Lang.ai for Financial Services and Insurance

Your core infrastructure relies on unstructured data. Enrich and structure this untapped data
Lang.ai helps you streamline workflows with AI-based automations across your organization.
Achieved without tapping into engineers or labeling data to train an algorithm.

analytics illustration
Findings from our financial institutions use cases

1. Enhance Customer Experience by analyzing every customer touchpoint, setting up alerts and enabling real-time routing

Every customer touchpoint will be categorized with the root cause so that you have a top-down view. Customize your analysis for each product: credit cards, loans, mortgages, wire transfers, checking and saving accounts. Set up a prioritization system for high-risk issues, and real-time routing to the right team or individuals.

gif placeholder

2. Build workflows to improve efficiency and ensure compliance using support tickets, calls notes or transcripts.

Lang.ai helps you enrich all of your customer interactions with concept-based tags that you build in a visual interface. Drive more efficient operations by cutting response times and identifying the issue in real-time. Audit your processes to ensure they meet the requirements for each financial product and legislation.

product illustration

3. Process insurance claims defining your own  tagging system
(concept taxonomy)

Insurance claims are the most relevant moment in your customers’ journey, but they are messy. Lang.ai helps you process claims accurately and efficiently by allowing you to define a tagging criteria with the concepts that Lang.ai surfaces (concept taxonomy).  Avoid unnecessarily long wait times (hours or days) when minutes can be critical to retain your customers.

gif placeholder

4. Build risk models based on customer interactions like call notes or emails

Enhance your collections and credit processes by adding a new source of untapped data: customer interactions (call notes or emails or chats). If there are certain expressions indicative of risk, you’ll be able to group them visually and include a new variable in your models.

product illustration
Your benefits after using lang

90%

Time Savings on manually reviewing tickets, surveys and cases

2h

Average time to build a workflow in Lang.ai for an operations person

10M+

Monthly interactions you will structure without tapping into engineers

In our customers’ words

Alberto foto

Alberto Iriarte

Strategy and Big Data Project Lead in the Office of the CDO, CaixaBank
Lang.ai has an impressive product that we saw early on could be used as an intelligence layer on top of all our free-text data to create our classification models.
The fact that they have such an accessible UI that our CX team loved was a great signal for us to buy it from the office of the CDO so that every business area can leverage it.

We’re also excited about how we’ve been working closely with the team on their governance roadmap as their goal of making NLP accessible is proving that the amount of users and projects can grow quickly.
How much can you save with Lang.ai?

How many support tickets do you receive monthly?

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
1200
processes automated
500
agent hours saved
32000 $
cost saved
* Calculations based on...

Automate tedious work as a CIO/CTO

Be an early adopter for the technology that will take your business to the future of intelligent operations across your organization
Get a demo