Intellibonds

Idea

Introduction

Our solution is a set of modular AI Assistants (virtual workforce) that support workflow and augment decision-making of credit analysts, portfolio managers, and traders (in development). The platform learns about the users' objectives and performs tasks on behalf of the user, allowing for analytics within a click of a button. Two modules we're planning to launch this year are as follows.

1) Virtual Credit Assist:

• Credit risk predictions.

• Financial metrics forecasting.

• Risk and Investment recommendations.

• Interactive analytical dashboards with a feedback loop.

2) Virtual Portfolio Assist:

• Portfolio construction and optimisation.

• Portfolio-specific trade idea generation.

• Investment strategy development and testing (in development).

• Rebalancing and performance monitoring (in development).

Intended impact

Currently, the process of credit risk assessment and FI fund construction typically takes days, requires multiple expensive tools and is done by large teams working in silos. This makes the investment process rather expensive, which means that actively managed fixed-income funds are rather costly to run.

With passive strategies and ETFs becoming rather popular in the last five years, active fixed income asset managers suffered from substantial fee and cost pressures which led to very low margins with many of their highly customized FI investment products barely viable. This is even more problematic in the low-interest-rate environment where returns are simply limited by BoE's decision on interest rates and fees can't go any lower.

Deploying our Assistants alongside white-collar employees would create a new product line - AI-active. The new product line would allow for active fund management with a passive cost base through a combination of AI-augmented decisions and robotic process automation.

Substantial accomplishments to date

1. October 2018 - incorporated.

2. Mar 2019 - Alpha prototype launched, IntelliBonds joined Level 39 incubator.

3. July 2019 - IntelliBonds joined Fintech Sandbox accelerator and Microsoft programme for startups ($120K credit awarded).

4. Jul 2019 - Data partnerships with IHS Markit and Moody's Analytics at no charge.

5. October 2019 - Beta prototype launched.

6. January 2020 Pilot testing with Vanguard and Jupiter AM; IntelliBonds selected to present its product during the New York Fintech week; Finalist of Barclays Accelerator powered by Techstar; formally rated by Early Metrics.

7. February 2020 - Data partnerships with Refinitiv, BondRadar and S&P at no charge.

8. March 2020 - selected startup to pitch Enterprise 100 at London Business School, strategic partnership with UCL.

Monetisation strategy

Our modular products have tiered pricing planned per license, with:

1. Credit Assist priced in between £20K - £25K.

2. Portfolio Assist priced in between £25K - £35K.

3. Trader Assist priced in between £30K - £35K.

Our prices represent 1/3rd of the costs that could be saved by our client if our product is deployed in their front office, with the remaining 2/3rds of costs left to them as savings. To illustrate, our Credit Assist price was set based on the comparison of platform and labour costs associated with a single credit analyst. On average, an analyst with 5 years of experience attracts total compensation of around £100K. Additional costs include the Bloomberg license (£20K) as well as various credit research licenses and data (another £30K) revenue. To deliver minimum credit risk coverage a small asset manager would typically have to employ at least 3 analysts. Or an asset manager could opt for our platform and get the same or better access to data and insights with a price tag of £50K without a need to hire the third analyst.

Use of proceeds

Proceeds of this funding round are planned to be used in 3 ways:

1. Product development - £225k - mostly salaries.

2. Distribution channels - £50k - mostly business partnerships, workshops and commissions.

3. Legal - £25k - mostly patents, trademarks and other legal/advisory fees.