Lightico

FEBRUARY 4, 2025

Auto finance has long been a realm where speed, accuracy, and compliance collide with complexity. Within financial services, this opens the door for more autonomous underwriting, more nuanced compliance checks, and improved risk management. Limitations : Prone to errors, long turnaround times, low scalability.

Finance 52

Finance AI Compliance Machine Learning 52

SurveySensum

MARCH 10, 2025

Manage Your Risks and Compliances Conversational Analytics helps industries like finance, healthcare, and telecom maintain compliance by monitoring conversations for potential violations. How It Works: Detects compliance breaches : Flags conversations that contain regulatory risks or inappropriate language.

AI 52

AI Text Analytics Compliance Sentiment Analysis 52

Lumoa

JANUARY 8, 2024

To remind you a bit of what it is and what it does, text analytics uses transforms unstructured text into structured data that’s actually useful for business decisions. Scalability: How big can the software handle large volumes of data as your business evolves?

Sentiment Analysis 147

Sentiment Analysis Text Analytics ML Machine Learning 147

Customer Experience Matrix

MARCH 3, 2019

Informatica lays out the contrast quite nicely: they characterize MDM as limited to highly governed, structured data that delivers the “best version of the truth” about master objects (customers, products, supplier, etc.), It illustrates the difference between MDM and CDP. This is one of those questions we still get fairly often.

Unstructured Data 82

Unstructured Data Machine Learning Artificial Intelligence Government 82

Customer Experience Matrix

JUNE 17, 2019

Data warehouses are largely limited to structured data. Data lakes are not unified or easily accessible to non-technical users. Data Management Platforms are limited to summary data about mostly anonymous individuals. CRM and marketing automation systems don’t easily combine data from external sources.

Compliance 83

Compliance Engineering Start-ups Retail 83

Customer Experience Matrix

FEBRUARY 23, 2007

The information might be in structured data such as a purchase record, or it might be something less structured such as an email message or Web page. Taking these together, I think most businesses capture enough experience data to build a detailed LTV model. The classification issue boils down to tagging.

Customer Experience Management 48

Customer Experience Management Customer Experience Structured Data Compliance 48

SurveySensum

MARCH 3, 2022

Semantria Storage and Visualization (SSV) allows you to collect, store, and analyze texts to generate reports and structure data to identify trends. . Get precise and accurate analytical data to resolve customer issues and tickets quickly. . Lexalytics provides semi-custom applications to resolve compliance issues if any.

Voice of the Customer 52

Voice of the Customer VOC Sentiment Analysis Close the Loop 52