financial institutions finally have the opportunity to level the playing field.
About the Author:
Ashoke Dutt is the CEO of Semantify, a pioneering semantic search technology platform company based in Chicago, Illinois. His career in global financial services spans more than 30 years and includes the launch of India’s first credit card business in 1989 at Citibank. Dutt went on to assume various other leadership roles at Citibank, including EVP, International Cards. He also served at Morgan Stanley (EVP, International Retail), and Discover Card (EVP, Marketing). Today, Dutt is an active entrepreneur and investor, serving as on boards of various start-ups and philanthropic organizations.
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