## Wilshire – AI-Powered Analytics Platform

###### Industry

###### Social media

###### Project type

###### Case study

###### Date

###### March 7th, 2024

### Project details

**Modernizing data infrastructure and enabling intelligent decision-making for one of the world’s leading investment firms.**

Wilshire is a global investment firm managing over **$100B in assets** across institutional and retail clients. We partnered with their data and product teams to modernize their analytics stack, develop AI-powered features, and improve operational efficiency across investment workflows.

## Services

- Matching Algorithm
- Recommendation Engine
- Data Strategy
- Financial Modeling

## Challenge

Wilshire needed to **revamp its legacy data systems** to meet growing client demands for faster insights, deeper transparency, and more personalized reporting. Analysts and investment teams were spending a significant amount of time on manual data wrangling and ad hoc analysis due to disconnected tools and outdated architecture.

There was also a growing need to surface insights more proactively and explore the integration of **machine learning and intelligent automation** into their internal platforms.

## Approach

We conducted a full discovery of Wilshire’s existing data architecture and collaborated with internal teams to identify high-friction points in the analytics and reporting pipeline. From there, we designed and implemented a **modernized data infrastructure**, built scalable APIs, and layered in **AI-powered insights**—including a recommendation engine for portfolio analysis and anomaly detection for risk monitoring.

## Outcome

Implemented an AI-assisted analytics dashboard in just 9 weeks, enabling analysts to process 50% more datasets per week. Decision cycles shortened from 2 weeks to 3 days, supporting multi-billion-dollar investment strategy decisions.

## What We Did

#### 01/Data Architecture Redesign

Audited and restructured data pipelines for improved reliability, scalability, and real-time accessibility.

#### 02/AI Model Integration

Implemented machine learning models for portfolio recommendation, risk flagging, and trend analysis across client portfolios.

#### 03/API Development & Dashboard Enablement

Built secure, flexible APIs to serve internal and external dashboards, enabling faster insights and customizable views.

#### 04/Automation of Reporting & Alerts

Automated routine reporting processes and added intelligent alerts for anomalies, thresholds, and market movements.