AWS Financial Services London

TP ICAP

Document Processing · IT Operations Automation · Risk Management · Security and Compliance

When Parameta attended an AWS workshop, it learned how different companies accelerate manual processes and boost productivity by using Amazon Bedrock , which facilitates the way that organizations build and scale generative AI applications.

Read the original story Explore all use cases

Parameta can then review and confirm the AI-generated assessment. “The compliance team loves the tool’s user-friendly interface,” says Rushmi Katyal, chief governance risk and business automation officer at Parameta. “It doesn’t require technical expertise; nearly anyone can upload a document and view the results in an easy-to-understand format.” With this solution, Parameta reduced the time to create a regulation database from 1 month to minutes.

Parameta, a division of TP ICAP, automated regulatory compliance reviews using generative AI on AWS, reducing review time from 1 month to minutes.

With the support of the AWS prototyping team, the company developed the solution in 3 weeks.

Reported impact

Business outcome

By improving its compliance review process, Parameta can now launch new services to clients at a fast pace. The success of this project has sparked interest in adopting AI across the firm. TP ICAP has even created a new position to oversee and nurture proofs of concept like this one. “By uploading different regulations, we can apply the tool to various products and use cases,” says Katyal. “We are creating new opportunities and possibilities for our organization using generative AI on AWS.” We are creating new opportunities and possibilities for our organization using generative AI on AWS.

Solution

For the tightly regulated financial services industry, staying compliant with regulations is a constant challenge. The compliance team at Parameta , a division of global markets and data solutions provider TP ICAP , spent hours manually reviewing the Benchmarks Regulation and assessing whether its products and documentation were up to par. Using Amazon Bedrock, Parameta developed a solution that uses generative AI to automate the compliance review process. Using Amazon Bedrock, the solution compares documents automatically to assess compliance. By improving its compliance review process, Parameta can now launch new services to clients at a fast pace. With the support of the AWS prototyping team, the company developed the solution in 3 weeks. Parameta, a division of TP ICAP, automated regulatory compliance reviews using generative AI on AWS, reducing review time from 1 month to minutes. Parameta can then review and confirm the AI-generated

Solution architecture

1 components · 1 layer

Compute
- Amazon Bedrock Runs core compute or model execution for the compliance review workload.

Evidence from the source

Now, Parameta uploads a regulation and transposes it into a database using Amazon Textract , which automatically extracts text, handwriting, layout elements, and data from scanned documents.

Parameta can then review and confirm the AI-generated assessment. “The compliance team loves the tool’s user-friendly interface,” says Rushmi Katyal, chief governance risk and business automation officer at Parameta. “It doesn’t require technical expertise; nearly anyone can upload a document and view the results in an easy-to-understand format.” With this solution, Parameta reduced the time to create a regulation database from 1 month to minutes.

Using Amazon Bedrock, Parameta developed a solution that uses generative AI to automate the compliance review process.

Using Amazon Bedrock, the solution compares documents automatically to assess compliance.

When Parameta attended an AWS workshop, it learned how different companies accelerate manual processes and boost productivity by using Amazon Bedrock , which facilitates the way that organizations build and scale generative AI applications.

With the support of the AWS prototyping team, the company developed the solution in 3 weeks.

Transparency Evidence & methodology 80/100 reference value · 88% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value80/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth10/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
3 metrics describe measurable impact.
Deployment scale5/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence88%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability23/25
11 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance8/10
The publication date comes from publisher-controlled metadata.
Source transparency9/10
2 source references document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity8/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

AWS
TP ICAP customer story

First-party
https://aws.amazon.com/solutions/case-studies/parameta-tp-icap-bedrock/

Source type
Vendor-published customer story

Published
Jan 1, 2024
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
TP ICAP
TP ICAP GROUP PLC Annual Report and Accounts 2025

First-party
https://tpicap.com/tpicap/sites/g/files/escbpb106/files/2026-04/ARA_Full%20report_2025.pdf
The 2025 key financial and performance metrics table lists 'Period end – Total headcount' as '5,444'.

Source type
Official annual report
Supports
- Company size

Date evidence

Publisher catalog date Jan 1, 2024 · AWS · First-party
Open date source

Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

Similar use cases

See all like this

AWS Apr 17, 2024 Chunghwa Telecom Telecommunications Taiwan Furthermore, Chunghwa Telecom needed a platform with robust security controls. To improve artificial intelligence (AI) data security and governance, the company migrated its generative AI projects to AWS. The first generative AI solution, the SDLC assistant, has saved developers an estimated 13 percent of their… Document ProcessingEnterprise Knowledge Search Amazon Bedrock · Amazon Polly

AWS Apr 15, 2024 InfoCert Public Sector Italy Training and deploying these models was a lengthy, costly process, which limited access to this set of capabilities to larger companies. While InfoCert was searching for a way to streamline such ML integrations, AWS… Additionally, InfoCert expects to reduce financial overhead by 80 percent for startup, development, and… Document ProcessingEnterprise Knowledge Search Amazon Bedrock

In-house Oct 20, 2025 BNY Financial Services global BNY wanted to scale AI adoption across the company without fragmented point solutions, while maintaining strong governance, risk management, compliance controls, and practical support for workflows such as payments,… 75% more AI solutions in production compared to the prior quarter Document ProcessingIT Operations Automation Contract Review Assistant · Eliza · Eliza agents